Systems and methods for subsurface oil recovery optimization.

(54) Title: SYSTEMS AND METHODS FOR THE OPTIMIZATION OF RECOVERY OF SUBSURFACE OIL.

(54) Title: SYSTEMS AND METHODS FOR SUBSURFACE OIL RECOVERY OPTIMIZATION.

(57) Summary

Systems and methods for the optimization of secondary and / or tertiary recovery of subsurface oil based on optimization analysis of any short-term, medium-term or long-term of the selected zones, wells, patterns / groups and / or fields.

(57) Abstract

Systems and methods for subsurface secondary and / or tertiary oil recovery optimization based on either a short term, medium term or long term optimization analysis of selected zones, wells, patterns / clusters and / or fields.

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Mexican Institute of Industrial Property

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PATENT TITLE NO. 344827

LANDMARK GRAPHICS CORPORATION

2107, Citywest Blv. Bldg. 2, Houston, Texas, 77042, USA

SYSTEMS AND METHODS FOR THE OPTIMIZATION OF RECOVERY OF SUBSURFACE OIL.

Int.CI.8: E21B47 / 00; G06F17 / 10; G06G7 / 48

RANJAN PRIYESH; BURT GORELL SHELDON; AMIT KUMAR; ALVIN STANLEY CULLICK; GUSTAVO A. CARVAJAL; KARELIS ALEJANDRA URRUTIA;

HASNAIN KHAN; LUIGI SAPUTELU; HATEM NASR

REQUEST

International filing date:

MX / a / 2016/001814 October 2012 ^ Divisional Patent Number: 337098

PRIORITY

Country:

Date:

Number:

US October 2011

61/544,202

Validity: Twenty years

Expiration Date: October 5, 2032 The reference patent was granted based on articles 1, 2, fraction V, 6 fraction. onHI, andWaH 'Lsyd' the Industrial Owner.

; In accordance with article 23 of the Industrial Property Law, this patent is valid for twenty years, issued from the date of filing of the international application and will be available until the end of the year. to keep the sections valid. -;

Fluien subscribes the Industrial Pre-Ownership (01/06/2004, 06/16/200

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Title you not Official 01/25/2 (

Jnciso a), 4^or and 12th fractions I _28/07/2|

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III and 7 bis 2 Se the Law of the ^ «994, 10/25/1996, 12/26/1999, 05/17/1999, 2012/01 and 04/09/2012); items t¹, 3 fraction V lili of the Regulations of the Mexican Institute of Industrial Property (DOF 14/12 / 19®, amended the article * and Si y Sfr-tteFES Organic statute

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of the Mexican Institute of Industrial Property (DOF 12/27/1999, amended on 10/10/2002, 07/29/2004, 08/04/2004 and 09/13/2007); 1^or, 3^orand 5th subsection a) of the Agreement that delegates powers to the Deputy General Directors, Coordinator, Divisional Directors, Heads of Regional Offices, Divisional Deputy Directors, Departmental Coordinators and other subordinates of the Mexican Institute of Industrial Property. (DOF 12/15/1999, amended on 02/04/2000, 07/29/2004, 08/04/2004 and 09/13/2007).

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Arenal No. 550 Floor 1, Coi. Santa María Tepepan town. Xochimilco. C P. 16020.

Mexico City Tel. (55) 53 34 07 00 lvwiv impí gob.ni

Issue Date: January 5, 2017

THE DIVISIONAL DIRECTOR OF PATENTS

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NAHANNY CANAL REYES

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SYSTEMS AND METHODS FOR THE OPTIMIZATION OF RECOVERY OF

SUBSURFACE OIL

FIELD OF THE INVENTION

The present invention relates generally to systems and methods for optimizing subsurface oil recovery. More particularly, the invention relates to the optimization of secondary and / or tertiary recovery of subsurface oil based on optimization analysis of any short-term, medium-term or long-term of the zones, wells, patterns / groups and / or selected fields.

BACKGROUND OF THE INVENTION

Different systems and methods are well known to maximize secondary and / or tertiary recovery of subsurface oil. Current systems for maximizing secondary and / or tertiary recovery are generally based on many steps, on different systems, and software tools, that users need to configure and manage themselves. This is a manual process, where the user will create a model of numerical analysis of the deposit, will run the model with few decisions and / or different operating parameters, will analyze the

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INDUSTRIAL results and choose the best answer. The non-automated process often requires running multiple applications, which are not integrated, to obtain results that will be integrated. As a result of the different applications required, a significant amount of reformatting data may be required between applications, creating additional work and the potential for error. Also, as the process is carried out manually in many publications, there are no traces of electronic review for later review. This can be further complicated since analysis tools are generally generic and are not designed to integrate data and to provide and evaluate simulations according to varying criteria. Current systems provide very little feedback on model quality and verification to ensure that the results are realistic. They do not provide interactive graphical feedback to the user at different levels of field operations and do not provide true optimization tools and decision support. They also don't take advantage of the true value of real-time data from the field. As a result, current systems are manual, laborious, and require data transfer from one system to another while requiring users to verify that the output of a system is usable as the

INSTITUTO MEXICANO DE LA REOPUOAL · INDUSTRIAL entry to another system. These shortcomings in current systems mean that the number of people who can do this type of work is very limited. As a result, this process is carried out by a limited number of experts within an organization. With a currently available set of tools, even these experts take a long time to carry out the process and are prone to errors due to the manual nature of the process.

