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The embodiments of the invention relate to the production of a hydrocarbon reservoir, and more specifically, methods, systems, and a non-transitory computer readable medium with a computer program stored in it to improve the simulation of a hydrocarbon reservoir.

<p>5 hydrocarbon reservoir simulation A group of hydrocarbon reservoirs.</p>

Hydrocarbon reservoir simulations can be generated to provide information regarding fluid flow and other characteristics within actual hydrocarbon reservoirs. Fluid flow simulations can be performed, for example, on models.

<p>10 In some circumstances, several simulations can be performed on a single hydrocarbon stock simulation model. Among the many advantages, running several simulations, for example, increases confidence in the simulation results and thus increases the value of the results during hydrocarbon stock analysis. A simulation is usually scheduled to run for one or more time steps—specific time intervals—as understood by people skilled in the art. The simulation is running</p>

<p>15th Multiple projects as part of the same project can sometimes be described as a simulation study.</p>

A simulation of a hydrocarbon stockpile can include both a user reaction 51 and a simulation procedure 52, as illustrated in Fig. 2a, for example. A user interaction 51 can include, for example, the upload and verification of historical data for a target hydrocarbon stockpile 53. Historical data can include, for example, actually measured data for a target hydrocarbon stockpile.

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Hydrocarbon, that is, measurements and observations collected during the discovery and production of a hydrocarbon reservoir. The Simulation 52 procedure can then control the simulation of the hydrocarbon stockpile. For example, a 52 simulator action could include starting a simulation process 54, outputting 55 time step data for the time step of the simulation process to produce 56 time step data,

<p>5 Determine if the time step is not the last step taken. If the time step is not the last time step performed 57, the simulation procedure 52 can then involve continuing the simulation 58 for another time step and then outputting the time step data 55. If the time step is the last time step then the simulation process is performed. see 57, however, the procedure for emulator 52 can then include termination of simulation 59 to produce 60 output data. A simulation procedure may include</p>

<p>10 Next on whether the simulator has more simulations (sometimes called “simulated states” or “simulated functions”) for procedure 61. If so, the simulator action 52 can then include capturing the next simulation 62 and then Then start the simulation 54. If the simulator has no more simulations for procedure 61, it can complete the simulation 63.</p>

A simulation of a hydrocarbon reservoir can include at least two important types of processes

<p>15th Fluid flow simulations in a hydrocarbon reservoir: (1) date-matching simulations and (2) prediction (or predictive) simulations. History-matching simulations can serve to validate the hydrocarbon reservoir model. Objective by producing several simulated hydrocarbon fluid flow data.The simulated hydrocarbon fluid flow data can then be compared with the simulated hydrocarbon fluid flow data.</p>

<p>20 Historical, note in real hydrocarbon reservoir. That is, date-matching simulations can calibrate a hydrocarbon reservoir model to reduce any mismatch between the model and the reservoir and for model reliability. Prediction simulations, on the other hand, can produce data regarding a predicted future hydrocarbon fluid flow. That is, engineers can use prediction simulations to answer questions about what happened in different possible development scenarios. In some</p>

<p>25 Circumstances, prediction simulations can be part of an optimization problem, and an engineer can </p>

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Simulation by running multiple simulations with results in a valid solution space to choose the simulation process most appropriate for a development objective. Multiple prediction simulations can thus be used to fine-tune development strategies to obtain objectives related to hydrocarbon storage development, for example. High quality hydrocarbon reservoir simulation models can be desirable because

<p>5 These models produce more accurate predictions. It is noted that, date-matching simulations can affect prediction simulations, however, because date-matching simulations can be used to improve the quality of a hydrocarbon reservoir simulation model after use for prediction simulations. Thus, date matching can be an important part of a hydrocarbon stockpile simulation</p>

.hydrocarbon reservoir simulation

<p>10 Furthermore, date matching is an optimization problem. One of the main goals of date matching can be used, for example, to validate a numerical hydrocarbon stock simulation model by minimizing differences between the numerical solution—the simulator output—and the field field historical pressure, production, and injection data. data. This validation process can lead to management and quantification</p>

<p>15th Better management and quantification for simulation model uncertainties. Finally, a date-matched numerical model can be used for forecasting studies and estimation assessments of the hydrocarbon domain. Figure 2b shows an example of the date matching method according to prior art. As shown in Figure 2b, for example, a geological model 71 can have a very large weight 72 to a simulation model 73. A fluid flow simulation 74 can then be run. Production data 75 are used,</p>

<p>20 To clarify whether the corresponding objective function can be determined 76. The objective function of a simulation study can be a function of a forecasting study, for example, to increase oil production, in some circumstances. Whereas in another example, a target function can be used for a history-matching study to develop a simulation model of a hydrocarbon reservoir that closely approximates the characteristics of a real hydrocarbon reservoir from its models. Thus, a target function can relate to the differences between the simulated output-simulated fluid flow output data.</p>

<p>25 74 flow simulation, i.e., fluid flow simulation results- and production data 57, eg. </p>

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More specifically, an objective function can be used to determine whether an acceptable match between the results of a fluid flow simulation and historical data has been observed, that is, measured data. Furthermore, a match can be determined based on some predetermined acceptance criteria. Defining an objective function can be "yes" when an acceptable match is reached, for example, when the difference between the output of a simulated stream

<p>5 Fluid 74 and production data 75 production data below the predetermined level. Conversely, the determination of a target function can be "no" when the difference between the fluid flow simulation output 74 and the production data 75 is greater than the predetermined level, for example. As illustrated in Figure 2b, for example, if the interview is Objective function 76, method 78 can be discontinued. If objective function 76 is not met, manual optimization can occur 77 and feed back to the simulation model 73.</p>

<p>10 Unlike manual date matching, Assisted History Matching (AHM) automates the optimization process using the most recent approved optimization algorithms in the industry. AHM is a class of simulation problems that allows reservoir simulation engineers to alter many variables simultaneously. Simulated, automating operations, able to be a better document for different date matching scenarios.</p>

<p>15th Using the AHM technique, for example, is shown in Figure 2c. As shown in Figure 2c, for example, a geological model 81 can have a very large volume 82 to produce a simulation model 83. A fluid flow simulation 84 can then be run to run on a simulation model 83. Next, a fluid flow simulation 84 can be run. 85 production data, whether 86 interviewed objective functions can be identified. If objective function 86 is met, process 88 can be matched. If objective function 86 is not met, it can start</p>

<p>20 Auxiliary Improvement Process 87 and feeds back to Geological Model 81.</p>

J describes. Holden, in "A Load Balancing Strategy for Oil Reservoir Modeling

<p>(2004) Cover A Load Balancing Strategy for Oil Reservoir Modeling</p>

Apply periodic Parallel Message Parsing Interface (MPI) transformation modeling to a set of tasks to reduce execution time by optimizing load balancing.

<p>25 Termination criteria using a fixed time period of simulated time </p>

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and fixed oil (a decrease in oil production below a threshold value). However, the techniques described in the Holden document require a significant amount of time and resources and do not reduce the number of simulations run for an entire scheduled duration.

General description of the invention

<p>5 Despite all this, date matching - even assisted date matching - still has several significant drawbacks. For example, date matching with help can be quite time-consuming. In some circumstances, for example, date matching can be run with the help of more than half the time and effort of hydrocarbon reservoir simulation engineers. In addition, the continued use of traditional practices, such as manual and assisted date matching, is increasingly impractical because models</p>

<p>10 Hydrocarbon reservoir simulation is always growing in scale and complexity. Moreover, hydrocarbon reservoir simulations continue to run on increasingly shorter timelines. At least one important problem is related to time matching, and moreover, many simulations are required to produce significant results. In fact, hundreds of simulations can be provided in some cases for a single assisted date matching process. can therefore</p>

<p>15th Running many simulations requires significant amounts of time and computing resources. Thus, the advantages and disadvantages of matching to history are often countered by its demands for a large amount of time and resources.</p>

Likewise, prediction simulation can have several drawbacks. Forecast simulations can also take a significant amount of time, for example, when they are part of projects with a timeline.

<p>20 Short. Furthermore, forecast simulations can also use a significant amount of an entity's sources. For example, in some cases the entity may use prediction simulations to investigate potential cycles of the procedure for developing a hydrocarbon stockpile. To help achieve it, the entity can run one or more simulations for each option of potential courses of action. Thus, when an entity considers many options, many options can be made</p>

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forecast simulations. Rather than date matching, prediction simulations can therefore require large amounts of time and resources.

After recognizing the problems and sources of problems associated, for example, with date matching and prediction simulations, and also recognizing the solutions to those problems, the applicants here reveal models

<p>5 For systems, a non-transitory computer-readable medium with one or more computer programs stored in it, and methods to be executed by the computer</p>

To improve hydrocarbon reservoir simulation for a range of hydrocarbon . reservoirs

.reservoirs

For example, an embodiment of the invention may include a system to improve the simulation of a hydrocarbon reservoir

<p>10 A group of hydrocarbon reservoirs. A system according to the model of the invention may include one or more processors that together have a limited and predetermined built-in computing power. Limited and predetermined embedded computing capacity, for example, may be available in response to the use of a simulation. A system can also have one or more I/O units in contact with one or more processors and a non-buffering memory medium in contact with one or more processors.</p>

<p>15th One or more processors. A memory medium, for example, can have computer-readable instructions stored in it. Moreover, when computer-readable instructions are executed, they cause the system to perform a series of steps.</p>

According to some embodiments, the steps can include initiation, for each group of reservoirs

hydrocarbons, all from a group of fluid flow simulations, eg. can be done

<p>20 Configure a set of fluid flow simulations to calibrate one or more hydrocarbon reservoir simulation models associated with each corresponding set of hydrocarbon reservoirs. Thus, a set of fluid flow simulations can thus select a set of simulations corresponding to the date. Each of a set of date-matching simulations can be configured to run for a corresponding predetermined time period, and each corresponding predetermined time period can include one or more of the</p>

<p>25 time steps. Moreover, each of a set of simulations can also be configured</p>

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Date Match Outputs a simulation dataset in response to running the corresponding date-matched simulation after each of one or more time steps. Each simulated data set can contain one or more simulated data values. Each of the corresponding group of hydrocarbon reservoirs can have a group of hydrocarbon wells, and a group of hydrocarbon wells can

<p>5 The hydrocarbons are specifically together a hydrocarbon field within each of the corresponding group of hydrocarbon reservoirs. Each of one or more simulated data values ​​can be configured to be associated with one group of hydrocarbon wells.</p>

The steps the system performs when computer-readable instructions are executed may also include termination, for each of the group of hydrocarbon reservoirs, each of the first set of one or more of the

<p>10 A set of simulations matching a date before completing the corresponding predetermined period of time. Termination of the first set of date-matching simulations can be in response to the output after a time step when each of the first set of date-matching simulations has a simulation error measurement of the hydrocarbon field. Furthermore, the termination of the first set of operations can be by continuation of a second set of one or more other set of identical simulations.</p>

<p>15th for history. Each of the second set of date-matching simulations could lack a hydrocarbon field simulation error measurement that exceeds the predetermined simulation termination error tolerance. Furthermore, the variance of a predetermined simulation termination error can be related to the preset values ​​of one or more threshold variables.</p>

In addition, according to another model, for example, both groups can be terminated

<p>20 The first of date-matched simulations when more than a predetermined number of hydrocarbon wells in each of the first set of date-matched simulations has a simulated hydrocarbon well error measure that exceeds the predetermined well termination error tolerance. In this example, each of the second set of simulations corresponding to the date - as the system continues - has fewer than the predetermined number of hydrocarbon wells so that each has a simulated well error measurement</p>

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Hydrocarbon exceeds a predetermined well termination error tolerance. The predetermined number of hydrocarbon wells can, for example, relate to predetermined values ​​of one or more threshold variables.

In each of the representative models, the predetermined finite embedded computing power can be configured to have more processing availability when the first set of matching simulations is terminated

<p>5 for history. Thus, termination of the first set of date-matching simulations can thus increase the availability of processing fluid flow simulations within the predetermined, finite built-in computing power of one or more other fluid flow simulations being run and reduce the total runtime of the hydrocarbon reservoir simulation.</p>

For example, each of the second set of date-matching simulations can run

<p>10 Coinciding with another one or more of the second set of simulations corresponding to the date after</p>

Finish each of the first set of simulations matching the date. Furthermore, a set of date-matched simulations for each set of hydrocarbon reservoirs can include a predetermined number of date-matched simulations, and a sum of predetermined numbers of date-matched simulations of a set of hydrocarbon reservoirs that can define a total number of

<p>15th Predetermined simulations matching the date. Additionally, the completion of a total number of simulations matching a predetermined date can be scheduled to require a predetermined amount of time and thus an expected total completion time. Termination of the first set of date-matching simulations for each group of hydrocarbon reservoirs can advantageously push a total number of predetermined date-matching simulations to terminate before the end of the total time</p>

<p>20 Expected completion.</p>

In some systems according to an embodiment of the invention, instructions in the non-buffered memory medium, when executed, can also cause the system to take additional steps. For example, additional steps could include initiating, in response to termination of a date-matching simulation, another different date-matching simulation by using one or more of one or more processors

<p>25 It has overprocessing availability in response to the termination of the simulation matching the date to enable it to start </p>

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too early for the other date-matching simulation. Furthermore, a set of date-matching simulations can be configured to calibrate one or more hydrocarbon reservoir simulation models associated with each of the corresponding set of hydrocarbon reservoirs by comparing distinct reservoir values ​​measured for each of the corresponding set of hydrocarbon reservoirs. In addition, it can be specified

<p>5 A measurement of the hydrocarbon field simulation error of a date-matched simulation after a time step in response to a comparison of one or more simulation data values ​​for the simulation data set associated with a date-matched simulation after a time step and one or more of a set of distinct reservoir values ​​measured for each of the corresponding set of hydrocarbon reservoirs. Similarly, a hydrocarbon well simulation error measurement can be specified for a date-matched simulation after a time step in response to a comparison to one or more</p>

<p>10 Simulation data values ​​for the simulation data set associated with the simulation corresponding to the date after the time step and one or more set of distinct reservoir values ​​measured for each of the corresponding set of hydrocarbon reservoirs.</p>

A system for improving hydrocarbon reservoir simulation of a group of hydrocarbon reservoirs according to another embodiment may also include, for example, one or more processors that together have the ability to

<p>15th Limited and predetermined embedded computing. Limited and predetermined embedded computing power can be available in response to the use of a simulation. A system can also have one or more I/O units in contact with one or more processors, as well as a non-buffering memory medium in contact with one or more of one or more processors. A memory medium can have computer-readable instructions stored in it that when executed prompt the system to perform a series of steps.</p>

<p>20 The steps may include, for example, for each group of hydrocarbon reservoirs, each of a set of fluid flow simulations. A set of fluid flow simulations can be configured to predict the future behavior of each corresponding set of hydrocarbon reservoirs. Thus, a set of fluid flow simulations can thus define a set of prediction simulations. Each set of prediction simulations can be configured to run for a corresponding predetermined period of time</p>

<p>25 and one or more time steps. Each of the set of simulations can also be configured</p>

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Forecasting Outputs a simulation dataset in response to a corresponding prediction simulation operation after each of one or more time steps. Each simulated data set can contain one or more simulated data values. Each corresponding set of hydrocarbon reservoirs can have a set of hydrocarbon wells, and each of one or more simulated data values ​​can be

<p>5 Prepared to be attached to one of a group of hydrocarbon wells.</p>

The steps may also include terminating, for each group of hydrocarbon reservoirs, each of the first set of one or more set of forecast simulations before the corresponding predetermined period of time is completed, for example. Termination of the first set of prediction simulations can be in response to the output after a time step when one or more of the one or more data values

<p>10 Simulation of the simulation data set associated with the first set of prediction simulations after the time step outside of the termination tolerance of the simulated data values. Furthermore, the first set of prediction simulations can be terminated when the second set of one or more other set of prediction simulations continues. One or more simulation data values ​​for the simulation data set associated with each of the second set of prediction simulations can be included after the time step</p>

<p>15th Inside the tolerance of termination of the simulated data values. Furthermore, the variance of termination of the simulated data values ​​can relate to the predetermined values ​​of one or more threshold variables. In addition, a predetermined finite built-in computing capacity can be configured to have increased processing availability when the first set of prediction simulations is terminated. Completing the first set of prediction simulations can thus increase processing availability for fluid flow simulations within computing power</p>

<p>20 finite and predetermined combined into one or more other fluid flow simulations that operate and reduce the total runtime of the hydrocarbon stockpile simulation.</p>

In some circumstances, each of the second set of time prediction simulations can work

With another one or more of the second set of prediction simulations after each of the first set of prediction simulations is finished. In addition, a group of operations can include

<p>25 Forecast simulations for each group of hydrocarbon reservoirs based on a number of specific prediction simulations </p>

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in advance. Addition of predetermined numbers of simulations for a set of hydrocarbon reservoirs can specify the total number of predetermined forecast simulations. Furthermore, the completion of a total number of predetermined forecast simulations can be scheduled to require a predetermined amount of time and thus determine an expected total completion time. It can cause the first group to end Z of

<p>5 Forecast simulations for each group of hydrocarbon reservoirs are useful in prompting an operation from the total number of predetermined forecast simulations to terminate before the end of the total expected completion time.</p>

In addition, a set of prediction simulations can be configured to predict the future behavior of each corresponding set of hydrocarbon reservoirs by using one or more hydrocarbon reservoir simulation models associated with each corresponding set of hydrocarbon reservoirs. maybe

<p>10 One or more hydrocarbon reservoir models are calibrated by using a set of measured characteristic reservoir values ​​and thus one or more calibrated hydrocarbon reservoir simulation models. Furthermore, each set of forecast simulations can be associated with an additional course of procedures to develop each of the corresponding set of hydrocarbon reservoirs associated with a corresponding forecast simulation and thus define a development strategy. Predetermined values ​​can also be associated with one or more</p>

<p>15th Threshold variables and inequality of termination of simulated values ​​data with one or more strategic outcome values</p>

Predetermined for one or more development strategies.

An embodiment of the invention may also include, for example, a computer-readable non-transient medium with one or more computer programs stored in it that can be operated by one or more processors to enhance the hydrocarbon reservoir simulation of a set of reservoirs.

<p>20 hydrocarbon. Furthermore, one or more computer programs can contain a set of instructions that, when executed by one or more processors, prompt one or more processors to perform a series of operations. The processes can include, for example, the initiation of, for each set of hydrocarbon reservoirs, each of the set of fluid flow simulations. The set of fluid flow simulations can be configured to calibrate one or more reservoir simulations</p>

<p>25 A hydrocarbon associated with each of the corresponding group of hydrocarbon reservoirs. Therefore, it can thus</p>

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A set of fluid flow simulations can define a set of simulations corresponding to the date. Furthermore, each of a set of date-matching simulations can be configured to run for a corresponding predetermined time period, and each corresponding predetermined time period can include one or more time steps. Each of a set of simulations can also be configured

<p>5 Date Match Outputs a simulation dataset in response to running the corresponding date-matched simulation after each of one or more time steps. Each simulated data set can contain one or more simulated data values. Each corresponding group of hydrocarbon reservoirs can have a group of hydrocarbon wells, and a group of hydrocarbon wells that together can define a hydrocarbon field within each of the corresponding group of hydrocarbon reservoirs. 10 Each of one or more simulated data values ​​can be configured to be associated with one of the wells</p>

hydrocarbon.

The operations, for each group of hydrocarbon reservoirs, may also include each of the first set of one or more of a set of simulations dated prior to completion of the corresponding predetermined period of time. The termination of the first set of matching simulations can be

<p>15th The date in response to the output after a time step when each of the first set of date-matching simulations has a hydrocarbon field simulation error measurement that exceeds the termination error tolerance of a predetermined simulation. Termination of the first set of date-matching simulations can also be while a second set of date-matching simulations is in progress for one or more of a set of date-matched simulations. Each simulation can lack date matching for the second set of simulation error measurement</p>

<p>20 For a hydrocarbon field that exceeds the predetermined simulation termination error tolerance. Furthermore, the predetermined simulation termination error variance can relate to predetermined values ​​of one or more threshold variables.</p>

In an example according to another model, each of more than a number of predetermined hydrocarbon wells in each of the first set of match-date simulations can have a simulated well error measurement

<p>25 A hydrocarbon that exceeds a predetermined simulation termination error tolerance. On the other hand, it can</p>

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Each of the second set of date-matching simulations has a smaller number of predetermined number of hydrocarbon wells such that each has a hydrocarbon well simulation error measure that exceeds the predetermined simulation termination error tolerance. The predetermined number of hydrocarbon wells and the variance of the termination error of a predetermined simulation can relate to predetermined values ​​of one or more of the 5 threshold variables.

The combined finite, predetermined, embedded computing power of one or more processors can be configured to have increased processing availability when the first set of date-matching simulations is terminated, for example. Limited and predetermined embedded computing power can be available in response to the use of a simulation. As a result, the first set of simulations can thus

<p>10 Matching to a date increases the availability of processing for fluid flow simulations within the predetermined and limited built-in computing power of one or more other fluid flow simulations that are running. Furthermore, termination of the first set of date-matching simulations can reduce the total runtime of the hydrocarbon stockpile simulation.</p>

In addition, in some circumstances, each of the second set of operations can operate

<p>15th A date-matching simulation in conjunction with one or more other date-matching simulations after each of the first set of date-matching simulations has been completed. Furthermore, a set of date-matching simulations for each group of hydrocarbon reservoirs can include a number of predetermined date-matching simulations. Adding a predetermined number of date-matching simulations to a set of hydrocarbon reservoirs can determine a predetermined total number</p>

<p>20 From simulations matching the date. The completion of a predetermined total number of simulations matching the date can be scheduled to request a predetermined amount of time and thus an expected total completion time. Termination of the first set of date-matched simulations for each set of hydrocarbon reservoirs can thus prompt an operation for a predetermined total number of date-matched simulations to terminate before the end of an expected total completion time.</p>

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In a non-temporary computer-readable medium having one or more computer programs stored in it according to an embodiment of the invention, the set of instructions, when executed by one or more processors, may also prompt one or more processors to perform additional operations. Operations can also include, for example, a start, in response to the termination of a date-matched simulation, a process

<p>5 Various other date-matching simulations by using one or more of the one or more processors that have more processing availability in response to the date-matching simulation, thus ensuring the early start of another date-matching simulation. In addition, a set of matching simulations can be configured to calibrate one or more hydrocarbon reservoir simulation models associated with each corresponding set of hydrocarbon reservoirs by comparing</p>

<p>10 With a hydrocarbon group, a characteristic reservoir feedstock is measured for each of the corresponding group of hydrocarbon reservoirs. A simulation error measurement of a hydrocarbon well can be specified for a date-matched simulation after a time step and one or more set of distinct reservoir values ​​measured for each of the corresponding set of hydrocarbon reservoirs.</p>

In a non-temporary computer-readable medium that has one or more computer programs stored in it to improve

<p>15th Hydrocarbon reservoir simulation of a set of hydrocarbon reservoirs In another embodiment, one or more computer programs may contain a set of instructions that, when executed by one or more processors, prompt one or more processors to perform a series of operations. that </p>

The operations include, for example, initiating, for each group of hydrocarbon reservoirs, each of a set of fluid flow simulations. A set of fluid flow simulations can be configured

<p>20 To predict the future behavior of each of the corresponding group of hydrocarbon reservoirs. The set of fluid flow simulations can thus define a set of prediction simulations. Each of a set of forecast simulations can be configured to run for a corresponding predetermined time period, and each corresponding predetermined time period can include one or more time steps. Each of the prediction simulations can also be configured to output a simulation dataset in response to a process.</p>

<p>25 A corresponding prediction simulation after each of one or more time steps. can include all</p>

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A simulated data set contains one or more simulated data values. Each corresponding group of hydrocarbon reservoirs can have a set of hydrocarbon wells, and each of one or more simulated data values ​​can be configured to be associated with one of the hydrocarbon wells. Operations can also include, for example, a termination, for each group of reservoirs

<p>5 Hydrocarbons, each of the first set of one or more of a set of prediction simulations before a corresponding predetermined time period is completed. The termination of the first set of prediction simulations can be in response to the output after a time step when one or more of the one or more simulation data values ​​for each of the simulation data values ​​associated with the first set of prediction simulations after the time step is outside the termination tolerance of the simulation data values . The group can also be terminated</p>

<p>10 The first of the prediction simulations is when a second set of one or more other set of prediction simulations continues. One or more simulation data values ​​of the simulation data set that are related to each of the second set of prediction simulations after the time step can be included within the termination tolerance of the simulation data values. Simulation data values ​​can relate to predetermined values ​​of one or more threshold variables. Built-in computing power can be configured</p>

<p>15th Limited and predetermined for one or more processors to have additional processing availability when the first set of prediction simulations is completed. Limited and predetermined embedded computing power can be available in response to the use of a simulation. Thus, termination of the first set of prediction simulations can thus increase the processing availability of fluid flow simulations within an aggregate, limited, pre-determined computational capacity for one or more fluid flows that are run. bonus</p>

<p>20 Furthermore, termination of the first set of predictions can reduce the total runtime of the hydrocarbon stockpile simulation.</p>

In some circumstances, each of the second set of synchronization prediction simulations may run with one or more of the second set of prediction simulations after each of the first set of simulations has been completed for each set of hydrocarbon reservoirs which may include a number of

<p>25 Predetermined prediction simulations. Can set sum predetermined number of simulations</p>

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Forecasting for a group of hydrocarbon reservoirs totals a predetermined number of forecast simulations, and the completion of a predetermined number of forecast simulations can be scheduled to require a predetermined amount of time and thus a total expected completion time. Finishing the first set of prediction simulations for each group of hydrocarbon reservoirs advantageously drives the process to a predetermined total number

<p>5 of forecast simulations to finish before the end of the total expected completion time.</p>

A model according to the invention may also include, for example, a computer-implemented method for improving the simulation of a hydrocarbon reservoir for a group of hydrocarbon reservoirs. For example, a method may include initiating, for each group of hydrocarbon reservoirs, each of a set of fluid flow simulations. A set of fluid flow simulations can be configured for one or more calibrations

<p>10 of hydrocarbon reservoir simulation models associated with each of the corresponding group of hydrocarbon reservoirs, eg. Thus, a set of fluid flow simulations can thus define a set of simulations corresponding to history. Each of a set of date-matching simulations can be configured to run for a corresponding predetermined time period, and each corresponding predetermined time period can include one or more time steps. Moreover, each . can also be configured</p>

<p>15th From a set of date-matched simulations to output a simulation dataset in response to running the corresponding date-matched simulation after each of one or more time steps. Each simulation dataset can contain one or more simulation data values. Each group corresponding to hydrocarbon reservoirs can have a group of hydrocarbon wells, and a group of hydrocarbon wells can together define a hydrocarbon field within each group</p>

<p>20 Correspondence to hydrocarbon reservoirs. Each of one or more simulated data values ​​can be configured to be associated with one group of hydrocarbon wells.</p>

A method may also include terminating, for each group of hydrocarbon reservoirs, each of the first set of one or more of a set of date-matched simulations before completing a corresponding predetermined time period. The first set of matching simulations can be completed

<p>25 To date during the continuation of the second set of one or more other set of simulations </p>

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date matching. The termination of the first set of date-matched simulations can also be in response to the output after the time step when each of the first set of date-matched simulations has a hydrocarbon field simulation error measurement that exceeds a predetermined simulation termination error tolerance. Each of the second set of matching simulations can be lacking

<p>5 For the date to measure a hydrocarbon field simulation error that exceeds the predetermined simulation termination error tolerance. The variance of the predetermined simulation termination error can relate to the predetermined values ​​of one or more threshold variables.</p>

The first set of date-matched simulations can be terminated according to another model when more than a number of predetermined hydrocarbon wells in each of the first set of 10 date-matched simulations have a simulated hydrocarbon well error measure that exceeds the termination error tolerance

predetermined well. Conversely, each of the second set of match-date simulations can have less than the predetermined number of hydrocarbon wells so that each has a simulation error measurement of the hydrocarbon well that exceeds the predetermined well termination error tolerance. The predetermined number of hydrocarbon wells and the predetermined well termination error variance can relate to predetermined values ​​15 of one or more of the threshold variables.