As a result of the limitations of current systems, users generally do not see multiple scenarios to account for possible uncertainties in the underlying deposit's numerical model. Nor do users exhaustively use optimization technologies to analyze, rank and choose the best development operations to increase secondary and / or tertiary oil recovery. This often excludes users from addressing uncertainties in a reservoir model by periodically re-evaluating selected scenarios based on data such as historical reservoir performance, patterns, wells, and / or zones or other data. On the other hand, in addition to all the limitations listed above, current systems do not provide good tools to allow a user to update a model, or series of

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INDUSTRIAL models. These difficulties in the generation of a first model serve as an impediment to the generation of later updates.

Nor do current systems address the overall performance of the field or the effectiveness of secondary or tertiary recovery processes. Practitioners of current processes will generally recognize that sweep efficiency is an important measure for the effectiveness of the recovery process. Sweep efficiency can be calculated at different locations in a field and at different scales. For example, sweep efficiency could be calculated locally near a well, at a zone level, between two wells, at a pattern level, at a field level, and at different levels in between. Currently, there is no good method for measuring or calculating sweep efficiency status indicators. There is also no integrated system and method for the simultaneous simulation and optimization of well production at different scales or classifications from field to equipment levels.

BRIEF DESCRIPTION OF ΙΛ INVENTION

The present invention therefore meets the above needs and overcomes one or more deficiencies in the current art by providing systems and methods for optimization of

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OF INDUSTRIAL PROPERTY Secondary and / or tertiary oil recovery based on optimization analysis of any short-term, medium-term or long-term of the selected zones, wells, patterns / groups and / or fields.

In one embodiment, the present invention includes a method for optimizing long-term oil recovery, comprising: i) selecting one or more zones, wells, patterns / groups or fields wherein said one or more zones, wells, patterns / groups or fields are selected from a scan efficiency status display, comprising one of a current scan efficiency status display and one of multiple predicted scan efficiency status displays; ii) showing multiple optimization scenarios and corresponding actions for optimizing said one or more zones, wells, patterns / groups or fields selected during an evaluation of a plan for the development of a field; iii) select one or more of the optimization scenarios and display each corresponding action; iv) selecting a prediction date for each selected optimization scenario; and v) show said one or more optimization scenarios, the effect of each corresponding action in said one or more zones, wells, patterns / groups or fields selected on the prediction date, and an updated field development plan using a system of computer, the updated field development plan is displayed for a field with a respective net present value calculation and projected production parameters.

In another embodiment, the present invention includes a program carrier device for carrying computer-executable instructions for optimization of long-term oil recovery. The instructions are executable to implement: i) select one or more zones, wells, patterns / groups or fields where said one or more zones, wells, patterns / groups or fields are selected from a sweep efficiency status display, which comprises one of a current scan efficiency status display and one of multiple predicted scan efficiency status displays; ii) showing multiple optimization scenarios and corresponding actions for optimizing said one or more zones, wells, patterns / groups or fields selected during an evaluation of a plan for the development of a field; iii) select one or more of the optimization scenarios and display each corresponding action; iv) selecting a prediction date for each selected optimization scenario; and v) show said one or more optimization scenarios, the effect of each corresponding action in said one or more zones, wells, patterns / groups or fields selected on the prediction date, and an updated field development plan, the plan of Updated field development is displayed for a field with a respective net present value calculation and projected production parameters.

Additional aspects, advantages, and embodiments of the invention will become apparent to those skilled in the art from the following description of the various embodiments and related drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is described below with references to the accompanying drawings in which like elements are referenced by like reference numerals, and in which:

Figure 1 illustrates a general process for subsurface oil recovery optimization in accordance with the present invention.

Figure 2 is a flow chart illustrating one embodiment of a method for implementing the present invention.

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Figure 3 is a flow chart illustrating one embodiment of a method for carrying out step 216 of Figure 2.

Figure 4 is a flow chart illustrating one embodiment of a method for carrying out step 220 of Figure 2.

Figure 5 is a flow chart illustrating one embodiment of a method for carrying out step 22 4 of Figure 2.

Figure 6 is a block diagram illustrating one embodiment of a system for implementing the present invention.

Figure 7 is an exemplary graphical user interface illustrating step 204 of Figure 2.

Figure 8 is an exemplary graphical user interface illustrating step 206 of Figure 2.