Furthermore, limited and predetermined embedded computing power of one or more processors can be configured to have increased processing availability when the first set of date-matching simulations is terminated. . Can thus finish the first set of matching simulations

<p>20 The date may increase processing availability for fluid flow simulations within a limited, pre-determined, aggregated computing power of one or more other fluid flow simulations that are running. As a result, termination of the first set of date-matching simulations can beneficially reduce the total runtime of a hydrocarbon stockpile simulation.</p>

For example, in some circumstances, each of the second set of operations can operate

25 Simulation corresponding to the date in time with one or more other groups of operations

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Date-matched simulations after each of the first set of date-matching simulations is completed. Furthermore, a set of date-matching simulations for each group of hydrocarbon reservoirs can include a predetermined number of date-matching simulations for each of the date-matching simulations. Can set the sum of predetermined numbers for date-matching simulations for a set of

<p>5 Hydrocarbon storages Complete a total of predetermined number of simulations matching the date. Could</p>

The completion of a predetermined total number of simulations matching the date is scheduled to require a predetermined amount of time and thus an expected total completion time. In addition, termination of the first set of date-matching simulations for each group of hydrocarbon reservoirs can cause the termination of a predetermined total number of date-matching simulations before

<p>10 The end of the total expected completion time.</p>

In some cases, a method can also include initiating, in response to the termination of a date-matched simulation, a different other date-matching simulation by using one or more of the one or more processors that have over-process availability in response to the termination of the date-matched simulation, to enable Hence from the early start of another chronological simulation. Furthermore it,

<p>15th A set of date-matching simulations can be configured to calibrate one or more hydrocarbon reservoir simulation models associated with each corresponding set of hydrocarbon reservoirs by comparing a set of distinct reservoir values ​​measured for each corresponding set of hydrocarbon reservoirs. In addition, a hydrocarbon field simulation error measure can be specified for a date-matched simulation after a response time step for comparing simulation data values ​​for one or more sets</p>

<p>20 Simulation data associated with the simulation corresponding to the date after the time step and one or more set of distinct reservoir values ​​measured for each of the corresponding set of hydrocarbon reservoirs.</p>

A method for simulating a hydrocarbon reservoir of a set of hydrocarbon reservoirs according to another embodiment may include, for example, initiating, for each set of hydrocarbon reservoirs, each of a set of fluid flow simulations. A set of fluid flow simulations can be configured to predict behavior

<p>25 The future of each of the corresponding group of hydrocarbon reservoirs, and a set of simulations of the flow </p>

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Fluid which can therefore define a set of simulation predictions, as a result. Each set of forecast simulations can be configured to run for a corresponding predetermined time period. Each corresponding predetermined time interval can include one or more time steps. Each set of prediction simulations can also be configured to output a simulated data set in response to an operation

<p>5 A prediction simulation after each of one or more corresponding time steps. Each simulated data set can contain one or more simulated data values. Each group corresponding to a hydrocarbon reservoir can have a group of hydrocarbon wells, and each of one or more simulated data values ​​can be configured to be associated with one of the hydrocarbon wells.</p>

<p>10 The method may then include terminating, for each group of hydrocarbon reservoirs, each of a first set of one or more set of forecast simulations before completing the corresponding predetermined period of time while a second set of one or more other set of forecast simulations continues . Termination of the first set of prediction simulations can be in response to the output after a time step when one or more of the one or more simulated data values ​​of a data set</p>

<p>15th Simulations associated with each of the first set of prediction simulations after the time step outside of the termination tolerance of the simulated data values. One or more simulation data values ​​for the simulation data set associated with each of the second set of prediction simulations after the time step, on the other hand, can be included within the termination tolerance of the simulation data values. The variance of termination of simulated data values ​​can relate to predetermined values ​​of one or more threshold variables. Could</p>

<p>20 That a predetermined, limited, embedded computing power of one or more processors is configured to increase processing availability when the first set of prediction simulations is completed. Limited and predetermined embedded computing power may be available in response to the use of a simulation. Termination of the first set of prediction simulations can thus increase processing availability for fluid flow simulations within a predetermined, finite embedded computing power aggregated into one or more other</p>

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Fluid flow simulations are working. Thus, termination of the first set of prediction simulations can thus beneficially reduce the total runtime of the hydrocarbon stockpile simulation.

In addition, each of the second set of coincidence prediction simulations can run with one or more other set of prediction simulations after each set is terminated.

<p>5 The first of the prediction simulations. Furthermore, a set of forecast simulations for each set of hydrocarbon reservoirs can include a predetermined number of forecast simulations, and a sum of predetermined numbers of forecast simulations for a set of hydrocarbon reservoirs can specify the total number of predetermined forecast simulations . The completion of the total number of predetermined forecast simulations can be scheduled to require a predetermined amount of time and thus determine a total of 10 expected completion times. It can finish the first set of simulations for each set</p>

The hydrocarbon storages drive the process advantageously for the total number of forecast simulations to terminate before the end of the total expected end time. In some circumstances, a set of prediction simulations can be configured to predict the future behavior of each corresponding set of hydrocarbon reservoirs by using one or more hydrocarbon reservoir simulation models associated with each set

<p>15th Correspondence to hydrocarbon reservoirs. One or more hydrocarbon reservoir models may be calibrated by using a set of distinct measured reservoir values ​​and thus one or more calibrated hydrocarbon reservoir simulation models. Furthermore, each of the set of prediction simulations can be associated with an additional course of procedures to develop each of the corresponding set of hydrocarbon reservoirs associated with the corresponding prediction simulation and thus define a development strategy. maybe</p>

<p>20 The predetermined values ​​of one or more threshold variables and the inequality of termination of simulated data values ​​are associated with one or more predetermined strategic outcome values ​​for one or more development strategies.</p>

Brief explanation of the drawings

These features, characteristics, and merits of the present invention will be better understood by looking at the following description, safeguards, and accompanying drawings. However, it is noticeable that the graphics

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It only describes several models of invention and is therefore not intended to limit the scope of the invention that allows for equivalent effective models.

Figure 1 is a representative schematic of a hydrocarbon reservoir simulation optimization system for one of the embodiments of the invention.

Figure 2a is a representative flowchart of a method according to the previous field.

<p>5 Figure 2b is a representative flowchart of a method according to the previous field.</p>

Figure 2c is a representative flowchart of a method according to the previous field.

Figure 3 is a representative diagram of the use of a predetermined finite embedded computing power by simulating a time-running hydrocarbon stock according to one of the invention embodiments.

Figure 4 is a representative schematic of a method for optimizing a hydrocarbon reservoir simulation according to a model

<p>10 Sister, take care.</p>

Figure 5 is a representative diagram of a method for improving hydrocarbon reservoir simulation according to an embodiment of the invention.

Figure 6 is a representative diagram of a method for improving hydrocarbon reservoir simulation according to an embodiment of the invention.

<p>15th Figure 7 is a graph of hydrocarbon storage simulation data for one of the models of the invention.</p>

Figure 8 is a representative diagram of a method for improving hydrocarbon reservoir simulation according to an embodiment of the invention.

Figure 9 is a representative scheme of a method for improving hydrocarbon reservoir simulation according to another embodiment of the invention.

<p>20 Figure 10 is a representative diagram of a method for improving hydrocarbon reservoir simulation according to another embodiment of the invention.</p>

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Detailed description:

In order to better understand each of the features and advantages of methods, systems, non-temporary computer-readable medium in which a computer program is stored according to the present invention, as well as others, which will become clear, in more detail, a more specific description of the models of methods, systems, middle is not

<p>5 A computer-readable timer that has a computer program stored in it for the current invention that has been disclosed</p>

About it briefly previously by referring to samples of it, as they are clarified in the attached drawings, which form part of this description. However, it should be noted that the drawings only show various models of roads, systems, and non-temporary computer-readable medium in which a computer program is stored according to the present invention and should therefore not be considered constraining models of roads, systems,

<p>10 A computer-readable non-temporary medium in which a computer program is stored for the current invention</p>

It can include other effective models as well, and the following tables show the number of matching operations and the simulation error melting: Table 1 shows the fifty checks of simulations that match the date and Table 2 shows the fifty refinements of the simulations matching the date

Table 1:

<tr><td><p>Differential finish simulation process</p></td><td><p>The number of compatible operations</p></td></tr><tr><td><p>10</p></td><td><p>45</p></td></tr><tr><td><p>20</p></td><td><p>32</p></td></tr><tr><td><p>25</p></td><td><p>27</p></td></tr><tr><td><p>30</p></td><td><p>21</p></td></tr>

15th Table 2:

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<tr><td><p>Differential finish simulation process</p></td><td><p>The number of compatible operations</p></td></tr><tr><td><p>10</p></td><td><p>21</p></td></tr><tr><td><p>20</p></td><td><p>1</p></td></tr><tr><td><p>25</p></td><td><p>1</p></td></tr><tr><td><p>30</p></td><td><p>1</p></td></tr>

The embodiments of the invention may include systems, a non-temporal computer-readable medium with one or more computer programs stored in it, and computer-implemented methods to improve the simulation of a hydrocarbon reservoir for a group of hydrocarbon reservoirs. Each group of hydrocarbon reservoirs can have a group of hydrocarbon wells, and a group of hydrocarbon wells for each group of hydrocarbon reservoirs together can define the hydrocarbon field within a hydrocarbon reservoir. In addition, models can relate to time-matching and prediction simulations of hydrocarbon reservoir properties and fluid behavior and flow within hydrocarbon reservoirs.

10

15

For example, a model for date-matching simulations could include a system for optimizing hydrocarbon stockpile simulations for a set of hydrocarbon reservoirs. Each group of hydrocarbon reservoirs can have a set of hydrocarbon wells, and a set of hydrocarbon reservoirs together can also define a hydrocarbon field within a hydrocarbon reservoir. A system according to one of the models that is applicable to other models may also include one or more 101 processors which together have a limited and predetermined embedded computing power, as shown in Figure 1, for example. A predetermined limited and built-in computing capacity, for example, could be available in response to the use of a simulation. That is, increased use of the simulation process can reduce the availability of computing power. A system can also have one or more I/O 104 connected to one or more 101 processors.

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Furthermore, a system can also have a non-cache 105 memory medium in contact with one or more of the one or more 101 processors. The 105 memory medium can have, for example, computer-readable instructions 106 in which it is stored. When a computer-readable instruction 106 is executed, it can prompt the system to perform a series of steps. can include

<p>5 The step, according to one model, is to start - for each of the set of hydrocarbon reservoirs - each of a set of fluid flow simulations. A set of fluid flow simulations can be a set of fluid flow simulations. Fluid flows can be configured to calibrate one or more calibrations of one or more 121 hydrocarbon reservoir simulation models associated with each of the corresponding set of hydrocarbon reservoirs. Calibration can relate specifically to a date-matching process, for example 10, as people skilled in this field will understand. As a result, it can thus be determined</p>

Fluid Flow Simulation Set A set of date-matched simulations. Each set of simulations matching a date can also be configured to run for a corresponding predetermined time period. In addition, each corresponding predetermined time period can include, for example, one or more time steps. Moreover, each . can be initialized

<p>15th Date-matched simulation set to output a simulation dataset in response to running the corresponding date-matched simulation after each of one or more time steps. Depending on a model, each simulated data set can contain one or more simulated data values. In addition, each corresponding group of hydrogen reservoirs can have a group of hydrocarbon wells, and a group of carbon wells together can define a hydrocarbon field</p>

<p>20 Within each of the corresponding group of hydrocarbon reservoirs. Each of one or more simulation data values ​​can be configured to be associated with one group of hydrocarbon wells. Furthermore, simulation data can include hydrocarbon well data such as production, injection, or pressure data.</p>

It can also include the steps the system takes when computer-readable instructions are executed

106 On termination, for each of the group of hydrocarbon reservoirs, for each of the first group of one or

25 More than a set of simulations matching the date before completing a corresponding predetermined time period,

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In response to output after a time step, a second set of one or more other set of date-matching simulations proceeded.

For example, each of the first set of date-matching simulations can be terminated when each of the first set of date-matching simulations has a simulation error measure

<p>5 For a hydrocarbon field, the termination error tolerance of a predetermined simulation exceeds. In this example, each of the second set of date-matching simulations, as the system continues, lacks a hydrocarbon field simulation error measurement that exceeds the predetermined simulation termination error tolerance. The variance of the predetermined simulation termination error can relate to the specified values ​​of one or more threshold variables 119. Threshold variables can include different types of variables that</p>

<p>10 Its properties can vary from one to the other. Threshold variables can also be related to, for example, reservoir pressure, fluid production, or injection rates, cumulative fluid production, and injection. A stock engineer may, for example, specify the values ​​of one or more threshold variables 119. For example, one or more threshold variables can relate directly or indirectly to one or more objectives (including It, in some cases, one or more of the functions</p>

<p>15th objective) to study a simulation of a hydrocarbon stockpile, as people skilled in this field will understand. A predetermined value of a single mutable cut-off value can therefore act as a boundary value, in some circumstances, before the simulation is completed.</p>

In another embodiment, for example, each of the first set of date-matching simulations can be terminated before completing the corresponding predetermined time period when more than a number of

<p>20 Predetermined hydrocarbon wells in each of the first set of date-matched simulations each exceed the predetermined well termination error tolerance. In this example, each of the second set of date-matching simulations that the system continues has less than a predetermined number of hydrocarbon wells such that each has a hydrocarbon well error measurement that exceeds the predetermined well termination error tolerance. An error tolerance can relate, for example, to values</p>

<p>25 Predetermined for one or more of the 119 threshold variables.</p>

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In each of the two representative models, the finite, predetermined embedded computing power can be configured to have increased processing availability when the first layer of date-matching simulations is terminated. Termination of the first set of simulations can thus increase the processing availability of a fluid flow operation with a limited, pre-determined, built-in computing power to one or more simulations.