Figure 9 is an exemplary graphical user interface illustrating step 306 of Figure 3.

Figure 10 is an exemplary graphical user interface illustrating step 324 of Figure 3.

Figure 11 is an exemplary graphical user interface illustrating step 406 of Figure 4.

Figure 12 is an exemplary graphical user interface illustrating step 412 of Figure 4.

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Figure 13 is an alternative exemplary graphical user interface illustrating step 412 of Figure 4.

Figure 14 is an exemplary graphical user interface illustrating step 422 of Figure 4.

Figure 15 is a table illustrating exemplary levels of optimization provided by the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The subject of the present invention is described specifically, however, the description itself is not intended to limit the scope of the invention. The subject can therefore also be incorporated in other ways, to include different steps or combinations of steps similar to those described in this document, in conjunction with other present or future technologies. Furthermore, although the term step may be used in this document to describe different elements of the methods employed, the term should not be construed as implying any particular order between the different steps disclosed in this document unless expressly limited otherwise. by description to a particular order. While the following description refers to the oil and gas industry, the systems and methods of the present invention are not¹⁰ IMPI limited to them and you can also eSí3g £ teas industries to achieve results = ι · ίmí i arpg - ........— ~

The present invention includes systems and methods for optimizing oil recovery by reducing unwanted fluid / gas production, reducing repair downtime, reducing overshot oil and gas, and maximizing present value through optimization. injection and production profiles. Systems and methods therefore consider intelligent manipulation of subsurface displacement profiles; surface and facility optimization constraints, well intervention / re-completion designs, and dynamic field development planning through decisions to drill and design new production / injection / observation wells.

The systems and methods carry out all permutations and combinations with monitoring, diagnostics and optimization from micro to macro scale ranging from equipment level to zone level to well level to pattern / cluster level to , finally, the level of the tank / field. The systems and methods allow the user to carry out present and / or predictive diagnostics in the field and / or state of sweep efficiency, as well as to advise the user of the optimal optimization actions

INDUSTRIAL PROPERTY for short, medium and long term time frames. The systems and methods allow the user to interactively carry out comparative what-if scenarios (war games) with the previously advised optimization actions, generate appropriate business cases, and therefore take and implement the appropriate optimization actions. that help maximize oil recovery and economic value.

The systems and methods use real-time surveillance field data to provide advanced value from integrated asset management, providing automated advice for multiple short, medium and / or long term wells / patterns and optimization at the field level. The systems and methods allow staff to perform predictive analysis on the effect of selected optimization actions, and deliver an intuitive user interface for improved collaborative decision-making among asset, warehouse, operations, and production staff. The systems and methods, therefore, or else the need for laborious simulation and optimization in separate actions.

In short, systems and methods enable monitoring of the subsurface condition of a production field and provide automated advice on proactive diagnostics. ₁₂ ΙΜΡΙ @

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Method Description

Referring now to Figure 1, a general process 100 for the recovery of subsurface oil in accordance with the present invention is illustrated.

In step 102, process 100 identifies the current state of the field. One embodiment of a method for identifying the state of the field today is illustrated by step 202 in Figure 2.

In step 104, process 100 predicts the state of the field. One embodiment of a method for field state prediction is illustrated by steps 204-208 in Figure 2.

In step 106, process 100 diagnoses the state of the field for today and the future, which may include identifying and detecting the oversprayed and unswept oil points using a moving water saturation function. One embodiment of a method for diagnosing the state of the field for today and the future is illustrated by step 210 in Figure

2.

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In step 108, process 100 advises optimization for short, medium, and long terms, if optimization is desired. One embodiment of a method for determining the desired optimization is illustrated by steps 212, 214, 218, and 222 in Figure 2.

If optimization is desired, then the user must also select whether the time frame for optimization will be short term, medium term, or long term. If short-term optimization is desired, then one modality of a method for short-term optimization is illustrated by steps 302-306 in Figure 3. If medium-term optimization is desired, then one modality of a method for medium-term optimization term is illustrated by steps 402-406 in Figure 4. If long-term optimization is desired, then one embodiment of a method for long-term optimization is illustrated by steps 502-506 in Figure 5.

The optimization can be provided as an automated assessment for reactive and proactive optimization of sweep efficiency to achieve key performance objectives - including time horizons (from 1 day to any number of years), reduce water management (as a percentage ), reduce downtime for repair times (as a percentage), reduce

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- . ^{D £} IA AMONITY &amp; quot; dustrial oil exceeded, and increase the ^ &lt;- np ^ ...... 1¿h do n '^^ gg wells and re-completions (as a percentage). Optimization can also enable timely decisions based on real-time data to provide up-to-date, predictive models and provide expert system and optimized advice.