<p>5 Fluid flow is actuated and reduce the total run time of the hydrocarbon stock simulation</p>

.reservoir simulation

Each of the second set of date-matching simulations can run simultaneously with one or more of the other second set of date-matching simulations after the first set of date-matching simulations has been completed. Furthermore, it can include a set of

<p>10 Date matching simulations for each set of hydrocarbon reservoirs on a number of predetermined matching simulations. Adding the predetermined numbers of date-matching simulations of a set of hydrocarbon reservoirs can specify a total number of pre-date-matching simulations, for example. A predetermined total number of date-matching simulations can be scheduled to request a predetermined amount of time to determine the total completion time</p>

<p>15th Expected. But termination of the first set of date-matching simulations for each group of hydrocarbon reservoirs can characteristically push the process of a predetermined total number of date-matching simulations to terminate before the end of the expected total termination time.</p>

A predetermined and limited built-in computing power of one or more 101 processors can limit the rate at which a set of date-matching simulations can be run, for example

<p>20 example. In some systems according to one embodiment of the present invention, when instructions 106 are executed in a non-buffered memory medium 105 it can also prompt the system to take additional steps to efficiently maximize the use of a predetermined, limited built-in computing power. Additional steps can thus include, for example, starting another date-match simulation in response to ending a date-matching simulation. For example, one or more of one or more can be used</p>

<p>25 of the 101 processors that have increased processing availability in response to the termination of a date-matched simulation </p>

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To start the other, a different date-matching simulation. Using one or more 101 processors that have increased processing availability in response to the termination of the time-matching simulation can start the date-matched simulation faster. Efficient use of limited built-in computing power can thus be increased because other date-matching simulations can take advantage of processing availability.

<p>5 The excess caused by terminating the simulation process.</p>

Additionally, a set of date-matching simulations can be configured to calibrate one or more 121 hydrocarbon reservoir simulation models associated with each corresponding set of hydrocarbon reservoirs by comparing a set of hydrocarbons to the actually measured 103 reservoir characteristic values ​​for each of the corresponding sets of 103 weights

<p>10 hydrocarbon. The values ​​of the measured reservoir properties can actually be 103 which are measured data relating to the hydrocarbon reservoir, ie, measurements and observations collected during the discovery and production of the hydrocarbon reservoir. For example, the measured reservoir properties values ​​can contain physically, eg, reservoir pressure, hydrocarbon production rates, percentage of water produced, or injection data. Furthermore, a simulated hydrocarbon field error measurement can be determined for a time step after the process</p>

<p>15th Date-matched simulation in response to compare (1) one or more simulation data values ​​to a set of simulation data associated with a date-matched simulation after a time step and (2) one or more set of 103 actually measured reservoir character values ​​for each of the corresponding set of hydrocarbon reservoirs. Similarly, a simulation error measurement of a hydrocarbon well can be determined for a time step after a date-matching simulation in response to the comparison of (1) one or more simulation data values</p>

<p>20 for a set of simulation data associated with a time-matched simulation after a time step and (2) one or more 103 actually measured reservoir properties values ​​for each of the corresponding set of hydrocarbon reservoirs.</p>

In some circumstances, the system can also have one or more 102 databases connected to one or more 101 processors. One or more databases can be configured

<p>25 data to contain, for example, a set of actually measured stock property values ​​of 103 each </p>

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From the group of hydrocarbons. One or more of the 102 databases may also be configured to contain, for example, one or more 121 hydrocarbon reservoir simulation models associated with each set of hydrocarbon reservoirs. Additionally, instructions 106 in non-buffered memory center 105 can also prompt the system to take additional steps, for both

<p>5 A set of hydrocarbon reservoirs, when implemented. For example, the steps can also include calculating one or more delta values ​​for well variances or for each of a set of simulations after a time step. The delta values ​​of well variances can be in response to the reception of one or more set of 103 measured distinct reservoir values ​​for each of the corresponding set of hydrocarbon reservoirs from one or more 102 databases. Moreover, it can be the one or</p>

<p>10 More delta values ​​between each of one or more simulated data values ​​of a set of simulation data associated with a time step and one or more set of distinct stored values ​​103 measured received from one or more databases102. In addition, the calculation of one or more delta values ​​for well variances can be based on a function: (1) each of one or more simulation data values ​​for a set of time step-related simulation data, (2) each of one or more set of values</p>

<p>15th A measured characteristic reservoir 103 is received from one or more of the 102 database, and (3) a predetermined well weight factor. A hydrocarbon well counterweight can be generated by a reservoir simulation engineer based on an expert knowledge of a hydrocarbon reservoir model and uncertainty in the reservoir model. Furthermore, the well weighting factors can be adjusted for all hydrocarbon wells in a hydrocarbon field and added to one as they aggregate.</p>

<p>20 A group of hydrocarbon wells, each of one or more delta values ​​of the well difference associated with the corresponding hydrocarbon well. Adding each of one or more delta values ​​of the well variance can thus determine the simulated well variance value. The step could also include, for example, specifying—for each of the set of date-matching simulations—a hydrocarbon field error gauge simulation by using the well simulation variance values ​​for each hydrocarbon field group of hydrocarbon wells. in a</p>

<p>25 Another model, for example, the steps could include defining - for each group of wells </p>

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Carbon in each of a set of date-matched simulations—measure the hydrocarbon well simulation error by using the simulation well variance value.

In some cases, one or more I/O 104 may also be set as input to receive predetermined values ​​of one or more threshold variables 119 and data

<p>5 Simulation for outputting 117 output simulation data. Furthermore, a set of date-matching simulations of each group of hydrocarbon reservoirs can be initiated by using one or more of one or more 101 processors. The initiation of each batch of date-matching operations for each group of hydrocarbon reservoirs can also be in response to the input of one or more input and output units.</p>

104 units 10

Additionally, in some cases, a system can also include a user terminal 115, as shown in Figure 1, for example. User Terminal 115 can be configured to display one or more sets of distinct reservoir values.

103 characteristic values ​​to a user by using display 116, for example

<p>15th example, in addition to specifying the predetermined values ​​of one or more threshold variables</p>

119 threshold variables in response to a user action inside portlet 118. When instruction 106 is executed in the non-transitory memory medium 105 it can also prompt the system to take additional steps, such as, for example, receiving preset values ​​for one or more of the 119 threshold variables by using one or more

<p>20 More than one or more I/O units 104 than user terminal 115. As shown in Figure 1, for example, user terminal 115 can be configured to display simulation data 117 to a user by using display 116.</p>

Furthermore, in some systems according to one embodiment of the invention, each of the 101 processors can have a single, limited, predetermined computing power. can be capacity

<p>25 Predetermined limited single computing, for example, a small part of the combined computing capacity </p>

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finite or predetermined for one or more 101 processors that are defined for a mathematical function by a predetermined finite built-in computing power and a number of one or more 101 processors.

In some systems according to one of the embodiments of the invention, when instructions 106 are executed in a non-memory medium

<p>5 timer 105, may also involve the system to perform other additional steps, such as, for example, restarting a date-matched simulation process terminated by using one or more single or more processors 101 that have overprocessing availability in response to the termination of a simulation match for history. This use can therefore be restarted for one or more of the 101 processors that have overprocessing availability in response to the termination of the simulation matching the date able to be restarted before</p>

<p>10 Finish the simulation matching the date. In some circumstances, the step can also still include a state of termination storing data representing a terminated date-matching simulation, for each of one or more of the terminated-date-matching simulations. The termination state of storing a data representative of a terminated date-match simulation can thus allow the terminated date-match simulation to be restarted in response to the terminated date-matching simulation termination state. The simulation process can be restarted,</p>

<p>15th For example, when the simulation fails due to a problem with the computer system, for example, a power outage.</p>

Models can also relate to a prediction simulation. A system of another embodiment may include, for example, one or more 101 processors that together have a limited and predetermined built-in computing power, as shown, for example, in Figure 10. Computing can be available

<p>20 finite and predetermined embedded in response to the use of a simulation. A system with a 105 non-cache memory medium can also have communication with one or more of one or more 101 processors. The 105 memory medium can have computer-readable instructions 106 stored on it that, when executed, prompt the system to perform a series of steps.</p>

The steps can include, for example, initiating, for each of the set of lockers

<p>25 hydrocarbon, for each of a set of fluid flow simulations. A group of . can be initialized</p>

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Fluid flow simulations to predict the future behavior of each of the corresponding group of hydrocarbon reservoirs. As a result, a set of fluid flow simulations can thus define a set of prediction simulations. Each of a set of forecast simulations can be configured to run for a corresponding predetermined period of time. In addition, each period of time can include

<p>5 Advance correspondence to one or more time steps. Each set of prediction simulations can also be configured, therefore, to output a set of simulation data in response to the corresponding prediction simulation after each of one or more time steps. Each simulated data set can include one or more simulated data values, and each corresponding set of hydrocarbon reservoirs can have a set of hydrocarbon wells. Each one can be configured</p>

<p>10 or more simulated data values ​​to be associated with one group of hydrocarbon . wells</p>

.wells

The steps may also include termination, for each set of hydrocarbon reservoirs, each of the first set of one or more of a set of prediction simulations before completing a corresponding predetermined time period, in response to the exit after a time step, when a second set of one or more of

<p>15th A bunch of other prediction simulations. The first set of prediction simulations can be terminated when one or more of the one or more simulation data values ​​of the simulation data set are related to the first set of prediction simulations after the time step is outside the tolerance of the values ​​of a simulation data pan, for example. Conversely, one or more simulation data values ​​for a set of simulation data associated with each set can be included.</p>

<p>20 The second is for prediction simulations after the time step within the simulation termination tolerance of the data values. Simulation termination tolerance of data values ​​can relate to predetermined values ​​of one or more of the 119 threshold variables. For example, two values ​​of the same mutable threshold threshold can define a simulation termination tolerance of data values, in some circumstances. In some cases, two or more predetermined values ​​of one or more threshold variables 119 can define a range of water values.</p>

<p>25 Acceptable product, permeability, or relative permeability factor tools, eg. Therefore, it can</p>

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The tolerance for termination of the simulation data values ​​includes a range of acceptable product water percentage values ​​and a range of acceptable reservoir pressure values, for example. When the tolerance of termination of the simulated data values ​​includes a range of acceptable stock pressure values, one or more of the predetermined threshold threshold variables can also be 119 a stock pressure target value, for example. The range of pressure values ​​can be related to

<p>5 Acceptable stock - an example of a simulated data value termination tolerance - with a target value of a stock pressure, for example, by including stock pressure values ​​close to the target value of the stock pressure. Limited, predetermined embedded computing power can be configured to have increased processing availability when the first set of prediction simulations is terminated. Termination of the first set of prediction simulations while the second set of prediction simulations is in progress can thus increase the availability of processing for operations</p>

<p>10 Fluid flow simulation within the limited and predetermined built-in computing power to one or more other fluid flow simulations that are run and can reduce the total runtime of the hydrocarbon stockpile simulation.</p>

In some circumstances, each of the second set of coincidence prediction simulations can run with one or more of the second set of prediction simulations after the set is terminated.

<p>15th The first of the prediction simulations. Furthermore, the set of forecast simulations for each group of hydrocarbon reservoirs can include a number of predetermined forecast simulations, such as a number of finite forecast simulations, and summing the predetermined numbers of forecast simulations for the set of hydrocarbon reservoirs that can determine the total Predetermined number of prediction simulations. The completion of a predetermined total number of forecast simulations can be included to request a time quantity</p>

<p>20 specific and thus determine the total time expected to complete. Termination of the first set of forecast simulations for each group of hydrocarbon reservoirs can characteristically drive the process to a predetermined total number of forecast simulations to finish before the end of the total expected time to complete.</p>

In addition, the set of prediction simulations can be configured to predict the future behavior of each corresponding set of hydrocarbon reservoirs by using one or more of the following:

<p>25 Hydrocarbon reservoir simulation models associated with each of the corresponding group of hydrocarbon reservoirs.</p>

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One or more hydrocarbon reservoir models can be calibrated by using a set of distinct measured reservoir values ​​103 and thus one or more calibrated hydrocarbon reservoir simulations 122. In some circumstances, each set of prediction simulations can be associated with an additional path. One of the procedures for developing each of the corresponding group of associated hydrocarbon reservoirs

<p>5 with the corresponding prediction simulation process. An additional course of action to develop each of the corresponding group of hydrocarbon reservoirs could thus define a development strategy, for example. Development strategies could include, for example, injecting an inhibitor into a hydrocarbon stockpile to improve hydrocarbon recovery. Other examples of development strategies could include, for example: (1) drilling of new wells with specific restrictions, (2) changing restrictions related to production or injection units,</p>

<p>10 (3) Estimation of the hydrocarbon obtained, and (4) Estimation of individual hydrocarbon wells or</p>

manifold. Furthermore, the predetermined values ​​of one or more of the threshold variables 119 and the inequality of termination of the simulation data values ​​can be associated with one or more predetermined strategic outcome values ​​for one or more development strategies. One or more predetermined strategic outcome values ​​may be associated with one or more objectives related to hydrocarbon stock development, for example

<p>15th example. As a result, one or more of the predetermined strategic outcome values ​​may include, for example, a fluid production rate higher than some predetermined minimum acceptable production rate.</p>

The system can also have one or more 102 databases connected to one or more processors 101. One or more 102 databases can, in turn, be initialized to include the set of 103 distinct stored values ​​for each of the set of servers. weights

<p>20 hydrocarbon and one or more hydrocarbon calibration stock simulation models 122 associated with each group of hydrocarbon reservoirs. In addition, instructions 106 in non-buffering memory center 105, when executed, can also prompt the system to perform a data storage step representing the termination state of a terminated prediction simulation for each of one or more terminated prediction simulations. Storing such data can therefore allow verification of the associated development strategy</p>

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with the terminated prediction simulation when required in response to the termination condition of the terminated prediction simulation, for example.

Sometimes, one or more predetermined strategic outcome values ​​for one or more development strategies may include, for example, a measurement of the maximum water content of a specific product.

<p>5 in advance, for one or more of a group of hydrocarbon reservoirs, as would be understood by persons skilled in the art. In this example, the predetermined values ​​of one or more of the threshold variables 119 can relate to the percentage of water produced. Furthermore, a violation of the variance termination of simulated data values ​​can occur when the percentage of water produced exceeds 30%, for each hydrocarbon well or group of hydrocarbon wells. In this example of the proportion of water produced, the value of the proportion of water produced can be measured</p>

<p>10 At the end of each time step and compared to the threshold for the percentage of water produced—one of the predetermined values ​​for one or more of the 119 Threshold variables—as determined by an engineer at the start of the process, eg 30%. If the simulated water yield is less than 30% cut-off value, then the next time operation can be resumed and run. Thus, the simulation process in which the percentage of water produced exceeds 30% can be completed, and the results are then displayed. In this example, it can</p>

<p>15th A water yield greater than 30% indicates that the simulated development scenario is not valid. The engineer has the choice between setting simulated data values ​​termination tolerances for all hydrocarbon wells and setting simulated data values ​​termination tolerances for a specified number of wells, for example. Therefore, simulated termination variance prediction simulations can violate simulated data values ​​when the percentage of water produced for a single well or group of wells exceeds 30%. When termination tolerance is set for simulated data values ​​for each well</p>

<p>20 Petroleum, for example, the termination tolerance of simulated data values ​​can be violated when the percentage of water produced in any of the reservoir hydrocarbon wells is greater than 30%, and the simulation can then be discontinued. But a simulated data value termination tolerance can instead be established for a group of hydrocarbon wells or for a single hydrocarbon well, for example, by establishing a simulated data value termination tolerance that will be violated when any hydrocarbon well is exceeded in the first set of</p>

<p>25 wells 30% and that the termination tolerance of simulated data values ​​will be violated when any well exceeds hydrocarbon </p>

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In the second group of wells 50%. In this example, violations of any of the established conditions could prompt the simulation to terminate. Those established conditions could be criteria for terminating a simulation, for example.