At step 110, process 100 includes what-if scenarios to evaluate and compare different optimization scenarios, which can also be considered as optimization war games. One embodiment of a method for conducting optimization what-if scenarios is illustrated by steps 308-316 in Figure 3 for short-term optimization, steps 408-416 in Figure 4 for medium-term optimization, and steps 508-516 in Figure 5 for long-term optimization.

In step 112, process 110 implements the optimization. One embodiment of a method to get or find the optimization implementation is illustrated by steps 318-326 in Figure 3 for short-term optimization, steps 418-426 in Figure 4 for medium-term optimization, and steps 518 -526 in Figure 5 for long-term optimization.

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The overall process 100 therefore provides a fully integrated subsurface tank management solution to improve sweep efficiency and allow warehouse and production personnel (probably engineers) to collaborate. This can be accomplished while monitoring reservoir dynamics during production, using surface and in-hole sensors, updating and simulating reservoir and well models. This can provide control strategies for short production optimization and increased recovery using surface plugs, ICDs, and smart wells while implementing optimization strategies in future planning, such as infill drilling to recover surplus oil.

The process 100 for optimization can be reactive, simple proactive, or enhanced proactive (proactive plus). Reactive optimization can be characterized as an immediate reaction to current conditions. Reactive optimization can occur in the short term and can be directed at actions such as optimizing shutter settings and production / injection rates. Simple proactive optimization can be characterized as an action based on predicted conditions, such as to predict fluid movement away from the wellbore and therefore to optimize

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INDUSTRIAL ^ ¿2L £ -subsurface operations by taking measures such as plugging a valve fitting inside the well in order to increase total recovery. Simple proactive optimization also focuses on optimizing long-term field development planning such as scheduling locations, repairs, their settings, etc. future producer / injector filler drilling. Enhanced proactive optimization, on the other hand, provides right-time integration of exploration, drilling, completion, and production disciplines while evaluating the appropriate plan of action to develop a field to ensure that there is sufficient time after the impacts are identified. optimization options that could affect them. Simple proactive optimization can occur over the medium term to the long term (such as, but not limited to, three months to 2 years) and includes reactive optimization actions along with short and medium term field development plan updates. term. Therefore, integration involves running various tank depletion scenarios as well as cost / benefit analysis scenarios, in real time, helping in this way to plan the best integrated solution across all disciplines of a tank life cycle. asset development. Proactive optimization enhanced by

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OS LA TRORUDA »INDUSTRIAL example, could allow the operator to change completion and production planning in real time for better final depletion, while actually drilling and gathering additional information about the deposit. The goals for each of these exemplary levels of optimization are illustrated by Table 1500 in Figure 15.

Therefore, process 100 is dependent on the appropriate timing of repository management including continuous repository viewing, proactive repository diagnostics and optimization, and predictive repository optimization analysis.

Referring now to Figure 2, a flow chart illustrates one embodiment of a method 200 for implementing the present invention.

In step 201, the current condition data or the previously calculated scenario condition data is selected using the client interface and / or the video interface that is described with reference to Figure 6. The selection of whether to use the Current condition data or previously calculated scenario condition data can be based on a subjective determination of whether current conditions or previous optimizations are used. Current condition data provides the ability to assess the current state of the field and to perform optimizations based on that data. Pre-calculated scenario condition data provides the ability to review the past state of the field relative to the current state and to perform optimizations based on the saved data, which may include optimized short, medium, or even long-term data .

At step 202 the current scan efficiency status is shown using techniques well known in the art and the video interface which is described with reference to Figure 6. Subsurface visualization techniques and current sweep efficiency status indicators, for example, can be used with integrated current condition data, pre-calculated scenario condition data, and historical data to provide a visualization of zones, wells , patterns / sectors and / or classified fields representing the current sweep efficiency status. Effective subsurface visualization requires visualization of reservoir dynamics as subsurface changes in the well, near the well, and away from the well. One goal of subsurface visualization is to create a very high resolution three-dimensional (3D) visualization interface, which can include different features including

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fiber optic, surface deformation visualization, 3D fluid displacement visualization, visualization

Oil bypassed 3D, oil / water interface display, streamline display, field / zone / well maps, isobaric maps, saturation maps, injection patterns at subsurface zone levels, and zone level designations production / injection.

In step 204, a future date is selected for the prediction of the sweep efficiency state without optimization and the number of intervention periods is selected using the client interface and / or the video interface that is described with reference to Figure 6. The selection of the future date and intervention periods is subjective and is based on the user's preference and / or experience. An example of a future date selected for the sweep efficiency status prediction without optimization and the number of intervention periods is illustrated by the graphical user interface 700 in Figure 7, which illustrates a future date four (4) years in the future and intervention periods of one year.

At step 206, displays of the predicted sweep efficiency status are generated at the selected future date and at the end of each of the intervention periods using techniques well known in the art.

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Figure 6. Displays include a sweep efficiency status rating for identified zones, wells, patterns / sectors, and / or fields as well as other potential user-defined spatial scales. An example of a display of the scan efficiency status predicted at a selected future date and at the end of each intervention period selected by Figure 7 is illustrated by the graphical user interface 800 in Figure 8.