One or more I/O modules for reception can also be set as an input

<p>5 104 for predetermined values ​​of one or more threshold variables 119 and simulated data to output</p>

<p>117. In addition, each set of prediction simulations can be initiated for each of the set of hydrocarbon reservoirs by using one or more single or more processors 101 and can also be in response to the input from one or more I/O units 104 In some circumstances, the system may also include a user terminal</p>

<p>10 115 is configured to display one or more of the set of 103 distinct, measured storage values ​​to a user</p>

and specifying predetermined values ​​for one or more threshold variables 119 in response to a user action during input 118. Furthermore, instructions 106 in non-buffering memory medium 105, when executed, can prompt the system to perform the receive step of the set values predetermines one or more of the threshold variables 119 by using one or more of one or more of the

<p>15th I/O modules 104 from user terminal 115. As shown in Figure 10, for example, user terminal 115 can also be configured to display simulated data 117 to a user by using display 116.</p>

On some systems, instructions 106 in a non-buffered memory medium 105, when executed, can prompt the system to perform the start step, in response to ending a prediction simulation, another 20 different prediction simulations. Various other prediction simulations can be started by using one or more

of one or more 101 processors that have increased processing availability in response to termination of a prediction simulation, for example, to enable early start of another prediction simulation. Additionally, each of the one or more 101 processors can have a predetermined finite individual computing power, and the predetermined finite individual computing power of a processor can be a very small 25 portion of the predetermined finite integrated computing power of one or more processors

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101 processors that are defined by a mathematical function of a predetermined finite embedded computing power and a number of one or more 101 processors.

The simulator itself can have an error tolerance that is separate and distinct from a simulation termination error tolerance, a well termination error tolerance, or a simulated data value termination tolerance, as skilled people will understand

<p>5 in this field. A simulated error tolerance can be set i.e., a simulated tolerance to ensure that the simulated numerical solutions are accurate and do not have significant errors. The tolerance of a simulator can depend on the arithmetic solutions of the simulator and the level of error that one can allow in the convergent numerical solution. Conversely, the termination error tolerance of a simulation, the termination error tolerance of a well, or the termination error tolerance of simulated data values ​​can be used in association with the termination of one or more simulations; Operations can be kept</p>

<p>10 Valid, i.e., not terminated, needs to be within one or more of the set's simulated tolerances. Therefore, a simulated tolerance can relate to numerical accuracy, while a simulation termination error tolerance can relate to a simulated process termination error tolerance, a well termination error tolerance, or a termination tolerance tolerance for simulated data values, a process termination criterion. For example, a simulation termination error tolerance or a well termination error tolerance can be used to determine whether a numerical solution is within an acceptable error range for observed historical data.</p>

<p>15th A simulated tolerance, on the other hand, can include, for example, numerical and physical balance tolerances.</p>

The predetermined, finite built-in computing power of one or more 101 processors can constrain the rate at which a system can run a set of fluid flow simulations, for example, including date-matching simulations, prediction simulations, or

<p>20 both of them. The use of the finite, predetermined embedded computing power 130 of one or more processors 101 over time 131 to run a set of simulations, for example, is illustrated in Figure 3. As illustrated in Figure 3, for example, a system that Demonstrated by running at least nine simulations, ie, running A-H. The limited and predetermined embedded computing capacity of 130 can be based on one or more of the 101 systems processors,</p>

<p>25 However, by restricting the first start of simulations to process A 132, process B 133, process C 134,</p>

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Process D 135. The next simulation is waiting to start, Process H 137, cannot start at the same time as Process A 132, Process B 133, Process C 134, and Process D 135 due to the limited and predetermined embedded computing power 130. In the example shown In Figure 3, process H137 starts after process A132 has been completed or terminated; Termination of Process A132 results in the availability of

<p>5 Incremental processing within a predetermined finite built-in computing power 130 for one or more processors 101. Similarly, process H 138 can start after process C 134 has finished, process G 139 can start after process D 135 has finished, process H 140 can start After process B 133 ends, process I 141 can start after process H 137 ends because availability is increased as a result of terminating the simulation. In another embodiment, a restart can take place for one or more processes</p>

<p>10 Expired, a process restart is expected to start before the new processes. As shown in Figure 3, for example, some simulations can, in some cases, use a predetermined finite embedded computing power 130 for one or more 101 processors more than other simulations. Likewise, some simulations can require more time to complete than others. The time required for the simulation process can also relate to computing power</p>

<p>15th available for the simulation process. Because the rate at which a set of simulations is completed depends on the finite and predetermined embedded computing power 130 of one or more 101 processors, more efficient use of the finite and predetermined embedded computing power 130 of one or more 101 processors could allow the system to complete a set of Simulation is faster. Therefore, by reducing the number of simulations that run for their entire scheduled period, it can be done</p>

<p>20 Reducing the amount of time required to achieve one or more simulation objectives. Although the number of simulations does not necessarily change, the number of simulations that are completed can be reduced. Premature termination of unhelpful simulations can thus save the time required to complete a set of simulations.</p>

25 A system in some circumstances can only run date-matching simulations, and in other circumstances a system can run only prediction simulations. But a system can also do

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Run both date-matching simulations and prediction simulations. For example, as shown in Figure 3, process c can be 134 time-matching simulations while process d 135 is a prediction simulation.

It can also integrate models of the invention related to date-matching simulations and processes

<p>5 Forecast simulation Intelligent arithmetic and management rules to automatically cut off a number of simulations that are run for their full time listed in a table, that is, their corresponding predetermined time slots. For example, models can reduce the number of date-matching simulations run for their corresponding predetermined intervals by stopping simulations that deviate from historical data, observed by more than a predetermined simulation termination error tolerance, at example, in</p>

<p>10 A simulation matching the date. Models can also turn off simulations that exceed or fall under some termination tolerance of user-defined simulation data values ​​in a typical study to simulate a prediction stock. For example, after a time-matched process or time-matched activities have been completed, a date-matched hydrocarbon reservoir simulation model, such as one of one or more calibrated hydrocarbon reservoir simulation models 122, may be used to develop prediction scenarios that rely on</p>

<p>15th Various development strategies. Forms of this disclosure can be used to assist inventory engineers in</p>

Eliminate development scenarios, i.e., development strategies, that do not meet the objectives—as defined as measured by one or more predetermined strategic outcome values—in a development strategy for an early stage in the report. For example, if a target, that is, one of one or more predetermined strategic outcome values, is set at 20,000 barrels per day for an oil production plateau for N years,

<p>20 A simulation can be selected if the potential fall field is under the early target in the simulation.</p>

In both date-matching simulations and prediction simulations, increasing confidence in the tools used to evaluate industry development plans can be of great importance, and invention models can successfully increase the level of confidence. In addition, innovative models can save CPU time

<p>25 CPU (Central Processing Unit) is sometimes called "resources". </p>

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computer”) when compared to traditional methods, which rely on manual intervention by simulation engineers. It is worth noting that, models can give simulation engineers the ability to efficiently manage their simulation situations by making decisions – based on some specific criteria predetermined (for example, predetermined values ​​of one or more threshold variables)

<p>5 Set by a user, such as a simulation engineer - whether to continue or stop the simulation instead of</p>

So safely.

Characteristically, inventive models can also have fewer number simulations—both date matching and prediction—running for the full term in their schedule. Models can thus reduce the number of turns to complete a study by reducing the time required to complete a large number of simulations.

<p>10 Furthermore, invention models can also save up to fifty percent (50%)</p>

Saving CPU time, which in turn can allow better resource use between different studies. Invention models can also enable petroleum engineers, for example, to complete their prediction and dating studies in a short time frame, allowing engineers to focus more on engineering work rather than worrying about managing the limited computing and storage resources available to them. Furthermore

<p>15th However, stock management rules can usefully allow engineers to control the values ​​of threshold variables that affect the performance of their numerical simulation models. Invention models can automatically capture values, including values ​​that relate to predetermined values ​​of one or more threshold variables and termination criteria, generated by an engineer who runs one or more simulations. The models of the invention may also make decisions, in favor of the engineer, to complete a simulation</p>

20 given.

In particular, for example, assisted AHM (history matching) can in some cases take up approximately 60% of an engineer's time and effort. In addition, traditional methods are used to display hundreds of simulations of a single auxiliary history—the The study of conformity is impractical: it always increases in size and complexity

<p>25 Model - The schedule for the project that is growing is lower than the previous schedule. you can play</p>

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Invention models enable engineers to start multiple date-matching projects, measured by eye simultaneously, for example. In addition, models can characteristically reduce the number of simulations by about thirty to fifty percent (30-50%), resulting in fewer spin-offs, and better use of limited computing and resource storage.

<p>5 Potentially saving an entity that can run simulations of a hydrocarbon stockpile that consumes millions of dollars annually in high-performance computing resources. The AHM can also assist with the conduct of forecasting studies based on uncertainty, for example, because the uncertainty that arises during the AHM can be transferred to the prediction studies. An engineer can then use the engineer's knowledge to doubt a hydrocarbon stockpile simulation model to choose the values ​​of one or more of the 119 threshold variables for use in operations.</p>

<p>10 Forecast simulation, for example.</p>

In addition to systems, models for an invention may also include computer-implemented methods. For example, a model may include a computer-implemented method for improving the simulation of a hydrocarbon reservoir for a group of hydrocarbon reservoirs. A method related to date matching can include starting 22, for each of the set of hydrocarbon reservoirs, each of the set of simulations

<p>15th Fluid flow, as shown, for example, in Figures 5 and 6. A set of fluid flow simulations can be configured to calibrate one or more hydrocarbon reservoir simulation models associated with each corresponding set of hydrocarbon reservoirs. A set of fluid flow simulations can thus define a set of simulations corresponding to the date of each corresponding set of hydrocarbon reservoirs. Each of the set can be initialized from a date-matching simulation</p>

<p>20 To run for a corresponding predetermined period of time. Furthermore, each corresponding predetermined time interval can include one or more time steps. Each set of date-matching simulations can also be initialized to output 203 simulation datasets in response to running the corresponding date-matching simulation after each One or more time steps. Each simulated data set can contain, for example, one or more simulated data values.</p>

<p>25 Each of the corresponding group of hydrocarbon reservoirs can have a group of hydrocarbon wells, </p>

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A group of wells can together define a hydrocarbon field within each corresponding group of hydrocarbon reservoirs. In addition, one or more simulated data values ​​may be configured to be associated with one set of hydrocarbon wells for each corresponding set of hydrocarbon reservoirs.

<p>5 A method may also include termination of 210 - for each set of hydrocarbon reservoirs - for each of the first set of one or more of a set of date-matched simulations before completing a predetermined time period corresponding to the exit after a time step while a second set continues from one or more of a set of other date-matching simulations. For example, in some circumstances, a method can include finishing 210 first set of simulations</p>

<p>10 Date matching when each of the first set of date-matching simulations has a hydrocarbon field simulation error measure that exceeds a predetermined simulation termination error tolerance 209, as shown in Figure 5, for example. In this example, each of the second set of date-matching simulations lacks a hydrocarbon field simulation error measure that exceeds the predetermined simulation termination error tolerance. A process termination error tolerance can be related to</p>

<p>15th Predetermined simulation with predetermined values ​​of one or more threshold variables.</p>

In another embodiment, for example, a method could include termination of 210 first set of date-matched simulations when more than a predetermined number of hydrocarbon wells are in each of the first set of date-matched simulations and each has a simulation error measurement of the hydrocarbon well which exceeds a predetermined well termination error tolerance 216, as has been done

<p>20 The illustration is in Figure 6, for example. In this example, each of the second set of match-date simulations can have fewer than the predetermined number of hydrocarbon wells so that each has a simulation error measurement of the hydrocarbon well that exceeds the predetermined well termination error tolerance. The predetermined number of hydrocarbon wells and the predetermined well termination error variance can relate to the predetermined values ​​of one or more threshold variables, for example.</p>

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Limited, predetermined, combined compute power can be available aggregated to one or more processors in response to the use of a simulation and can be configured to have increased processing availability when the first set of date-matching simulations is completed. Thus, finishing 210 first set of simulations matching the date can increase processing availability for flow simulations

<p>5 Fluid within the predetermined and limited built-in computing power of one or more other fluid flow simulations that are run and reducing the total runtime of the hydrocarbon reservoir simulation.</p>

In some circumstances, each of the second set of date-matching simulations may run concurrently with one or more of the second set of date-matching simulations after the first set of date-matching simulations is completed. Furthermore, 10 can include a set of simulations matching the date for each set of reservoirs

The hydrocarbon contains a predetermined number of date-matched simulations, and summing the predetermined number of date-matching simulations to a set of hydrocarbon reservoirs can determine a total of a predetermined number of date-matching simulations. The completion of a predetermined number of simulations matching the date can be scheduled to require a predetermined amount of time and thus

<p>15th Determine the total expected completion time. Termination of the first set of date-matching simulations for each set of hydrocarbon reservoirs can usefully push the process totaling a predetermined number of date-matching simulations to terminate before the end of the total expected completion time.</p>

A method can also, in some circumstances, include starting another different date-match simulation, in response to termination of a date-matching simulation. One or more of . can be used

<p>20 One or more processors that have overprocessing available in response to ending the date-matched simulation to start another, different date-matching simulation. Using one or more of one or more processors with increased processing availability in response to termination of the date match simulation can thus enable the early start of the other date match simulation.</p>

A set of date-matching simulations can, in some circumstances, be configured to calibrate