In step 208, one of the predicted scan efficiency status displays or the current scan efficiency status display is selected using the client interface and / or the video interface that is described with reference to Figure 6. Each selected visualization can provide additional details, including history for sweep efficiency status indicators at any zone, well, pattern / sector, and / or field scale.

At step 210, the cause of any undesirable sweep efficiency status indicators for the selected sweep efficiency status display is diagnosed using well-known diagnostic techniques, such as those found in the

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DecisionSpace ™ software for ^ cpópybog simulation ·. ··· -Ler · cause can be displayed by an automated advisory feature that uses indicators including volumetric efficiency, void replacement, displacement efficiency, nominal pressure and capture factor of well (Fcap) layer by layer in the reservoir. The cause can also be diagnosed by comparing data for current conditions with historical data or data from previously calculated scenario conditions. Different diagnostics can also be carried out by evaluating a flow or production rate that is normalized by a length of the drilling interval. A streamline numerical calculation can also be used to estimate correlation factors and well designation factors.

In step 212, method 200 determines whether production optimization analysis is desired based on the results of step 210. If optimization analysis is desired, then method 200 proceeds to step 214. Alternatively, method 200 may proceed to steps 218 or 222 if optimization analysis is desired. Optimization analysis may be desirable, for example, if the cause of any undesirable sweep efficiency status indicators is identified by the diagnosis carried out in step 210. Otherwise, optimization analysis may not be desirable if no undesirable sweep efficiency status indicators. If optimization analysis is not desirable, then method 200 terminates.

In step 214, the method 200 determines if short-term optimization analysis is desired based on the results of step 210 and if the cause of any undesirable sweep efficiency status indicators can be resolved (e.g., by set a shutter). If no short term optimization analysis is desired, then method 200 proceeds to step 218. Alternatively, method 200 may proceed to step 222 if short term optimization analysis is not desired. If short-term optimization analysis is desired, then method 200 proceeds to step 216.

In step 216, short-term optimization is carried out. One embodiment of a method to carry out short-term optimization is illustrated in Figure 3.

In step 218, method 200 determines whether medium-term optimization analysis based on the results of step 210 is desirable and whether the cause of any undesirable sweep efficiency status indicators cannot be immediately resolved within a question. from one day to a few months (eg equipment repair). If mid-term optimization analysis is not desired, then method 200 proceeds to step 222. Alternatively, method 200 may proceed to step 214 if mid-term optimization analysis is not desired. If medium-term optimization analysis is desired, then method 200 proceeds to step 220.

In step 220, medium-term optimization is carried out. One modality of a method to carry out medium-term optimization is illustrated in Figure 4.

In step 222, method 200 determines whether long-term optimization analysis based on the results of step 210 is desirable and whether the cause of any undesirable sweep efficiency status indicators cannot be resolved immediately or in a few months but can be resolved within a year or more (eg, drilling new wells). The decision between conducting short-term optimization analysis, medium-term optimization analysis, or long-term optimization analysis is subjectively based on the experiences and skills of the person making the decision. If long-term optimization analysis is not desired, then method 200 ends. Alternatively, method 200 may proceed to step 214 or step 218 if optimization analysis is not desired at

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Long-term INDUSTRIAL. If long-term optimization analysis is desired, then method 200 proceeds to step 224.

In step 224, long-term optimization is carried out. One embodiment of a method to carry out long-term optimization is illustrated in Figure 5.

Referring now to Figure 3, a flow chart illustrates one embodiment of a method 300 carrying out step 216 in Figure 2.

In step 302, all zones, wells, patterns / groups and / or fields to be optimized are selected from the selected sweep efficiency status display using the client interface and / or the video interface that is described with reference. to Figure 6.

At step 304, a series of classified optimization scenarios and corresponding actions are shown for reactive optimization using the video interface that is described with reference to Figure 6 and techniques well known in the art. The series of ranked optimization scenarios and corresponding actions for reactive optimization are based on optimizing selected zones, wells, patterns, groups, and / or fields, which can be exported to a net present value calculator. Thousands of optimization scenarios can be created by simulating the tank or using proxy models.

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In step 306, one or more optimization scenarios can be selected and the corresponding action for optimizing the selected zones, wells, patterns / groups and / or fields is displayed using the client interface and / or the video interface that is described with reference to Figure 6. An example of a corresponding action display is illustrated by the graphical user interface 900 in Figure 9.

In step 310, a prediction date can be selected for each selected optimization scenario using the client interface and / or video interface that is described with reference to Figure 6. The prediction date determines the period of time to be used. Run each respective selected optimization scenario in a simulator.

In step 312, said one or more selected optimization scenarios and the effect of each corresponding action on the selected zones, wells, patterns / groups and / or fields are displayed on the prediction date using the video interface described with reference to Figure 6. The display may include, for example, changes in sweep efficiency status indicators, different subsurface display parameters for selected zones, wells, patterns / groups, and / or fields, and

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In step 314, method 300 determines whether optimization is desired based on the results of step 312. If optimization is desired, then method 300 proceeds to step 316. If optimization is not desired, then method 300 proceeds to step 318.

In step 316, the desired optimization scenario (s) can be selected from said one or more selected optimization scenarios for implementation using the client interface and / or the video interface described with reference to Figure 6.

In step 318, the data underlying the results of step 312 is saved.

In step 320, the data underlying the results of step 312 selected in step 316 for implementation is saved.

At step 322, method 300 determines whether the user has action approval to unilaterally implement the desired optimization scenario (s). If the user does not have action approval, then method 300 proceeds to step 324. If the user has action approval, then method 300 proceeds to step 326.

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In step 324, a request for implementation of the desired optimization scenario (s) can be generated and / or submitted with a business case report, recommendation and analysis using the client interface and / or the interface of video that is described with reference to Figure 6. An example of a request for implementation of the desired optimization scenario (s) is illustrated by the graphical user interface 1000 in Figure 10.

In step 326, the corresponding action (s) for each optimization scenario to be implemented can be remotely executed or approved for manual implementation using the client interface and / or the video interface that described with reference to Figure 6.

Referring now to Figure 4, a flow chart illustrates one embodiment of a method 400 for carrying out step 220 of Figure 2.

In step 402, all zones, wells, patterns / groups and / or fields to be optimized are selected from the selected scan efficiency status display using the client interface and / or the video interface that is described with reference. to Figure 6.

In step 404, a series of classified optimization scenarios and corresponding actions are displayed for the ₂₈ IMPI ^

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INDUSTRIAL proactive optimization using the video interface described with reference to Figure 6 and techniques well known in the art. The series of ranked optimization scenarios and corresponding actions for proactive optimization are based on optimizing selected zones, wells, patterns, groups, and / or fields, which can be exported to a net present value calculator. Optimization actions could be actions such as repairs / network-completions, compliance, surface instrumentation, and others.

In step 406, one or more optimization scenarios can be selected and the corresponding action for optimizing the selected zones, wells, patterns / groups and / or fields is displayed using the client interface and / or the video interface that is described with reference to Figure 6. An example of selecting one or more optimization scenarios is illustrated by the graphical user interface 1100 in Figure 11.

In step 410, a prediction date can be selected for each selected optimization scenario using the client interface and / or the video interface that is described with reference to Figure 6. The prediction date determines the time period that he runs every

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selected optimization scenario up simulator.

At step 412, said one or more selected optimization scenarios, the effect of each corresponding action on the selected zones, wells, patterns / groups, and / or fields on the prediction date, and an updated field development plan for the field with the respective net present value calculation and projected production parameters are displayed using the video interface described with reference to Figure 6. The visualization may include, for example, changes in sweep efficiency status indicators, different subsurface display parameters for selected zones, wells, patterns / groups, and / or fields, and different net present value derivatives for each scenario of selected optimization. An example of such a display is illustrated by graphical user interface 1200 and 1300 in Figures 12 and 13, respectively.

In step 414, method 400 determines whether optimization is desired based on the results of step 412. If optimization is desired, then method 400 proceeds to step 416. If optimization is not desired, then method 400 proceeds to step 418.

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In step 416, the desired optimization scenario (s) can be selected from said one or more selected optimization scenarios for implementation using the client interface and / or the video interface described with reference to Figure 6.

In step 418, the data underlying the results of step 412 is saved.

In step 420, the data underlying the results of step 412 selected in step 416 for implementation is saved.

In step 422, method 400 determines whether the user has action approval to unilaterally implement the desired optimization scenario (s). If the user does not have action approval, then method 400 proceeds to step 424. If the user has action approval, then method 400 proceeds to step 426. An example of action approval to implement the desired optimization scenario (s) is illustrated by the graphical user interface 1400 in Figure 14.

In step 424, a request to implement the desired optimization scenario (s) can be generated and / or sent with a business case report, recommendation and analysis using the client interface.

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Figure 6.

In step 426, the corresponding action (s) for each optimization scenario to be implemented can be remotely executed or approved for manual implementation using the client interface and / or the video interface that described with reference to Figure 6.

Referring now to Figure 5, a flow chart illustrates one embodiment of a method 500 for carrying out step 224 of Figure 2.

In step 502, all zones, wells, patterns / groups and / or fields to be optimized are selected from the selected scan efficiency status display using the client interface and / or the video interface that is described with reference. to Figure 6.