25 One or more hydrocarbon reservoir simulation models associated with each corresponding set of reservoirs

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Hydrocarbon by comparing a set of characteristic reservoir values ​​measured for each of the corresponding set of hydrocarbon reservoirs. Furthermore, a hydrocarbon field simulation error measure can be specified for a date-matched simulation after a time step in response to the comparison of (1) one or more simulation data values ​​to a set of simulation data associated with a date-matched simulation after

<p>5 time step and (2) one or more of a set of distinct reservoir values ​​measured for each corresponding set of hydrocarbon reservoirs. Additionally, a hydrocarbon well simulation error measurement can be specified for a date-matched simulation after a time step in response to a one (1) comparison one or more simulation data values ​​for a set of simulation data associated with a simulation corresponding to a date after a time step and (2) one or more set of distinct stored values ​​measured for each set</p>

<p>10 Correspondence to hydrocarbon reservoirs.</p>

In some cases, a method for each set of hydrocarbon reservoirs may also include calculating one or more delta values ​​for well variances, for each of a set of simulations corresponding to the date after a time step and in response to the reception of one or more set of distinct measured reservoir values For each of the corresponding group of hydrocarbon reservoirs. One or more of the 15 delta values ​​for well differentials can be delta values ​​between each of one or more values ​​of the simulation data for a set

From simulation data associated with a time step and one or more of a set of measured distinct stock values. The delta values ​​of the well variance can be based on a function of (1) each of one or more simulation data values ​​for a set of time step-related simulation data, (2) each of one or more of a set of measured characteristic reservoir values, and (3) . A predetermined well weight factor. It can also be

<p>20 A method, for each group of hydrocarbon wells, includes each of one or more delta values ​​of the well differentials associated with the corresponding hydrocarbon well. The sum of all of one or more of the delta values ​​of the well variance associated with the corresponding hydrocarbon well can determine the simulated well variance value. A method may also include, for example, the determination of a hydrocarbon field simulation error measurement, for each of a set of date-matched simulations. A simulated error measurement can be specified for a field</p>

<p>25 hydrocarbon by using simulated well variance values ​​for each group of hydrocarbon wells </p>

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for the hydrocarbon field. In another embodiment, a method may include determining a simulated hydrocarbon well error measurement, for each set of hydrocarbon wells in each of the set of date-matched simulations. The simulated error measurement of a hydrocarbon well can be determined by using simulated well variance values, for example.

<p>5 In some circumstances, a method can also include receiving threshold variables 201 of one or more predetermined values ​​in response to user input, as shown, for example, in Figures 5 and 6. Furthermore, in some cases, each of the one or more processors can have a predetermined limited individual computing capacity. A limited single computing power can be predetermined for the processor, for example, a small portion of the limited built-in computing power</p>

<p>10 A predetermined for one or more processors that is defined by a mathematical function of a predetermined finite built-in computing power and a number of one or more processors.</p>

A method can also include, for example, restarting a terminated date-match simulation by using one or more of the one or more processors that have increased processing availability in response to the termination of a date-matched simulation. Can therefore when using one or more of the

<p>15th One or more processors with increased processing availability in response to the termination of a date-matched simulation should start early in a date-matched simulation. In some cases, a method can also include storing 212 data representing the termination status of a completed date match simulation, for each of one or more terminated date match simulations. Termination status data can be saved in a record keeping knowledge base, for example. In addition, it can thus</p>

<p>20 To store data representative of a terminated simulation's termination status, for example, allow a rerun of a terminated simulation's termination if necessary in response to a terminated simulation's termination status. Furthermore, the routing termination state data can also then be used to generate input for a new simulation to avoid creating a new simulation that is too close to the input data blank for a pre-terminated process.</p>

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Thus, a method related to date matching can include, for example, receiving 201 predetermined values ​​for one or more threshold variables, starting 202 simulations, and outputting 203 simulation datasets for a simulation at the time step, as shown in Figures 5 and 6. A method can then include determining 204 whether a time step is a time step

<p>5 The last simulation process. If the time step is the last time step of the simulation, a method can then include termination of 205 simulations, outputting 208 data associated with the simulation, and specifying 207 whether to start another simulation. If the start of another simulation is 207, a method can include starting 202 of that simulation. If no further simulations are to be started 207, a method can include termination of 214 simulations. If you are not a step</p>

<p>10 Time is the final time step of the 204 simulation, a method can include calculating the 206 hydrocarbon field simulation error measurement at the time step 209 which then determines whether the hydrocarbon field simulation error measurement exceeds a predetermined simulation termination error tolerance, as shown, For example, in Figure 5. If the simulation error measurement for a hydrocarbon field does not exceed the tolerance of the termination error of a predetermined simulation 209, a method can include starting 211</p>

<p>15th Another time step then outputs 203 simulation datasets for a simulation at the time step. If the simulation error measurement for a hydrocarbon field exceeds the variance of a predetermined simulation termination error of 209, a method may include termination of 210 simulations. In another embodiment, a method may also include, if the time step is not the last time step of the 204 simulation, calculating the 215 simulation error measurements of the hydrocarbon well for each hydrocarbon well associated with the</p>

<p>20 The simulation, as shown, for example, in Figure 6. A method could then include determining whether the number of hydrocarbon wells in the simulation having a simulated error measure of a hydrocarbon well exceeds a predetermined well termination error tolerance greater than the number of Predetermined hydrocarbon wells, as shown, for example, in Figure 6. If the number of hydrocarbon wells exceeds the predetermined number of hydrocarbon wells, a method can include termination of 210 processes</p>

<p>25 simulation. If the number of hydrocarbon wells does not exceed the predetermined number of hydrocarbon wells 216, the method can include initiating another 211 time steps after which simulated data output</p>

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for a simulation at time step 203. After terminating the simulation 210, a method can then include storing 212 data representing the termination state of a completed simulation, as shown, for example, in Figs 5 and 6. P to Oh, it can also include a way to determine whether the start of the simulation process terminated. If the simulation process is not restarted, it can be terminated

<p>5 simulation process. If the simulation is restarted, it is started.</p>

A method according to another embodiment can include, for example, starting 202, each of a set of hydrocarbon reservoirs, each of a set of fluid flow simulations, as illustrated in Figure 11, for example. A set of fluid flow simulations can be configured to predict the future behavior of each of the corresponding set of hydrocarbon reservoirs, and set of simulations

<p>10 Fluid flow can thus define a range of prediction simulations. Additionally, each of the set of forecast simulations can be configured to run for a corresponding predetermined time period, and each corresponding predetermined time period can include one or more time steps. Furthermore, each set of prediction simulations can be initialized to produce 203 sets of simulation data in response to a corresponding prediction simulation after each of the one or more steps</p>

<p>15th timeline. Each simulated data set can contain, for example, one or more simulated data values. In addition, each corresponding group of hydrocarbon reservoirs can have a group of wells. Each of one or more simulated data values ​​can be configured to be associated with one group of hydrocarbon wells.</p>

The method may also include a termination of 210, for each of the group of hydrocarbon reservoirs, each of

<p>20 A first set of one or more set of prediction simulations before completing a corresponding predetermined time period, time step after the response to output, when a second set of one or more of another set of prediction simulations continues. The first set of prediction simulations can be terminated when one or more of the one or more simulation data values ​​for a set of simulation data are associated with each of the first set of prediction simulations after the time step</p>

<p>25 Out of tolerance termination values ​​for 299 simulation data. Both . can be included</p>

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One or more simulation data values ​​for a set of simulation data associated with each of the second set of prediction simulations after a time step, however, within the termination tolerance of the simulation data values. The variance of termination of the simulated data values ​​can relate to the predetermined values ​​of one or more threshold variables, for example. Limited and limited built-in computing power can be configured

<p>5 Pre-assembled for one or more processors to have additional processing availability when the first set of prediction simulations is completed. Limited and predetermined embedded computing power can be available in response to the use of a simulation, for example. Thus, ending the first set of prediction simulations can thus increase the processing availability of fluid flow simulations within the predetermined, finite built-in computing power of one or more other fluid flow simulations being performed.</p>

<p>10 operate and reduce the total runtime of the hydrocarbon stockpile simulation.</p>

In some circumstances, each of the second set of coincidence prediction simulations may run with one or more of the second set of prediction simulations after completing the first set of prediction simulations. Furthermore, a set of forecast simulations for each group of hydrocarbon reservoirs can include a number of specific forecast simulations.

<p>15th Predetermined, summing up predetermined numbers of prediction simulations for a set of hydrocarbon reservoirs can determine a total predetermined number of prediction simulations. The completion of a predetermined total number of forecast simulations can be scheduled to require a predetermined amount of time and thus the total expected completion time. Completing the first set of prediction simulations for each group of hydrocarbon reservoirs can advantageously drive the process for a predetermined total number of operations</p>

<p>20 Forecast simulation to finish before the end of the total expected completion time.</p>

In addition, a set of prediction simulations can be configured to predict the future behavior of each corresponding set of hydrocarbon reservoirs by using one or more hydrocarbon reservoir simulation models associated with each corresponding set of hydrocarbon reservoirs. One or more hydrocarbon reservoir models may be calibrated by using distinct measured reservoir values ​​25 and thus one or more hydrocarbon reservoir calibration simulations may be calibrated. in addition to,

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Each set of forecast simulations can be associated with an additional course of procedures to develop each of the corresponding set of hydrocarbon reservoirs associated with the corresponding forecast simulation. Such an additional course of action can define a development strategy. Furthermore, predetermined values ​​can be related to one or more of the threshold variables and the termination tolerance of the values ​​of the data values.

<p>5 Simulation data with one or more predetermined strategic outcome values ​​for one or more development strategies. In some circumstances, a method may also include storing data representing a termination condition of a prediction simulation, for each of one or more of the termination simulation simulations, thus allowing the development strategy associated with the termination simulation to be checked as necessary in response to a simulation termination condition. The prediction is terminated. Additionally, it may include one or</p>

<p>10 More than values ​​predetermined strategic outcomes for one or more development strategies on the measurement of the maximum predetermined product water percentage for one or more of the group of hydrocarbon reservoirs, for example.</p>

A method may also include receiving 201 predetermined values ​​of one or more threshold variables in response to user input. A method can also have a start, in response to an end

<p>15th A prediction simulation, a different other prediction simulation by using one or more of the one or more processors that have overprocessing availability in response to the termination of the prediction simulation, which can thus enable it to be started before the other prediction simulation starts. In some cases, each of one or more processors can have a predetermined finite individual computing power, and the predetermined finite individual computing power of a processor can be a small portion of</p>

<p>20 A predetermined finite embedded computing power of one or more processors defined by a mathematical function of a predetermined finite embedded computing power and a number of one or more processors.</p>

Thus, a method for prediction simulations can include, for example, receiving 201 predetermined values ​​for one or more threshold variables, starting a 202 simulation, and outputting 203 simulation data sets for a simulation at a time step, as has been done. The illustration in Figure 11,

<p>25 for example. A method can then include determining 204 whether the time step is</p>

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It is the last time step of the simulation process. If the time step is the last time step of the simulation 204, then a method can include ending 205 simulation 205, outputting 208 the data associated with the simulation, and determining 207 whether to start another simulation. If another simulation is being started 207, a method can include starting the simulation process 202

<p>5 That. If another simulation is not started 207, a method can include termination of 214 simulations. If the time step is not the last time step of the 204 simulation, a method can include comparing 298 simulated data values ​​at the time step of the termination tolerance of the simulated data values ​​and then determining 299 whether any of the simulation data values ​​are outside the termination slips of the simulation data values , as shown, for example, in Figure 11. If all 10 simulation data values ​​are inside the 299 simulation data value termination slips, a method can have 211 initiation steps</p>

Another time is then to enter 203 sets of simulation data for the simulation process at the time step. If any of the simulation data values ​​are outside the 299 simulation data termination errors, however, a method can include termination 210 simulations. After 210 simulations are completed, a method can then include storing 212 data representing the termination state of a terminated simulation. bonus

<p>15th Furthermore, a method can also include whether the completed simulation is restarted. If the simulation is not restarted, the simulation can be terminated. If the simulation is restarted, it is started.</p>

An engineer may, for example, first verify historical data associated with a hydrocarbon stockpile that the engineer intends to match to date or an engineer intending to run a forecast simulation. Using knowledge about reservoirs, the engineer can specify the values ​​of one or more threshold variables to guide

Operate an intelligent calculation in making the correct decision as to whether to maintain the simulation or to terminate the simulation. Control can then be transferred to a simulator to start simulations (sometimes called “simulations” or “simulated states”). The one-time simulation arrives at a time step, rather than the final time step, the process worker can pick up

<p>25 Intelligent arithmetic or automatically initiates validation and decision-making based on the values ​​of one or more of the </p>

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Threshold variables as predetermined by an engineer. The computation can then decide to start the simulation or, alternatively, return control back to the simulator to continue the simulation. The worker can then search the simulation activities until the last time step of the last simulation is reached and no more simulations to perform the task. for example

<p>5 Example, a route according to one embodiment of the invention is illustrated, for example, in Figure 4, which can also be applied to other embodiments, as well. As illustrated in Figure 4, for example, a simulation of a hydrocarbon stockpile can include a user reaction 145, a simulating procedure 146, and a procedure by 147 according to embodiments of the invention. A factor according to the models of the invention is sometimes described here as an intelligent arithmetic operator.</p>

<p>10 A user interaction 145 could, for example, include both downloadable and investigational historical data 148. So, a user could load historical data from different sources such as a database or easy files, into a view package for a linear fragment of verification, for example. Historical data can include distinct, measured stock values, for example. User interaction 145 can also include selecting one or more 149 threshold variables and setting</p>

<p>15th The values ​​of one or more of the threshold variables 150. For example, one or more of the threshold variables and the values ​​of one or more of the threshold variables can be performed by visual investigation or by running a sensitivity analysis. A user, such as an engineer, can specify the values ​​of one or more threshold variables using user knowledge and feedback, for example. The values ​​of one or more threshold variables can be determined depending on the study objective</p>

<p>20 etc. weigh; Thus, the variance of the termination error of a predetermined simulation process, the variance of the error of termination of a predetermined well,</p>

The variance of termination of simulated data values ​​can also be subject to stockpile study. Fluid production reservoir pressure or injection rates, cumulative fluid production, and injection rates can be examples of marginal value changes. The values ​​for one or more of the threshold variables 156 can then be produced for an acceptable factor profile. The 146 Simulator can then start.

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The simulation procedure 146 may include operations that are controlled by a simulator, as people skilled in this field will understand. For example, the procedure for Simulator 146 could include starting the simulation process 151, outputting the time step data 152 to produce the time step data 153, and then determining whether the time step is the last time step to be run by the simulator 154. If

<p>5 The time step was the last time step to be run with Simulator 154, the Simulation 146 procedure could then include the termination of the simulation 164 to produce output 165. The output 165 and the time step data 153 could, for example, include well data Hydrocarbons are simulated such as production, injection, and pressure data. If the step is not the last time step to be performed by the simulator 154, however, the action of a factor 147 can be started. For example</p>

<p>10 For example, an operator may perform an automatic verification and a decision process 155 uses the values ​​of one or more of the threshold variables 156. It can then be determined if the 157 termination criteria are met. A termination calibration 157 can be provided, in the context of a date-matched simulation, for example, when a hydrocarbon field simulation error measurement exceeds a predetermined simulation termination error tolerance or, alternatively, when</p>

<p>15th More than a number of predetermined hydrocarbon wells each have a simulated hydrocarbon well error measurement that exceeds the predetermined well termination error variance. In the context of a prediction simulation, however, termination calibration 157 may be available, when one or more of the one or more simulated data values ​​of a set of simulation data are outside the termination tolerance of the simulated data values, for example. If a termination calibration 157 is not available, the 146 simulation procedure can be resumed by</p>

<p>20 Continue the simulation process 158 and then output the time step data 152. If one is available from</p>

The termination calibration 157, however, the factor action 147 can include stopping the current simulation process 159. The factor action 147 can then include storage of termination state data 163 before resuming the simulation action 146 to terminate the simulation 164. After stopping the simulation The current simulation 159, the simulation procedure 146 can also include determining whether the procedure is to have 160 numbers

<p>25 Greater than simulations. If there is 160 for a larger number of simulations 160, then</p>

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Simulation actions can include capturing the next simulation to run 161 after which simulation 151 is started. If there are no additional simulations, simulation 162 completes.

In some embodiments, it can be a key process during the intelligent computational process factor, according to the embodiments of the invention, the automatic validation process and the decision process 155. For example, for simulations

<p>5 Matching to date, an engineer-user of simulation control can choose to use at least two options—that is, according to one or more of at least two models that relate to date-matching—the automatic validation process and decision process 155. For example, in at least the first option , The automatic validation and decision process 155 can include, first, the calculation of the difference between the date data and the simulation data. For example, a select calculation can include delta (8), where:</p>

00 e) II

n - (history !0+ sim)/2.00) . 29.

10)

In the above equation, delta (8) can be a good differential delta. Furthermore, a "history" can represent a historical value, an observed value (ie, distinct measured reservoir values), such as, for example, one or more of a set of distinct measured reservoir values ​​for the hydrocarbon reservoir associated with the simulation. Similarly, a sim can represent one or more simulated data values ​​for a set of data

<p>15th Simulations associated with the simulation process at the time step. Moreover, it can represent</p>

<p>*OR• 00 a predetermined well weighting agent associated with a hydrocarbon well. One or more deltas Δ can be specified for each of one or more hydrocarbon wells. The automatic validation and determination process can include an error from each hydrocarbon well from each point of interest that is to be accrued in a global error measurement. For example it can include accounts for a group of wells</p>

20 hydrocarbon on:

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43 + 42 + [4t[]]]

43 + 42 + [4-y]]]

43 + 42 + [4t]]]

■■■+ 3]] 412 -a - 2 [412 -a - [[412 = 3 lbs]^p

In the previous equations, AwellJ could refer to the error measurement of a hydrocarbon well, i.e., a well variance value, and Aglobal could represent a global error measurement. The automatic validation and resolution process 155 can then include calculating an error percentage, or percent error, as

<p>5 He can then allow the operator to make a decision to terminate or continue the simulation process. For example, accounts can include:</p>

no.hist. ■pomts0 (,) g

In the above equation, err% can be a simulated error measurement of the hydrocarbon field.

After measuring a simulation error of the hydrocarbon field (err% in the previous equation), a factor of 10 can make a decision to terminate or continue the simulation based on the variation of the termination error of a given simulation.

in advance. For example, if the simulation error measure for a hydrocarbon field is greater than a predetermined simulation termination error tolerance, the operator can decide to terminate the simulation, while continuing the simulation can measure the simulation error measure for a hydrocarbon field no greater than the simulation termination error tolerance specified in advance. Alternatively, a measurement error related to . may be used

<p>15th To compare against the variance, such as the variance of the termination error of a predetermined simulation process.</p>

In at least a second option, for example, an engineer user could select a number of major hydrocarbon wells for matching at a specific point in time. A termination calibration can then be determined, for example, a predetermined well termination error, for a given well, for example, by using calculations including:

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l;5we

UGiKisti 001+5

% 211 : 577

6 - 5 25-1 (Jaa 01++01+920) 94

In the previous equation, for example, no. hist, points on the number of 'history' values ​​used to select. That is, it can have a number of distinct measured tank values ​​used to specify 8, for example. Moreover, in the previous equations, . can denote

<p>5 err % refers to a simulated hydrocarbon well error measurement, and tolerance can refer to a predetermined well termination error tolerance. The minimum number of wells that need to converge, within a predetermined well termination error tolerance, can then be determined to match an acceptable date—that is, a number of predetermined hydrocarbon wells. The automatic validation and resolution process 155 can then stop the simulation if the minimum number of wells does not meet at the point specified in</p>

<p>10 time. For example, selections can include:</p>

Uncle 001927115 6!!** 01115 +)?

stop else

continue

Embodiments of the invention may also include a non-temporary computer-readable medium with one or more computer programs stored in it that may be operated by one or more processors to enhance the hydrocarbon reservoir simulation of a group of hydrocarbon reservoirs, for example. can include

<p>15th One or more computer programs contains a set of instructions that, when executed by one or more processors, prompt one or more processors to perform a series of operations. Operations can include, for example, starting each set of hydrocarbon reservoirs from each set of fluid flow simulations. A set of fluid flow simulations can be configured to calibrate one or more hydrocarbon reservoir simulations associated with each set.</p>

<p>20 Corresponding to hydrocarbon reservoirs. A set of fluid flow simulations can be carried out, thus,</p>

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Define a set of simulations matching the date. Each of a set of date-matching simulations can be configured to run for a corresponding predetermined time period, and each corresponding predetermined time period can include one or more time steps. Each set of date-matched simulations can also be configured to output a set of simulation data in response

<p>5 Runs the simulation matching the corresponding date after each of one or more time steps. Each simulated data set can contain, for example, one or more simulated data values. Furthermore, each of the corresponding group of hydrocarbon reservoirs can have a group of hydrocarbon wells, and a group of hydrocarbon wells together can define a hydrocarbon field within each of the corresponding group of hydrocarbon reservoirs. can be initialized</p>

<p>10 Each of one or more simulated data values ​​to be associated with one of the group of hydrocarbon wells associated with each of the corresponding group of hydrocarbon reservoirs.</p>

Operations, for each set of hydrocarbon reservoirs, may also include each of a first set of one or more of a set of simulations dated prior to completion of the corresponding predetermined time period, in response to an exit after a time step, when a second step continues

<p>15th for one or more of a set of other date-matching simulations. For example, the first set of date-matching simulations can be terminated when each has a hydrocarbon field simulation error measurement that exceeds a predetermined simulation termination error tolerance. In this example, each of the second set of simulations lacks a date to measure a hydrocarbon field simulation error that exceeds the predetermined simulation termination error tolerance. maybe</p>

<p>20 The variance of the predetermined simulation termination error is related to predetermined values ​​of one or more threshold variables.</p>

In an example according to another model, the first set of date-matched simulations may be terminated when more than a predetermined number of hydrocarbon wells in each of the first set of date-matched simulations have a simulated hydrocarbon well error measurement that exceeds the error tolerance

<p>25 Finish a predetermined well. In this example, each of the second set of simulations has</p>

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Matching to date is less than a predetermined number of hydrocarbon wells so that each has a simulated hydrocarbon well error measurement that exceeds the predetermined well termination error tolerance. Furthermore, the predetermined number of hydrocarbon wells and the predetermined well termination error variance can be related to predetermined values ​​of one or more threshold variables.

<p>5 A limited, predetermined, integrated compute capacity aggregated to one or more processors may be available in response to the use of a simulation, and may be configured to have increased processing availability when the first set of date-matching simulations is terminated. Termination of the first set of date-matched simulations can thus increase the processing availability of fluid flow simulations within a predetermined, limited embedded computing power to one or more other operations.</p>

<p>10 A fluid flow simulation is run. Thus, termination of the first set of date-matching simulations can reduce the total runtime of the HRCS simulation.</p>

For example, each of the second set of date-matching simulations can run concurrently with one or more other set of date-matching simulations after the first set of date-matching simulations is finished. Furthermore, a set can include

<p>15th From the date-matching simulations of each set of hydrocarbon reservoirs to a number of predetermined date-matching simulations, and summing up the predetermined numbers of date-matching simulations to a set of hydrocarbon reservoirs that can select a total number of predetermined date-matching simulations. The completion of a total number of simulations matching a predetermined date can be scheduled to require a predetermined amount of time thus to determine the total time to complete</p>

<p>20 is expected. Termination of the first set of date-matching simulations for each set of hydrocarbon reservoirs can usefully push the process total of a predetermined number of date-matching simulations to terminate before the end of the total expected completion time.</p>

In some non-cache-readable medium having one or more computer programs stored in it, according to an embodiment of the invention, the set of instructions, when executed by one, may also

<p>25 or more processors, by pushing one or more processors to perform additional operations. for example</p>

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For example, operations can also include starting, in response to ending a date-matching simulation, and various other date-matching simulations. One or more of the one or more processors with increased processing availability in response to termination of the date-matched simulation may be used to start the other-date-matched simulation. Can thus use one or more of the one or

<p>5 More processors that have overprocess availability in response to terminate the date-matched simulation enable early start of the other date-matched simulation.</p>

A set of matching-date simulations can be configured to calibrate one or more hydrocarbon reservoir simulation models associated with each corresponding set of hydrocarbon reservoirs by comparing a set of distinct reservoir values ​​measured for each corresponding set of hydrocarbon reservoirs. Moreover, the hydrocarbon field simulation error measurement can be determined for a step-by-step simulation process

Response time for comparison of (1) one or more simulation data values ​​for a set of simulation data associated with the simulation corresponding to the date after the time step and (2) one or more set of distinct reservoir values ​​measured for each of the corresponding set of hydrocarbon reservoirs.

On some non-cache-readable media that has one or more computer programs stored on it,

<p>15th According to one embodiment of the invention, the set of instructions, when executed by one or . can also be</p>

More than one processor, by pushing one or more processors to perform other additional operations. Operations for each set of hydrocarbon reservoirs may also include, for example, calculating one or more delta values ​​for well variances for each set of date-matching simulations after a time step. The delta values ​​of well variances can be in response to the reception of one or more

<p>20 The set of distinct reservoir values ​​measured for each of the corresponding set of hydrocarbon reservoirs. Furthermore, one or more delta values ​​for well variances can be deltas between both one or more simulated data values ​​of the time step-related simulation data set and one or more of the set of measured distinct stock values. The delta values ​​for well variances can also be based on a function of (1) each of one or more simulation data values ​​of the simulation dataset associated with the time step,</p>

<p>25 (2) each of one or more of a set of distinct measured reservoir values, and (3) a specific well weighting factor </p>

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in advance. The operations may then include summing, for each group of hydrocarbon wells, each of one or more delta values ​​of the well differentials associated with the corresponding hydrocarbon well. The sum of one or more delta values ​​for well variances can determine the simulated well variance value. In some circumstances, for example, the processes can also still include, for each of a set of simulations

<p>5 Matching to date, on the measurement of hydrocarbon field simulation error by using simulation well variance values ​​for each hydrocarbon field group of hydrocarbon wells. In another embodiment, for example, operations could include determining, for each group of hydrocarbon wells in each of a set of matched-date simulations, the measurement of a simulation error of the hydrocarbon well by using the simulation well's variance value.</p>

10

15

In some non-temporal computer-readable environments that have one or more computer programs stored in them, according to an embodiment of the invention, the set of instructions, when executed by one or more processors, may also prompt one or more processors to perform additional operations , such as, for example, receiving predetermined values ​​of one or more threshold variables in response to user input. In addition, each of the one or more processors can have a predetermined limited individual computing power. A single finite predetermined compute power of a processor can be, for example, a small portion of the predetermined finite embedded compute power of one or more processors that is determined by a mathematical function of a predetermined finite integrated compute power and a number of one or more processors .