At step 504, a series of classified optimization scenarios and corresponding actions are displayed that derive from the integration disciplines of exploration, drilling, completion and production of the right moment (the desired future point in time - short, medium or long term) for enhanced proactive optimization (proactive plus) using the video interface described with reference to Figure 6 and techniques well

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known in the field while evaluating the appropriate action plan to develop a field. The series of ranked optimization scenarios and corresponding actions for proactive optimization plus are based on optimizing selected zones, wells, patterns, groups, and / or fields, which can be exported to a net present value calculator.

In step 506, one or more optimization scenarios can be selected and the corresponding action for optimizing the selected zones, wells, patterns / groups and / or fields is displayed using the client interface and / or the video interface that described with reference to Figure 6.

In step 510, a prediction date can be selected for each selected optimization scenario using the client interface and / or the video interface that is described with reference to Figure 6. The prediction date determines the period of time that each respective selected optimization scenario is run in a simulator.

In step 512, said one or more selected optimization scenarios, the effect of each corresponding action on the zones, wells, patterns / groups and / or

IMPI iiwrnvro Mexican fields selected on the prediction date »v an oían Has updated field development for the field with the respective net present value calculation and the projected production parameters are displayed using the video interface that is described with reference to the Figure 6. The display may include, for example, changes in sweep efficiency status indicators, different subsurface display parameters for selected zones, wells, patterns / groups, and / or fields, and different net present value derivatives for each scenario of selected optimization. Optimization scenarios could include actions such as long-term secondary and tertiary oil recovery exploration strategies, infill drilling, re-drilling of water injection positions, and other field development actions.

In step 514, method 500 determines whether optimization is desired based on the results of step 512. If optimization is desired, then method 500 proceeds to step 516. If optimization is not desired, then method 500 proceeds to step 518.

In step 516, the desired optimization scenario (s) can be selected from said one or more selected optimization scenarios for your

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implementation using the client interface and / or the video interface described with reference to Figure

6.

In step 518, the data underlying the results of step 512 is saved.

In step 520, the data underlying the results of step 512 selected in step 516 for implementation is saved.

In step 522, method 500 determines whether the user has action approval to unilaterally implement the desired optimization scenario (s). If the user does not have action approval, then method 500 proceeds to step 524. If the user has action approval, then method 500 proceeds to step 526.

In step 524, a request for implementation of the desired optimization scenario (s) can be generated and / or submitted with a business case report, recommendation and analysis using the client interface and / or the user interface. video described with reference to Figure 6.

In step 526, the corresponding action (s) for each optimization scenario to be implemented can be remotely executed or approved for manual implementation using the client interface and / or

INSTITUTO MEXICANO DE ΙΛ WIIMD INDUSTRIAL the video interface described with reference to Figure 6.

System Description

The present invention may be implemented by means of a computer-executable instruction program, such as program templates, generally referred to as software applications or computer-executed application programs. The software may include, for example, routines, programs, objects, components, and data structures that carry out particular tasks or implement particular abstract data types. The software forms the interface to allow a computer to react according to an input source. DecisionSpace ™, which is a commercial software application available from Landmark Graphics Corporation, can be used as an interface application to implement the present invention. The software can also cooperate with other code segments to initiate a variety of tasks in response to the received data in conjunction with the source of the received data. Other code segments may provide optimization components including, but not limited to, neural networks, ground modeling, historical tuning, optimization, visualization, data management, il— ι · maix *

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INDUSTRIAL - deposit simulation and economy. The software can, be stored and / or carried in any variety of memory such as CD-ROM, magnetic disk, bubble memory, and semiconductor memory (eg, different types of RAM or ROM). Furthermore, the software and its results can be transmitted over a variety of carrier media such as fiber optics, metallic wire, and / or over any of a variety of networks, such as the Internet.

On the other hand, those of skill in the art will appreciate that the invention can be practiced with a variety of computer system configurations, including handheld devices, multiprocessor systems, consumer-programmable or microprocessor-based electronics, minicomputers, mainframe computers. , and the like. Any number of computer systems and computer networks are acceptable for use with the present invention. The invention can be practiced in distributed computing environments where tasks are carried out by remote processing devices that are linked through a communication network. In a distributed computing environment, the program modules can be located on local and remote computer storage media including memory storage devices. The present invention can be

IMPI • Wnvro M £ X_ICano therefore implementing hardware, software, or a combination thereof, in conjunction with a computer system or other processing system.

Referring to Figure 6, a block diagram illustrates one embodiment of a system for implementing the present invention in a computer. The system includes a computing unit, sometimes referred to as a computing system, which contains memory, application programs, a client interface, a video interface, and a processing unit. The computing unit is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the invention.