In some non-temporal computer-readable media that has one or more computer programs stored

<p>20 In which, according to one embodiment of the invention, an instruction set, when executed by one or more processors, can also drive one or more processors to perform other additional operations. For example, operations can also include restarting a date-matched simulation that is terminated by using one or more of one or more processors that have increased processing availability in response to the termination of a date-matched simulation. Can thus use one or more of the one</p>

<p>25 One or more processors with increased processing availability in response to the termination of a simulation matching the date </p>

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It enables a restart before the simulation process matches the completed date. In some cases, the operations can then include storing data representing the termination state of a terminated date-matching simulation, for each of one or more terminated-date-matching simulations. Storing data representing the termination state of a terminating simulation can thus allow a restart of a simulation process

<p>5 Matches the terminated date when required in response to the simulation's termination status matching the terminated date.</p>

In some non-cache-readable environments that have one or more computer programs stored in them according to another form, one or more computer programs may contain a set of instructions which, when executed by one or more processors, drive one or more Over processors to perform a series of operations. Operations can include, for example, start - for

<p>10 Set of hydrocarbon reservoirs - all set of fluid flow simulations. A set of fluid flow simulations can be configured to predict the future behavior of each corresponding set of hydrocarbon reservoirs. The set of fluid flow simulations can thus define a set of simulations. In addition, each forecast simulation process group can be configured to run for a corresponding predetermined time period, and each corresponding predetermined time period can include:</p>

<p>15th One or more time steps. Each set of prediction simulations can also be initialized to output a simulation dataset in response to the corresponding prediction simulation after each of one or more time steps. Each simulated data set can include one or more simulated data values, and each corresponding set of hydrocarbon reservoirs has a set of hydrocarbon wells. Each of one or more simulated data values ​​can be initialized to be</p>

<p>20 Connecting it to one of the hydrocarbon wells.</p>

Operations may also include terminating, for each set of hydrocarbon reservoirs, each of the first set of one or more set of simulations before terminating the corresponding predetermined time period, in response to the output after a time step, while a second set continues for another one or more than one set of prediction simulations. The first set of prediction simulations 25 can be selected when one or more of the one or more simulation data values ​​of the simulation data set

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Associated with each of the first set of prediction simulations after the time step outside the inequality of termination of the simulated data values. One or more simulation data values ​​for a simulation data set associated with each of the second set of prediction simulations after a time step, on the other hand, can be included within the termination tolerance of the simulation data values. Termination tolerance can relate to data values

<p>5 Simulation with predetermined values ​​of one or more threshold variables, eg. A limited, predetermined, integrated compute capacity aggregated to one or more processors can be available in response to the use of a simulation and can be configured to have increased processing availability when the first set of prediction simulations is completed. Thus, termination of the first set of prediction simulations when a second set of simulations continues can increase the availability of processing for simulations</p>

<p>10 Fluid flow within the finite and predetermined built-in computing power to one or more other fluid flow simulations being run. Thus, termination of the first set of prediction simulations while the second set of prediction simulations is in progress can reduce the total runtime of the hydrocarbon stockpile simulation.</p>

For example, each of the second set of coincidence prediction simulations can work with

<p>15th Another one or more second set of forecast simulations after completing the first set of forecast simulations. Furthermore, the set of forecast simulations for each ensemble of hydrocarbon reservoirs can include a number of predetermined forecast simulations, and the sum of predetermined numbers of forecast simulations for the ensemble of hydrocarbon reservoirs can specify the total number of predetermined forecast simulations. In addition, the completion of the total number of . can be scheduled</p>

<p>20 From predetermined forecast simulations to order a predetermined amount of time and thus determine a total expected completion time. Termination of the first set of prediction simulations for each group of hydrocarbon reservoirs can advantageously push a total of predetermined number of prediction simulations to terminate before the end of the total expected completion time.</p>

In some circumstances, a set of prediction simulations can be configured to predict future behavior

25 for each of the corresponding group of hydrocarbon reservoirs by using one or more models

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Hydrocarbon reservoir simulation associated with each of the corresponding group of hydrocarbon reservoirs. One or more hydrocarbon reservoir models may be calibrated by using a set of distinct measured reservoir values ​​and thus one or more calibrated hydrocarbon reservoir simulation models. Furthermore, each of the set can be related to prediction simulations associated with an additional pathway of

<p>5 Procedures for developing each of the corresponding set of hydrocarbon reservoirs associated with the forecast simulation process</p>

The debate and thus determine the development strategy. The predetermined values ​​of one or more threshold variables and the termination tolerance of the simulation data values ​​can be associated with one or more predetermined strategic outcome values ​​for one or more development strategies. In addition, the instruction set, when executed by one or more processors, can also drive one or more of the

<p>10 Processors to perform data storage representing the termination state of a terminated prediction simulation, for each of one or more terminated prediction simulations. Storing such data therefore allows for validation of the development strategy associated with the terminated prediction simulation process when necessary in response to the termination condition of the terminated prediction simulation. In addition, one or more predetermined strategic outcome values ​​for one or more development strategies may include a measurement of the maximum proportion of water produced</p>

<p>15th Predetermined for one or more groups of hydrocarbon reservoirs, eg.</p>

In some non-cache-readable environments that have one or more computer programs stored in them, the instruction set, when executed by one or more processors, may also prompt one or more processors to run, in response to the termination of a prediction simulation , another different prediction simulation process. Various other prediction simulations can be started by using

<p>20 One or more of the one or more processors that have increased processing availability in response to the termination of the prediction simulation and thus can start before the other prediction simulation. Additionally, each one or more of the processors can have a predetermined limited individual computing power. A single processor's predetermined finite computing power can be a small portion of a predetermined, finite integrated computing power of one or more processors defined by a mathematical function</p>

<p>25 For limited and predetermined embedded computing power and a number of one or more processors. bonus</p>

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Thus, the instruction set, when executed by one or more processors, can also prompt one or more processors to perform an reception of predetermined values ​​of one or more threshold variables in response to user input.

For example, it can include a arithmetic operation, according to models related to date matching and operations

<p>5 Simulate a prediction, on the following steps, as illustrated in Figure 9, for example. User interaction 145 can include loading historical data 230 and checking or interrogating historical data 231. Historical data can include, for example, distinct, measured stock values. User interaction can also include specifying threshold value variables 232, specifying threshold value variables for a termination calibration to select a simulation process 233, and making the values ​​that are specified</p>

<p>10 Variable threshold and termination calibration are available for operator intelligent calculation. A termination calibration can include, for example, tolerance values, such as a simulation termination error tolerance, a well termination error tolerance, or termination error tolerance for simulated data values. In some cases, such as in some embodiments of matching dates, a termination calibration may also include a number of predetermined hydrocarbon wells. The simulation procedure 146 can include whether the presence procedure is 240, and, if not, the completion of the simulation</p>

<p>15th 243. If in the presence of additional simulations a presence of 240 is performed, it can also include</p>

Run the simulation 146 to run the simulation for a time step 241 and determine if the time step is the last time step to run 242. If the time step is the last time step to run 242, the simulation run 146 can then include Determining whether there are additional processes, the presence of 240 is performed. If the time step is not the last time step, the presence of 240 is performed

<p>20 By doing 242, an intelligent arithmetic operator can control the simulation process. Action may include</p>

Factor 147 checks for threshold value variables for predetermined values ​​and calibrates 250 Terminates the predetermined simulation process, determines whether one or more termination calibrations are met, and, if not, returns control to the simulator to run the simulation for another time step 241 . The 251 termination criteria can be met, in the course of a date-matched simulation, at

<p>25 For example, when a hydrocarbon field simulation error measurement exceeds the simulation termination error tolerance</p>

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A predetermined or, alternatively, when more than a number of predetermined hydrocarbon wells have a hydrocarbon well simulated error measurement that exceeds the predetermined well termination error tolerance. In the context of a prediction simulation, however, 251 termination calibrations may be met when one or more of the one or more simulation data values ​​of the simulation data are outside the termination tolerance of the simulation data values,

<p>5 For example. If 251 is encountered with one or more termination calibrations, then a worker's action 147 can include termination of the simulation 252 and exiting 253 rewrites before control returns to the simulator. The run of simulation 146 can then include terminating the simulation process 244, producing a simulation output 245, and determining if there are simulations being run of 240. The steps could include, for example, the following:</p>

<p>10 Load historical data</p>

Investigate/interrogate historical data

Identify threshold variables

Define the values ​​of the threshold value variables to define the termination criteria

Making values ​​for the threshold value variables and the termination titration

<p>15th Available for smart . arithmetic operator</p>

For each simulation run

start simulation run Start a simulation process

Each step has a time step

output time step information

<p>20 If it's not the last step of time</p>

Agent Control

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Check values ​​for the threshold value and termination calibration variables

If a calibration interview is terminated

End the simulation process

Write Restart Output

<p>5 Agent output</p>

Simulator Control

Simulator Control End simulator

wrap-up simulation

also

<p>10 If not the last simulation state</p>

Go to start the simulation process

also

complete

end if lo

<p>15th also</p>

Continue the simulation process

end if lo

end of

end of

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An entity can have approximately 100,000 requests for conventional procedure (i.e., forecasting) and hydrocarbon stockpile simulation studies in one year. The following is a representative exercise to illustrate the possible savings that are produced by the models of the invention. An entity has a total of 100,000 simulations in a given year.40% of the savings realized, will be

<p>5 Future savings 10,000 simulations * 40%, that is, 40,000 operations. Moreover, if the average node-hours for each simulation job is 600 knot-hours, the total savings of total node-hours is about 400,000 operations * 600 knot-hours, i.e. 24,000,000 knot-hours are saved. Assuming that four (4) groups of nodes provide 17,940,480, i.e., 1.3-512 groups are saved. Thus, the invention models can be a major step towards</p>

<p>10 A final goal for storage simulation engineers: to be able to automatically date-match a storage model using optimal computing and storage resources, for example.</p>

Several simulation studies were conducted to test a calculation process according to the model of the invention. The results show savings of fifty percent (50%) in simulations that lose their resources if they continue. Moreover, the results of studies and decisions related to invention models can be compared with a course of action

<p>15th Engineers manually identify good and bad simulations as part of the date matching process. There are two illustrative examples. The first example includes fifty checks of simulation simulations for history, as illustrated in Figure 8a. The examination can be part of a date-matching simulation. More specifically, you can usually enter a date match during phases that search the solution space of a problem to find the solution (date match). In a feature of the solution space, checking can be</p>

<p>20 Operations are "tuning" operations in the sense that they can search a larger solution space and help the solution space limit or size for a next stage: purification. In the refinement stage, refinements can only pertain to searching a finite and measured solution space as in the previous stage (checking) looking for a solution or solutions to a problem. In the first illustrative example, when the simulation termination error tolerance was ten percent (10%) . (, 45 processes have been stopped. That is, when the maximum allowable error that can be</p>

<p>25 . Determined by predetermined values ​​of a controlled variable threshold value (eg 10%), can be </p>

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45 of the scans are stopped. When the simulation termination error tolerance is mitigated, however, the number of simulations can be reduced by the operator. For example, when the simulation termination error tolerance was (20%), 32 processes were halted. When the simulation termination error tolerance was thirty percent (30%), twenty-one processes were halted. The second example includes

<p>5 Fifty refinements of simulations matching the date, as illustrated in Figure 8b. In the second example, when the simulation termination error tolerance is ten percent (10%), twenty one stops. Similarly, while the simulation termination error tolerance is mitigated during purification, the number of simulations to be stopped can be reduced by a factor For example, when the simulation termination error tolerance is twenty percent (20%), twenty-five percent (25%),</p>

<p>10 Or thirty percent (30%), one process is halted. The simulation termination error tolerances represented in Figure 8a and Figure 8b can pre-determine the maximum allowable global errors measured from hydrocarbon wells associated with a hydrocarbon stockpile simulation model, for example. Rerun the study that the worker can automatically and accurately match a simulated job calibration set by an engineer, that is, determine whether the process is good or acceptable and should</p>

<p>15th It continues or, alternatively, is bad or unacceptable and must be terminated. In addition, reruns of the study determined that controlling the variance of the termination error of the simulation process can improve the accuracy and severity of the factor.</p>

The accuracy of the results illustrated by the factor is illustrated, for example, in Figure 7. The percentage of water produced over time is plotted, for example, in Figure 7, to show how it compares

<p>20 The results of the percentage of water produced by simulating the historical product water percentage data. The lines associated with the simulations are named, as illustrated, according to the following convention: the first three numbers represent the volume of the associated hydrocarbon storage simulation model (for example, the number of cells in the simulation), the four represent the associated simulation model configuration, and the last number represents the (if any) any additional purifications associated with date simulation variables, eg, measured stock features.</p>

<p>25 Explanation: Simulations associated with lines 303, 304, 305, 306, 309 and 310 . are terminated</p>

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on top of the table. There is no early termination of the simulation associated with line 307, however, because

The simulation associated with line 307 is reasonably close to the historical water yield data that is represented by line 308. As shown, line 307 is the closest—and most closely related to—line 308. In addition, line 302 represents the output of the simulation according to for art

<p>5 Previously, line 301 is an example of outputting the same simulation as line 302 according to one of the models of the invention. That is, line 301 shows when the simulation was carried out according to the previous art completed according to one of the models of the invention. Notably, the simulation, which was unacceptably far apart from the historical data, was terminated earlier according to one of the models of the invention compared to previous art. Moreover, it can be to finish the simulation process early - as represented by line 301 - to be produced more</p>

<p>10 Useful for greater availability of computing power and limited resources when compared to prior art, as exemplified by line 302. Each of the simulations associated with lines 303, 304, 305, 306, 307, 309, and 310 is associated with configuring predetermined storage properties—that is, parallels Gauge stock- eg permeability. In other words, each simulation can be associated with the initialization of a measured storage function that can be previously referenced and specified by a simulation engineer, for example.</p>

<p>15th Invention models can help better manage and improve limited computing and storage resources. Models can thus help reduce the growth of a collection per year to simulate the highly efficient inventory and storage requirements of an entity. Models can also improve rotation times for multidisciplinary origin teams conducting hydrocarbon stockpile studies. Models can focus on identifying useful simulations with useful automatic selection and early eliminations that will be ignored in</p>

<p>20 Finish by engineers etc. I weigh. In many embodiments of the invention described herein, a person of ordinary skill in this field may perceive that many types of memory are computer-readable such as memory described herein by reference to several computers and servers, for example, computer, server, computer, server network, or other computers with models of the present invention. Examples of computer-readable media include, but are not limited to: Non-type media</p>

<p>25 Fixed, encrypted hard disk such as read-only-memory ROMs,</p>

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CD-ROMs, "Compact Disc read-only-memory" discs, DVD-ROMs, or Electrically EEPROMs (Erasable Programmable Read-Only Memory), on a recordable type such as floppy disks disks, CD- hard disk drives, hard disk

<p>5 R/RWs, RAM "Random Access Memory" DVD, RWs "writer" / Digital Versatile Disc (DVDs) R "reader" + DVD “Digital Versatile Disc” flash drives, memory sticks, and any newer types of memory, and a transfer type medium such as 10 digital and analog communication links. For example, such a medium may include working instructions, as well as instructions relating to the systems and steps of a method previously described that can operate on a computer. Persons skilled in the art will understand that such medium may be in other locations in place of, or in addition to, the locations described for storing computer software products, for example, that include software on it. People skilled in this field will understand that various models</p>

<p>15th The software and electronic components described previously may be executed and maintained by a device</p>

electronic, software, or a combination of the two, and such models may be thought of by the models of the present invention.

Models of methods, systems, and a non-temporary computer-readable medium in which a computer program is stored for the present invention are disclosed in the drawings and specifications, and although 20 specific terms are identified, the terms are used in descriptive direction only and not for the purpose of limitation. Examples of methods, systems, and non-temporary computer-readable media with a computer program stored in it for the present invention are described in detail by reference to those examples shown. It will be clear, however, that various changes and modifications are made within the scope and range of models for methods, systems, and a non-temporary computer-readable medium with a computer program stored in it for the present invention as described in

<p>25 The above limitation, and such modifications and changes are equivalent and part of this disclosure.</p>

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