Memory primarily stores application programs, which can also be described as program modules containing computer-executable instructions, executed by the computing unit to implement the present invention described herein and illustrated in Figure 2. The memory therefore includes a subsurface oil recovery optimization module, which enables the methods illustrated and described with reference to Figure 2 and integrates functionality from the remaining application programs illustrated in Figure 6. . The kind of

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Subsurface oil recovery optimization, for example, can be used, unlike current art, to perform many of the functions that are described with reference to steps 201, 202, 204, 206 (regarding display), 208, 210, 212, 214, 218, 222, 302, 304 (regarding display and classification), 306 (user selection), 308 (regarding selection), 310, 312 (in terms of display), 314, 316, 318, 320, 322, 324, 326, 402, 404 (regarding display and classification), 406 (user selection), 408 (regarding selection), 410, 412 (regarding display), 414, 416, 418, 420, 422, 424, 426, 502, 5 04 (regarding display and classification), 506 (user selection), 508 (regarding selection), 510, 512 (regarding display), and 514, 516, 518, 520, 522, 524, 526 in the Figures 2, 3, 4 and 5. The memory also includes DecisionSpace ™, which can be used, for example, as an interface application to perform the functions described with reference to steps 206 (for predicted sweep efficiency status), 304 (for predicted sweep efficiency status). calculation of classified scenarios), 306 (suggested actions), 308 (in terms of effects), 312 (in terms of predicted changes in the sweep efficiency status indicators), 404 (regarding the calculation of classified scenarios), 406 (suggested actions), 408 (regarding the

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9 M UICAN INSTITUTE ^or Say L * PRCHSWAD

INDUSTRIAL effects), 412 (in terms of predicted changes in the sweep efficiency status indicators), 504 (in terms of calculating classified scenarios), 506 (suggested actions), 508 (in terms of effects), and 512 (regarding the predicted changes in the sweep efficiency status indicators) in Figures 2, 3, 4 and 5. Although DecisionSpace ™ can be used as an interface application, other interface applications can be used, instead of, or the subsurface oil recovery optimization module can be used as a standalone application.

Although the computing unit is shown as having generalized memory, the computing unit typically includes a variety of computer-readable media. By way of example, and not limitation, computer-readable media may comprise computer storage media and communication media. The memory of the computer system may include computer storage media in the form of volatile and / or non-volatile memory such as Read Only Memory (ROM) and Random Access Memory (RAM). A Basic Input / Output System (BIOS), which contains the basic routines that help to

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transfer information between elements within the unit of ⁴⁰ IMPIOS Mexican institute,, Γ4 LA FROrtEDAD g— UW computation, such as during boot, typioam ^ n ^ e ^ is stored in ROM. RAM typically cuirtrl ^ liy tlatü'S '-' and / 'Cr program modules that are immediately accessible and / or currently being operated by the processing unit. By way of example, and not limitation, the computing unit includes an operating system, application programs, other program modules, and program data.

Components displayed in memory can also be included on other removable / non-removable, volatile / non-volatile computer storage media or can be implemented in the computing unit through an application program interface (API, Application Program Interface) or cloud computing, which may reside on a separate computing unit connected through a computer system or network. For example only, a hard disk drive can read from or write to non-removable, non-volatile magnetic media, a magnetic disk drive can read from or write to a removable, non-volatile magnetic disk, and an optical disk drive can read of or write to a removable, non-volatile optical disc such as a CD-ROM or other optical media. Other removable / non-removable, volatile / non-volatile computer storage media that can be used in the exemplary operating environment may include, but are not limited to ₄₁ IMPIAS ^H MEXICAN INSTITUTE

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INDUSTRIAL XgTW a, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like. The drives and their associated computer storage media discussed above provide storage of computer-readable instructions, data structures, program modules, and other data for the computing unit.

A customer can enter commands and information into the computing unit through the customer interface, which can be input devices such as a keyboard and pointing device, commonly referred to as a mouse, trackball, or touch sensor. The input devices can include a microphone, joystick, satellite dish, scanner, voice recognition or gesture recognition, or the like. These and other input devices are often connected to the processing unit through a common system link, but can be connected by other interface and common link structures, such as a parallel port or a universal serial bus (USB , Universal Serial Bus).

A monitor or other type of display device can be connected to the system bus via an interface, such as a video interface. I also know⁴² ffiJTITlITO MEXICANO can use a graphical user interfaceWSTmxi

Graphical User Interface) with the interface¹ -'tfe¹VítíW -¹ country? a - receive instructions from the client interface and transmit instructions to the processing unit. In addition to the monitor, computers can also include other peripheral output devices such as speakers and a printer, which can be connected via a peripheral output interface.

Although not many other internal components of the computing unit are shown, those skilled in the art will appreciate that such components and their interconnection are well known.

While the present invention has been described in relation to presently preferred embodiments, it will be understood by those skilled in the art that it is not intended to limit the invention to those embodiments. It is, therefore, contemplated that different alternative embodiments and modifications can be made to the disclosed embodiments without departing from the spirit and scope of the invention as defined by the appended and equivalent claims therein.

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NOVELTY OF THE INVENTION we®^to_TOl

Having described the present invention, Comer ^ twtewe «« leT - eA considers it as a novelty and, therefore, the content of the following is claimed as property: