Identification of prevailing orientations of cracks

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority benefit of provisional application №61 / 710,582 US patent called "Identifying dominant fracture orientations", filed October 5, 2012 and the application №13 / 896,792 patent US utility called "Identifying dominant fracture orientations" filed May 17, 2013.

BACKGROUND

[0002] This description relates to the identification of the dominant fracture orientation based on the microseismic data. Microseismic data are often recorded in connection with fracturing operations, performed concerning the subterranean formation. fracturing operation is usually performed to create artificial cracks within the subterranean formation, and thus to increase the productivity of the underground hydrocarbon reservoir. Pressures created in step fracturing, may induce low amplitude and low-energy seismic events in the subterranean formation, and the events can be detected by sensors and collected for analysis.

SHORT DESCRIPTION

[0003] According to a general aspect of the predominant orientation of fractures in a subterranean zone is identified based on the microseismic data.

[0004] In some aspects, the main orientation plane is determined for each of the plurality of basic faces. Main plane defined coplanar subsets or are in coplanar subsets data microseismic events (e.g., three or more of microseismic events) collected in step fracturing the subterranean zone (for example, collected before, during or after fracturing operations) . Calculate the quantity of the basic orientation of the planes in each of a plurality of orientations ranges (for example, directions). Identifying the predominant orientation of the crack to the subterranean zone based on the identified one or more quantitative parameters.

[0005] Embodiments may include one or more of the following features. The histogram (eg, based on the Hough transform, or other calculations) is calculated and displayed; Histogram shows the quantity of the basic orientations of the planes in each of the ranges of directions. Identified quantitative parameter orientations basic planes can be a probability value, the statistical value, frequency value, a numeric value or the value of another type.

[0006] Additionally or alternatively, these and other implementations may include one or more of the following features. Each base plane orientation includes angle and strike angle for one of the main planes. A plurality of orientations ranges identified on the basis of basic orientations of planes. Many bands orientations identified by the sort of angles stretch, identifying clusters of assorted corners of the strike, the sort of angles of incidence, identify clusters of assorted angles of incidence and determine the range of orientations on the basis of clusters of assorted corners and stretch clusters assorted angles of incidence.

[0007] Additionally or alternatively, these and other implementations may include one or more of the following features. Many bands orientations are fixed values ​​determined independently of the orientation of the main planes. Each coplanar subset of microseismic events were identified on the basis of data on microseismic events. Calculate the normal vector to the base plane defined by each coplanar subset. Main orientation plane is calculated based on the normal vectors.

[0008] Additionally or alternatively, these and other implementations may include one or more of the following features. Identification of the dominant fracture orientation includes identifying a plurality of orientations prevailing cracks. Identifying the predominant orientations of a plurality of cracks includes identifying a range of orientations having the largest numerical parameters cracking planes. Identify the cluster of microseismic events associated with each of the predominant orientation of cracks. Predominant fracture plane for each of the predominant orientation of the crack formed on the basis of selection (for example, the optimum or otherwise) microseismic events in the cluster. selection process can be based on the algorithms of the least distance, maximum likelihood algorithms or any other suitable means.

[0009] The details of one or more embodiments are reflected in the accompanying drawings and the description below. Other features, objects and advantages will become apparent from the description and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

In the drawings:

[0010] FIG. 1A - an example well system; FIG. 1B - computing a block diagram of an example subsystem 110 of FIG. 1A;

[0011] FIG. 2 - a graph illustrating an example of a histogram;

[0012] FIG. 3A and 3B - diagrams illustrating an example of the orientation of a crack plane; and

[0013] FIG. 4 - block diagram of an example method of identifying the sequence of actions predominant orientations of cracks.

[0014] In the various drawings, like numerals refer to like elements.

DETAILED DESCRIPTION

[0015] The following US patent application included in the present disclosure by reference: (1) pre-application №61 / 710,582 US patent called "Identifying dominant fracture orientations", filed October 5, 2012; (2) application for US №13 / 896,400 patent application, entitled "Geometrical presentation of fracture planes", filed May 17, 2013; (3) the application №13 / 896,389 US patent entitled "Analyzing microseismic data from a fracture treatment", filed May 17, 2013; (4) the application №13 / 861,986 US patent called "Identifying orientation clusters from microseismic data", filed on April 12, 2013; (5) the application №13 / 896,394 US patent entitled "Determining a confidence value for a fracture plane", filed May 17, 2013; (6) the application №13 / 896,406 US patent entitled "Managing microseismic data for fracturing matching", filed May 17, 2013; (7) the application №13 / 792,772 US patent entitled "Updating microseismic histogram data", filed on March 11, 2013; (8) the application №13 / 896,425 US patent entitled "Propagating fracture plane updates", filed May 17, 2013; (9) the application №13 / 896,617 US patent called "Identifying fracture planes from microseismic data", filed May 17, 2013.

[0016] According to some aspects of which are described in this application, the parameters of fracture dominant fracture orientation or other data identified on the basis of MS data. In some cases, individual data of these and other types of dynamically identify, for example, in real time during the operation fracturing or hydraulic fracturing operation. In many applications, and methods of analysis require identification in real time based on the fracture planes of microseismic events, and the individual plane cracks can be displayed to show the time evolution of the geometric and reduction, including the location, distribution, growth, reduction or disappearance of cracking planes. Such functionality can be incorporated into the control system, software, technical support or other types of tools available to engineers or operators of oil and gas industry, where they analyze the potential oil and gas deposits, stimulate hydraulic fracture and analyze the resulting signals. These tools can be provided by a reliable and immediate interface for presentation and visualization of dynamic characteristics of hydraulic fracturing cracks, which may facilitate the analysis of the complexity of the cracks, cracks grid structure, movement of rock blocks and manifold geometry. Such tools can facilitate estimation of efficiency fracturing operations, increasing, for example, as a result of improvements, improving or optimizing the crack density and length and height of the trajectory. Such improvements in the performance of hydraulic fracturing operations, applied to the collector, can lead to increased production of hydrocarbons or other resources or products from a reservoir.

[0017] fracturing operations can be applied in any suitable subterranean zone. fracturing operation is often used for thick layers of low permeability reservoirs which may include a conventional oil and gas reservoirs of low permeability zones of continuous resource basin and shale gas reservoirs or other types of layers. Fracturing can create artificial cracks in the earth that can increase the production of hydrocarbons from the reservoir.

[0018] During the use of hydraulic fracturing operations as a result of the injection of fluids under high pressure can change the voltage, increase of voltage, voltage orientation accumulate shear stress and other effects occur in underground geological structures. In some individual cases, microseismic events associated with hydraulic fractures created by the performance of work on hydraulic fracturing. Acoustic energy or sounds associated with the stresses in the rock, fracturing or deformation can be detected and collected by the sensors. In some individual cases, microseismic events have a relatively low energy (for example, on the log value of the intensity or magnitude of the moment less than three), and some uncertainty, or inaccuracy, or measurement error associated with locations of events. The uncertainty can be described, for example, prolate spheroid, and the maximum likelihood corresponds to the center of the spheroid and the minimum corresponds to the edge of credibility. Furthermore, in some instances the time uncertainty (or intensity) of the signal uncertainty timestamp events or a combination of these uncertainties and other species may occur and can be described by the same or by other means.

[0019] Mapping microseismic events can be used to determine the geometric position of the source locations of microseismic events detected on the basis of longitudinal and transverse waves. You can obtain additional information about the microseismic events, including the location of the source space, event location and the uncertainty of measurement position, the time the event occurred, the magnitude of the moment of the event, the direction of motion of the particles From detected longitudinal and transverse waves (for example, p-waves and s-waves) and the energy spectrum of the radiation, and possibly other parameters. Monitoring microseismic events can be performed in real time, and moreover, in some cases, individual events processed in real time during the fracturing operation. In some instances, after fracturing operation microseismic events resulting from the operation, are collected together and treated as "postdannye".

[0020] Processing of the microseismic event data collected when the fracturing operation may include mapping of cracks (cracks also called mapping). The matching process can identify cracks plane cracks in any zone on the basis of microseismic events collected from the zone. In some examples, numerical algorithms used for comparison of data on fracture microseismic event (e.g., event location, event location uncertainty of measurement, the time value of the event, etc.) for identifying individual cracks which correspond to the assembled set of microseismic events. Some examples of computer algorithms allow to calculate the statistical properties of the paintings cracks. The statistical properties may include, for example, crack orientation, crack trends orientations crack size (e.g., length, height, area, and cross-section, etc.), the density of cracks, the complexity of the fracture properties of the grid of cracks, etc. In some computational algorithms take into account the uncertainty of the event locations through the use of implementations locations of microseismic events. For example, the implementation of alternative statistics associated with Monte Carlo methods can be used for a given probability distribution with respect to the distribution of spheroid or distribution of other species.

[0021] Generally, mapping algorithms cracks may operate in real-time data, postdannym or any combination of these temporary data, and other species. Some computational algorithms cracks comparisons only work on postdannym. Algorithms running on postdannym can be used in the case where any subset of several subsets of processed microseismic data collected in step fracturing; such algorithms may apply (such as the original data) to a subset of the total cultivated microseismic events. In some embodiments, the fracture mapping algorithms can work on real-time data. Such algorithms can be used for automatic real-time comparison of cracks during fracturing operations. Algorithms running on the real-time data can be used during the fracturing operation, and such algorithms may be adapted or dynamically update the model for the previously identified reflection cracks newly registered microseismic events. For example, simultaneously with the detection and collection of processing microseismic events field fracturing automatic matching algorithm in real time cracks may respond to these new events by identifying and producing dynamic fracture planes in real time from microseismic events already collected. Some cracks comparing computational algorithms may work postdannyh and combination of data in real time.

[0022] In some cases, when a new microseismic event is added to the existing set N of events which have been collected in real time, N + 1 may be considered as an event postdannye and processing, for example, using an algorithm that can operate on postdannym. In some circumstances there is enough time to perform a full real-time as an algorithm running on postdannym. In some embodiments, the data of new events can be processed adequately based on, for example, the nature of real-time events, their separation in time, the geometrical locations of accumulated events that have not been completely processed, or a combination of these and other criteria.

[0023] In some cases, the mapping algorithm is adapted to work in conditions which occur when processing microseismic data in real time. For example, the problems or situations several types may occur mainly in the context of real time. In some individual cases, the methods in the real time processing can be adapted to accommodate (or to reduce or eliminate) the poor precision which is sometimes associated with cracks secreted from the data sets that do not contain a sufficient number of microseismic events or not containing a sufficient number of microseismic events in certain parts region. Some methods in realtime processing can be adapted for the formation of cracks in the data are consistent with data on fractures obtained based on postdannyh processing methods. For example, when processing the same data several ways of processing in real time, as described in this application, results are obtained which statistically is the same as the corresponding statistical criterion testing the hypothesis (statistical T-criterion and F-criterion), the results obtained postdannyh processing means .

[0024] adapt (e.g., from a user perspective instantly) for presenting data to users of the identified cracks in some cases, the methods in the real-time processing is possible without difficulty. Such features may allow fishing engineers or operators to dynamically obtain information about the geometry of cracks and adjust operation parameters for hydraulic fracturing, if necessary (for example, to improve, improve, optimize or change operation). In some individual cases, crack plane dynamically obtained from microseismic data and display in real time for a field engineer. Methods for real-time processing may have a characteristic that ensures a high speed of operation. In some cases, the characteristics can be improved by using parallel computing technology, distributed computing, parallel threading methods, fast binary search algorithms, or combinations of them, as well as other hardware and software solutions that facilitate the execution of operations in real time.

[0025] In some embodiments, the mapping technique may crack directly submitted information about fracture planes associated with three-dimensional microseismic events. The submitted cracks planes can be displayed grid of cracks that have multiple orientation and form a complex pattern of cracks. In some cases, the parameters fracturing cracks produced from the cloud data microseismic events; such parameters may include, for example, fracture orientations trends, fracture density and complexity of cracks. Information about cracking parameter may be a field engineer or operator, for example, on a table, numerical or graphical user interface, or UI, which combines table, numeric and graphic elements. The GUI can be presented in real time and can display real-time dynamic characteristics fracturing cracks. In some individual cases, it can help reservoir engineers to perform analysis of the complexity of the cracks, cracks and collector grid geometry or can help them better understand the process flow of hydraulic fracturing.

[0026] In some embodiments, accurate reliability values ​​are used for the quantitative evaluation of reliability indicators of cracks planes received from microseismic data. The exact values ​​of authenticity may be used for the classification of cracks on the levels of confidence. For example, three levels of reliability (low confidence level, average level of reliability and a high confidence level) suitable for some situations, while the other number may be suitable for different situations (e.g., two, four, five, etc.). The exact value of the crack plane of reliability can be calculated on the basis of all relevant data. In some embodiments, the exact value of the reliability of the plane of the crack is calculated based on the locations of microseismic events and uncertainties provisions, values ​​of moments of individual microseismic events, the distances between the individual events and the reference plane cracks, the number of reference events associated with the crack plane, and the weight variation of crack orientation, along with some others.

[0027] The exact values ​​can be calculated reliability and crack plane can be classified in any suitable time. In some cases, the exact values ​​of the reliability calculated and classify cracks plane in real time during the fracturing operation. Fracture plane can be presented to the user at any suitable time and in any suitable format. In some instances cracks are plane in real time on the graphical user interface in accordance with the exact values ​​of reliability, according to the precise levels of accuracy or according to any other type of classification. In some instances, users can select individual groups or individual plane (for example, with high levels of confidence) for monitoring or analysis. The planes of the cracks can be presented to the user in an algebraic format, numeric, graphical format or a format that is a combination of these or other formats.

[0028] In some embodiments, monitoring microseismic events is performed in real time during the fracturing operation. In addition, the monitoring of events can be processed in real time, they can be later processed as postdannyh or can be processed using the combined processing of data in real time and postdannyh. Events can be processed in any suitable manner. In some cases, the event is treated individually at the time at which they are received, and the order in which they are received. For example, state S (M, N-1) of the system can be used to represent the M planes formed at the preceding N-1 events. New N-th occurring event may trigger S (M, N-1) system. In some cases, when receiving the N-th event histogram or distribution of orientations of the ranges or update form. For example, a histogram of probability distribution or histogram Hough transform degenerate planes in the angular stretch or fall can be formed to identify the possible dominant orientations included in the sets of cracks.

[0029] The main plane can be formed on the basis of a subset of microseismic events. For example, any three non-collinear points in space can uniquely define base plane. Main plane defined by three non-collinear microseismic events can be represented by the vector normal to the plane of the components (a, b, c). The normal vector (a, b, c) can be calculated on the basis of the spatial position of the three events. The orientation of the main plane can be calculated based on the normal vector. For example, the fall of θ and φ strike may take the form

<img file="00000001.tif" he="13" wi="115" img-format="tif" img-content="undefined" />

The angle of incidence θ can be represented by a crack plane of the angle between the fracture plane and the horizontal plane (e.g., plane xy). Angle φ stretch crack plane can be represented by the angle between a horizontal reference axis (e.g., axis x) and the horizontal line at which the crack plane intersects the horizontal plane. For example, the angle of the strike can be set with respect to the North or the other of the horizontal reference direction. crack plane can define other parameters, including other angular parameters, rather than the strike angle and the angle of incidence.

[0030] In general, N can maintain events P = N (N-1) (N-2) / 6 major planes defined strike and dip angles. The histogram probability can be constructed on the basis of orientation angles. The histogram probability or histogram improved Hough transform may have a suitable configuration based on the size of the column histogram. For example, the configuration of the histogram, a fixed set of variables and static size columns may be based on a fixed size and fixed number of columns columns, natural optimum amount of stretch in the columns and the angles of incidence histogram bars or other species. The histogram may be based on any suitable number of microseismic events (e.g., tens, hundreds, thousands, etc.) or any suitable range of orientations. In some cases, multiple discrete histogram determined for poles, and each column represents a discrete range orientations. Quantitative parameters of the main planes of each discrete range can be calculated on the basis of the main planes. In some cases, each main orientation plane falls in a range of orientations associated with one of the columns. For example, in the case of N microseismic events each of the main planes P can be attributed to the column of the histogram, and can calculate the quantity of the basic planes assigned to each column. Computed quantitative parameter for each column can be any suitable value. For example, the quantitative parameter can be unnormalized number of main planes, a quantitative parameter can be normalized probability, frequency, or part of the main planes, or quantitative parameter may be a value other form which is suitable for the histogram. The histogram can be formed to represent the main quantitative parameter planes assigned to all the posts or to represent the quantitative parameters of the main planes assigned to a subset of the columns.

[0031] In some embodiments, the histogram is represented as a three-dimensional bar chart, the three-dimensional surface of the card or other suitable graphics in an appropriate coordinate system. The peaks on the graph bar graph can show the dominant fracture orientation. For example, one axis can represent histogram stretch angles from 0 ° to 360 ° (or other range) and strike angles can be subdivided into any suitable number of columns; on the other axis of the histogram can represent angles of incidence from 60 ° to 90 ° (or at another range) and the angles of incidence can be subdivided into any suitable number of columns, which may be the same or different sizes. Quantitative parameters (eg, probability) for each column can be submitted by the third axis of the histogram. The resulting graph can have local maxima (peaks). Each local maximum (peak) can show the corresponding angle of the strike and the angle of incidence, which represent the predominant orientation of the crack. For example, the local maximum of the histogram might show that a greater number of planes aligned along the main direction of orientation (orientation or range) than in the direction of neighboring orientations, and these basic plane almost parallel or substantially on the same level.

[0032] The range of orientations, each bar of the histogram display can be determined by any appropriate means. In some cases, each column represents a predetermined range of orientations. For example, a method for non-uniformly distributed bars of fixed sizes. In some cases, the size of each band or column depends on the data provided by the histogram. For example, you can use a natural way to optimal size of the columns. For example, a method for adaptive columns sizes. In some instances the orientation of the main planes are sorted, and sorted the clusters identified orientations. For example, all the stretch can be sorted in order of decreasing or increasing and then grouped into clusters; similarly, all falling values ​​can be sorted in order of decreasing or increasing and then grouped into clusters. Clusters can be linked to a two-dimensional grid, and you can count the number of the main planes in each grid cell. In some cases, this method can dynamically adaptive clustering to form, resulting in a highly accurate values ​​for the prevailing orientation. This method and associated drill them can be implemented in the computational complexity N³log (N) and in the ordinary computer memory complexity. In some cases, the size of the columns for the strike and dip are fixed and each cell of the grid placing the main plane can be accurately determined with the appropriate stretch and fall when the computational complexity of N³.

[0033] The planes of fracture associated with a set of microseismic events can be obtained based on the predominant orientations included in the histogram data. Main plane which is supported to the predominant orientation (θ, φ), may be parallel or almost on the same level. Main plane located at the same level, can be combined with each other to form a new plane cracks stronger support (e.g., representing a greater number of microseismic events). Any suitable method can be used to combine the planes of cracks. In some cases, for each dominant orientation (θ, φ) form the normal to the plane of the vectors with components (sin θ cos φ, sin θ sin φ, cos θ). In some instances the results are not sensitive to the location of a plane and a plane without loss of generality it can be taken into account through its normal vector (for example, assuming that the origin lies in the plane). The plane can be described as x sin θ cos φ + y sin θ sin φ + z cosθ = 0. Distance (with sign) of each event (x₀, y₀, z₀) From the base line to the formed plane it can be represented as d = - (x₀ sin θ cos φ + y₀ sin θ sin φ + x₀ cos θ). In this representation, events with opposite signs d situated on opposite sides of the plane.

[0034] In some cases, microseismic events are grouped into clusters based on their distance from the plane formed by cracking. For example, a cluster of events may include events group closest to the plane of the crack formed. By itself, each microseismic events cluster can support concrete crack plane. Cluster size is correlated with the number of events that comprise the cluster. In some cases, the data entered by the user or other program data can specify the minimum number of events supported in the cluster. The minimum cluster size may depend on the number of microseismic events in the data. In some instances minimum cluster size must be greater than or equal to three to three. For example, clusters having a size exceeding the minimum cluster size, or equal to it, can be considered legitimate planes cracks. fitting algorithm can be applied to determine the position and uncertainty of the location of events in each cluster to find the respective planes of cracks. In some embodiments, the process for creating the cluster, you can use an adaptive method. In some cases (optimal) set of clusters can be obtained by uneven grouping in each of two directions (for example, at the corners of the strike and dip) main orientation plane.

[0035] Any suitable method can be used to identify the plane of the crack on the basis of a set of microseismic events. In some cases, the selection method used chi-square test. Given K observed microseismic event locations can be represented as (x_i, y_i, z_i), And the uncertainty of measurement may be represented as (σ_ix, σ_iy, σ_iz) Where 1≤i≤K. The model parameters z = ax + by + c plane can be calculated, for example, by minimizing the evaluation function chi-square

<img file="00000002.tif" he="12" wi="108" img-format="tif" img-content="undefined" />

Evaluation function chi-square test can be solved by any suitable means. In some individual cases, the decision may be obtained by finding solutions to the three partial differential equations χ²(A, b, c) with respect to variables, where each partial derivative to zero lead. In some individual cases, there is no analytical solution for these non-linear equations. Numerical methods (for example, Newton's method, the Newton-Raphson method, CG method, or other method) can be used to find a solution for the parameters a, b and c, and the angles strike and dip can be calculated (for example, using the equation (1) above). The predominant orientation of the crack plane, calculated on the basis of microseismic events can be the same as the predominant orientation of the cracks identified in the histogram, or may differ from it. Additional or other method can be used to find solutions for the coefficients of the plane, for example, by minimizing the maximum absolute value of the i-th contribution<img file="00000003.tif" he="13" wi="46" img-format="tif" img-content="undefined" /> or any other suitable metric.

[0036] In some embodiments, using the algorithm iterate against all possible orientations of the prevailing spread for all possible plane cracks. In some cases, using the algorithm iterate on the selected subset of possible orientations prevailing. When the plane iterations may converge. Some planes are exactly the same as each other, and some may be close to each other. For example, the two planes can be considered close to each other when the average distance from one plane another plane is less than a predetermined threshold. The threshold distance may be set, for example, as a control parameter. The threshold distance may be set, for example, adaptively during the iteration process. With the help of the algorithm can be combined with each other and close to the plane of the supporting events one plane can be associated with other supporting events, obtained by combining the plane (planes). By combining algorithm can detect certain events that were associated with the two planes being combined, not associated with the plane of the resulting combination. For example, with respect to the real-time situation in certain relative amounts of new unrelated events unification process can be carried forward to the subsequent stages of the algorithm or at a later time.

[0037] In some cases, limitations imposed on the crack plane identified based on the microseismic data. For example, in some cases the residual events distances should be less than the predetermined allowable distance. The allowable distance may be set, for example, as a control parameter. In some individual cases, identified the plane cracks must be properly calculate, to designate (maximum specified) the final size of the cracks. Border truncated planes can be calculated based on the position of supporting events and event locations of measurement uncertainty. New course-dimensional plane of the cracks can be combined with the already identified planes cracks subject to final size conditions.

[0038] In some individual cases, the new N-th microseismic events associated with the planes of the fractures have been identified on the basis of the previous N-1 microseismic events. When you link a new event with the existing crack the algorithm can be used to upgrade an existing fracture. For example, the update may change the crack geometry, location, orientation, crack or other parameters. When you select one of the previously identified planes cracks can calculate the distance from the plane of the crack of a new event. If the distance is less than the reference distance parameter or equal to, the event may be added to the reference set of events to crack plane. If the distance is more than the reference parameter range, plane other previously identified cracks may be selected (e.g., iteratively or recursively) as long as the plane is not detected within the threshold distance. After a new event to be added to the fracture plane of the reference set can be estimated, and if necessary, recalculate new values ​​stretch and falling (for example, using the chi-square method or another selection of a random or deterministic method) of the crack plane. A re-calculation of fracture parameters leads to a limited change in the orientation due to the conditional distance control.

[0039] In some cases, when a new event associated with microseismic fracture plane, one or more parameters (e.g., the residual of the distance, area, etc.) can be modified or optimized. The residual distance r plane may represent the average distance from the reference plane to the event. If the discrepancy is less than a predetermined distance T residual tolerance, a new event can be identified in relation to it a set of events for the plane. In some cases, an additional process with which other events associated set of reference chosen from the list, begin and end when the residual distance r falls within a predetermined T. In some instances the selected event necessary to its connection to another plane cracks (e.g. with neighboring plane). If the selected events are not suitable plane, this event can be sent to unbound cart (such as when a new incoming event may not be associated with any of the existing planes). If the selected event are suitable plane, the selected event can be regarded as a new event for this plane. The above algorithm can be repeated and complete, such as when a new level of confidence in the (new event caused) slightly varies relative to the preceding level of confidence (e.g., a change is within the thresholds) or pursuant to any other suitable criterion for completion. The area of the crack plane can display the size of the crack plane. The experiment shows that the new event usually leads to crack propagation along the length of the plane, growth in height or both. Therefore, the computational processes can be restricted s condition nondecreasing area, resulting in a new plane area should grow to a larger value than the initial plane area (as opposed to reduction) or remain the same when a new event is added to a plane.

[0040] The orientation of the fracture plane can be expressed depending on the angle, or any of its trigonometric functions. In some instances crack plane orientation can include two independent components, each corner crack can display plane. For example, normal vector angles of the strike and dip, or other suitable parameters can be used to display the orientation of the crack plane. Changing the orientation of the plane of the crack (or fracture plane other changes) may result in displacement of some related reference events from a list in the list of related events unrelated events based on their distances from the plane of the crack updated. Additionally or alternatively the crack plane orientation change can lead to assigning certain events previously unconnected to the plane of a crack on the basis of their proximity to the updated crack plane. In addition, some of the events associated with similar planes may also be associated with the current plane. If a new event associated with the two planes of cracks, fissures plane may intersect. In some cases, the intersecting planes can be combined. If the new event is not belong to any existing crack plane, it can be defined in the list of unrelated events.

[0041] At any point N accumulated microseismic events can be considered a subset of the set of finite postdannyh of events. In such cases, the orientation distribution or histogram based on the first N events may differ from the histogram or distribution of orientations formed based on the final postdannyh. Some plane cracks produced on the basis of N microseismic events that may not be accurate, and this uncertainty may diminish as time increments or the accumulation of more events. For example, the accuracy and reliability may be lower than the initial time when the detectable plane cracks associated with microseismic events that are close to the wellbore. Such data may indicate a fracture plane, which are arranged nearly parallel to the borehole, even if these are not the real plane cracks.

[0042] The exact accuracy of the crack can be used as a measure of certainty associated with the fracture plane, identifiable on the basis of microseismic data. In some cases, the accuracy of identifying the exact real time during the fracturing operation. Precise accuracy can be determined based on any suitable data using any suitable calculation. In some cases, the exact plane of the crack affects the reliability of the value of the number of microseismic events related to the crack plane. For example, the current reliability value can be scaled (e.g. linear, linear, exponential, polynomial, etc.) relative to the number of microseismic events in accordance with the function. A number of microseismic events related to the crack plane, it is possible to include (such as weight, exponent, etc.) into the equation to calculate the exact certainty. In some individual cases, the crack plane is of higher reliability, when the crack plane is supported by a large number of microseismic data points (or low confidence value when the crack plane is supported by a smaller number of microseismic data points).

[0043] In some cases, the exact plane of the crack affects the reliability of the value of the uncertainty of microseismic event locations associated with the crack plane. For example, the current reliability value can be scaled (eg, linear, nonlinear, exponential, polynomial, etc.) with respect to the uncertainty of location of microseismic events in accordance with the function. The uncertainty of the location of microseismic events can be included (eg, the weight, the exhibitor or any decaying function of distance, etc.) into the equation to calculate the exact certainty. In some individual cases, the crack plane is of higher reliability, when the crack plane supports the microseismic data have low uncertainty (or low confidence value when the crack plane supports the microseismic data have increased the uncertainty).

[0044] In some cases, the exact plane of the crack affects the reliability of the value of the time value of microseismic events related to the crack plane. For example, the current reliability value can be scaled (e.g. linear, linear, exponential, polynomial, etc.) relative to the time value of microseismic events according to the function. The magnitude of the moment of microseismic events can be included (such as weight, exponent, etc.) into the equation to calculate the exact certainty. The magnitude of the moment of microseismic events may represent the energy and intensity (sometimes proportional to the square of the amplitude) of the event. For example, the time value of microseismic events may be the energy value or the intensity on a logarithmic scale or other type value representing the energy intensity. In some individual cases, the crack plane is of higher reliability, when the crack plane supports the microseismic data have increased the intensity (or low confidence value when the crack plane supports the microseismic data having a lower intensity).

[0045] In some cases, the exact plane of the crack affects the reliability of the value of the distance between the crack plane and microseismic events related to the crack plane. For example, the exact value of the reliability can be scaled (eg, linear, nonlinear, exponential, polynomial, etc.) relative to the average distance between the crack plane and microseismic events that support the crack plane. The average distance can be included (such as weight, exponent, etc.) into the equation to calculate the exact certainty. In some individual cases, the crack plane is of higher reliability, when the crack plane supports the microseismic data, which on average are closer to the plane of the crack (or low confidence value when the crack plane supports the microseismic data, which on average are further from the plane of the crack) .

[0046] In some cases, the exact plane of the crack affects the reliability of the value orientation of the plane of the fracture with respect to the trend prevailing orientation in the set of microseismic data. For example, the exact value of the reliability can be scaled (eg, linear, nonlinear, exponential, polynomial, etc.) relative to the angular difference between the plane orientation of the cracks and the prevailing trend in the orientation of microseismic data. orientation angles may include stretch, or drop any combination of a relevant (for example, the solid angle in three dimensions). The orientation can be included (such as weight, exponent, etc.) into the equation to calculate the exact certainty. Microseismic data set may have one orientation prevailing trend or it may have multiple orientation prevailing trends. Trends predominant orientation can be divided, for example, primary, secondary, etc. In some individual cases, the crack plane has increased the reliability of the value when the crack plane is consistent with the trend prevailing orientation in the set of microseismic data (or low confidence value when the crack plane deviates from the trend prevailing orientation in the set of microseismic data).

[0047] The weight value, called "weight variation orientation cracks" can be a difference between the angular orientation of the fracture plane orientation and the prevailing trend in the microseismic data. Weight variation of crack orientation can be a scalar value, which is maximal when the crack plane is consistent with the trend prevailing orientation. Weight variation of the crack can be minimum orientation orientations at cracks which are spaced from the maximum fracture orientation prevailing trend. For example, when there is a single dominant trend fracture orientation, crack orientation weight variation can be zero for cracks that are perpendicular (or normal) to the dominant fracture orientation. According to another example, when there are numerous trends dominant fracture orientation, the weight variation of the crack orientation may be zero to cracks having a prevailing orientation between the orientations of cracks. Weight variation crack orientation ratio can be calculated by the orientation of the plane orientation and reported under homogeneous case.

[0048] In some cases, where there are numerous trends dominant fracture orientation, crack orientation weight variation has the same maximum value for each trend dominant fracture orientation. In some cases where there are multiple dominant fracture orientation, the weight variation of the crack is oriented more local maximum value for each dominant fracture orientation. For example, the weight variation of the crack orientation may be 1.0 to cracks which are parallel to the first orientation of the predominant trend cracks cracks to 0.8, which are parallel to the second orientation prevailing trend of cracks and fissures to 0.7, which are parallel to the third fracture orientation prevailing trend . Weight variation of the orientation of the crack can be reduced to local minima between the trends prevailing orientations of cracks. For example, the weight variation of the orientation of cracks between each adjacent pair of the prevailing orientation of cracks may determine the local minimum halfway between the dominant fracture orientation, or at another point between the dominant fracture orientation.

[0049] In the detailed reliability parameter may affect the uncertainty of the location of the reference microseismic event, the value of the time reference microseismic event, the distance between the support microseismic events and crack plane, the number of reference events associated with the plane, the weight variation of crack orientation, other values ​​or any suitable combination of one or more of these. Some general patterns accuracy increases with increasing magnitude of the time, and variation with increasing orientation, and with increasing the number of reference events and improve the accuracy of their location, and with an increase in the weight variation as a function of distance. These factors can be used as input data by setting the weight in the equation for accurate reliability. For example, in some models weight are linear or non-linear functions of these factors, and the weight variation of the crack orientation may be more weight affects the accuracy of the plane. In some instances, the precise accuracy of the computed as:

Reliability = (weight variation of crack orientation)  *

<img file="00000004.tif" he="9" wi="36" img-format="tif" img-content="undefined" /> ((Weight of location uncertainty) *

(Weight values ​​torque) * (the weight variation range)). <img file="00000005.tif" he="1" wi="3" img-format="tif" img-content="undefined" />(3)

To calculate the reliability can use other equations or algorithms.

[0050] The identified plane cracks can be divided into levels of reliability on the basis of exact values ​​of reliability crack planes. In some individual cases, use three levels: low confidence level, the average level of reliability and a high level of reliability. One can use any suitable number of levels of reliability. In some instances when you add a new event to the reference set associated with an existing fracture plane corresponding to crack reliability parameter may be increased, which may cause increased level of reliability of the current value to a value greater than one, if the value is there. In another example, in case of deviation fracture orientation of the orientation trends present in postdannyh of microseismic events, the gradual accumulation of microseismic events may be generated decrease crack reliability, mainly according to the weight variation of the crack orientation, and therefore the level of the plane of reliability decreases to low, if any. This especially applies to fractures formed at the initial time fracturing operation; it is also applicable to other types of cracks in other situations.

[0051] The users (for example, a field engineer, service engineer, interpreters and others) may be provided graphics planes fractures identified on the basis of microseismic data. In some cases, a graphical representation allows the user to visualize the identified plane with a representation of graphic panels confidence levels in real time. For example, three image panels can be used to represent planes individually cracks with low reliability, the reliability of the average level and a high level of reliability. In some cases, cracks low reliability planes are created in the initial moments of time fracturing operation. In some cases, cracking plane with high reliability level over time extend in a direction almost perpendicular to the wellbore. As new microseismic events gradually accumulate over time, a graphic image can be updated, to allow the user to dynamically observe the connection planes of the cracks between the levels of reliability associated with graphic panels.

[0052] The confidence levels of the Group can be represented as graphs planes for cracks or group confidence levels can be presented in a different format. confidence levels can be represented algebraically group, for example by algebraic display parameters (e.g., parameters, equations for the plane) planes of cracks in each group. confidence levels of the Group can be presented as a figure, for example, by displaying the numerical parameters (eg, strike, drop, square, etc.) planes of the cracks in each group. confidence levels of the Group can be presented in tabular form, for example, by displaying a table of parameters of algebraic or numerical parameters fracture planes in each group. Additionally, crack plane can be represented graphically in three-dimensional space or another space. For example, cracks can be represented in a plane rectilinear coordinate system (for example, coordinates x, y, z), in polar coordinates (e.g., r coordinates, θ, φ) or in a different coordinate system. In some examples, crack plane can be represented as a line at the intersection of the plane of the crack on the other plane (for example, a line in the xy plane, a line in the plane xz, yz plane in line or in any line or plane on the surface).

[0053] In some instances graphical representation allows users to track and visualize the spatial and temporal evolution of the specific plane fractures, including education, distribution, and growth. For example, the user can watch the stage of the spatial and temporal evolution of the specific fracture plane, such as, for example, the initial identification of crack plane based on three of microseismic events, the event that changes the plane orientation, the event that causes the plane area growth (e.g., vertical , horizontally or in both directions), or any other stage of evolution of the crack plane. Spatial and temporal evolution of the fracture plane may be the spread of fracturing fluid and proppant into the skeleton of the rock. Visualizing the dynamics of fracture planes can help users to better understand the process of hydraulic fracturing, more precisely to analyze the complexity of the cracks, to evaluate the effectiveness of hydraulic fracturing, or improve the well treatment.

[0054] Although the examples described herein, including data microseismic events, methods, and systems described herein may be applied to other types of data. For example, the methods and systems described herein may be used for processing the data sets, comprising data elements that are not associated with microseismic events, which may include other types of physical data relating to a subterranean zone. In some aspects herein proposed concept of processing large amounts of data, and the concept can be adapted for various applications that are not specifically described in this application. For example, the methods and systems described herein may be used for analyzing the spatial coordinate data of orientations, or other types of information collected from any source. For example, it is possible to collect samples of soil or rocks (for example, during drilling) and determine the concentration of the specified compound (e.g., certain salts) as a function of location. This can help geophysicists and operators to assess the geological layers in the rock.

[0055] FIG. 1A shows a schematic exemplary representation of a system of wells 100 with computer subsystem 110. An exemplary system 100 includes wells treated well and an observation well 102 104. The observation well 104 can be located remotely from the machined hole 102, hole 102 near the treated or at any suitable location. The well system 100 may include one or more additional treated wells, monitoring wells or other types of wells. Computing subsystem 110 may include one or more computing devices or systems located near a processing hole 102 near the observation well 104, or elsewhere. Computing subsystem 110 or any of its components may be positioned at a distance from the other components shown in FIG. 1A. For example, computing subsystem 110 may reside in a data center, in computing equipment or in another suitable location. The well system 100 may include additional or other elements, and the elements of a system of wells may be arranged as shown in FIG. 1A, or in any other suitable configuration.

[0056] The illustrated example 102 treated well is a borehole 101 in a subterranean zone 121 below the surface 106. The underground zone 121 may include one or part of the rock formation rock formation or subterranean zone 121 may include more than one rock formation. In the example shown in FIG. 1A, subterranean zone 121 comprises various underground layers 122. Ground layer 122 may be determined by the properties of geological or other subterranean zone 121. For example, each of the ground layers 122 may correspond to a particular lithology, fluid content of the concrete, the particular profile of voltage or pressure or any other suitable characteristic. In some instances, one or more subsurface layers 122 may be a fluidic manifold which contains hydrocarbons or other fluids species. Subterranean zone 121 may include any suitable rock formation. For example, one or more subsurface layers 122 may comprise sandstone, carbonate materials, shale, coal, mudstone, granite or other material.

[0057] The illustrated exemplary processed hole 102 includes a discharge processing subsystem 120, which includes a tool 116 vehicles, road pumping units 114 and other equipment. Injection processing subsystem 120 may be used to discharge processing subterranean zone through the well bore 121 101. Discharge treatment may be hydraulic fracturing operation in which cracks are formed in the subterranean zone 121. For example, when the discharge treatment may be initiated to open or spread in one or crack multiple subterranean layers 122. fracturing operation may include an operation to test the hydraulic mini-tear on the hydraulic regular operation, or broken, for subsequent hydraulic fracturing operation, an operation to re-fracturing, the final fracturing operation or hydraulic operation rupture of another species.

[0058] In step fracturing treatment fluid may be injected into a subterranean zone 121 under any suitable pressure liquid and liquid rates. Liquids can be injected at a pressure above or below the fracture initiation pressure, higher or lower than the pressure at the closure of cracks or any suitable combination of these and other fluid pressures. Pressure initiate fractures in the formation is minimal discharge pressure fluid in which the spread can be initiated or artificial fractures in the formation. In step fracturing artificial cracks in the formation may or may not be initiated and propagate. Closing Pressure in the formation of cracks is minimal fluid pressure at which a crack existing in a subterranean formation can be extended. When the fracturing operation the natural or artificial fractures in the reservoir may or may not expand.

[0059] The operation of fracturing can be performed using any suitable system using any suitable method. Automotive pumping units 114 may include a mobile craft, fixed installations, slides, tubes, pipes, liquid receivers or tanks, pumps, valves, or other suitable structures and equipment. In some instances road pumping units 114 are connected to the work string disposed in the borehole 101. During road works pump units 114 may pump fluid through the work string and into the subterranean zone 121. The injected fluid may include a fracturing fluid, proppant, a washing liquid additives or other materials.

[0060] fracturing operation can be performed in one place or fluid injection in numerous places in the subterranean fluid discharge zone, and the liquid can be injected during one period of time or for multiple different time periods. In some instances when the fracturing operation can use many different fluids in one injection point wellbore fluid pumping numerous places in many different boreholes or on the ground in any suitable combination. Furthermore, in step fracturing fluid can be pumped through the drill holes of any suitable type, such as, for example, drilling vertical wells, inclined wellbores, horizontal wellbores, wellbores curvilinear or any suitable combination of these and other wells.

[0061] Operation fracturing can be regulated by any suitable system using any suitable method. Tool cars 116 may include a mobile craft, fixed installations or other suitable structure. Tool cars 116 may include a discharge control system which monitors and controls the fracturing operation performed by the processing subsystem 120 injection. In some embodiments, the discharge control system may be in conjunction with other equipment for monitoring and controlling the operation fracturing. For example, tool 116 may be cars in conjunction with automotive pump unit 114, underground monitoring instruments and equipment.

[0062] The operation of hydraulic fracturing, work and other natural phenomena and can produce microseismic events in a subterranean zone 121 and the microseismic data can be collected from the subterranean zone 121. For example, the microseismic data may be collected using one or more sensors 112 associated with observation wells 104, or microseismic data can be collected using other types of systems. Microseismic information found in the system 100 wells, may include acoustic signals generated from natural phenomena, acoustic signals associated with the fracturing operation performed for the treated wells 102, or other types of signals. For example, the sensor 112 can detect the acoustic signals generated by sliding rock movements of rock, rock fracturing, or other events in the subterranean zone 121. In some instances individual microseismic events can be determined on the basis of microseismic data.

[0063] Microseismic events in a subterranean zone 121 may, for example, along or near the induced hydraulic fracture. Microseismic events may be associated with the existing natural fractures or cracks planes fracturing, work created by hydraulic fracturing. Under certain conditions, most of the sedimentation detected microseismic events associated with the cracking of rocks due to shear / slippage. These events may or may not match the tension induced hydraulic fractures, which have a substantial width. On fracture orientation may affect the voltage mode, the presence of joint systems which were formed at different times in the past (for example, in the same or another stress orientation). In some embodiments, the older cracks can be cemented over geologic time and can be stored in the geological environment in the form of planes in rocks attenuation.

[0064] The observation well 104 shown in FIG. 1A is a borehole in the subterranean region 111 below the surface 106. The observation well 104 includes sensors 112 and other equipment which can be used for detection of microseismic data. Sensors 112 may include geophones or other types of listening equipment. In system 100, the wells sensors 112 may be located at different places. FIG. 1A shows sensors 112 mounted on surface 106 and lower surface 106 in the wellbore 111. In addition or alternatively the sensors may be located at other places above or below the surface 106 at other locations in the wellbore 111 or in another borehole . Observation well 104 may include additional equipment (such as a work string, packers, casing or other equipment), not shown in FIG. 1A. In some embodiments, the microseismic data is detected the sensors installed in the wellbore 102 or the treated surface, with observation well is used.

[0065] In some cases, all the computing subsystem 110, or part of it may be contained in technical command center to well-site location, at a remote location in the center on a real-time control operations in another suitable location or in a number of places. System 100 wells, and computing subsystem 110 may include any suitable infrastructure connected or have access thereto. For example, system 100 may well include multiple individual link or a network of interconnected links. The communication links may include wired or wireless communication system. For example, sensors 112 may be associated with tool car computing subsystem 116 or 110 over wired or wireless networks or lines, or automobiles tool 116 may be connected to the computing subsystem 110 via wired or wireless links or networks. The communication links can include a common data transmission network, a private data network, satellite line, dedicated communication channel, telecommunication lines, or any suitable combination of these and other communication lines.

[0066] Computing subsystem 110 may analyze the microseismic data collected in the system 100 wells. For example, computing subsystem 110 may analyze data of microseismic events during the operation fracturing subterranean zone 121. Microseismic data in step fracturing may include data collected before, during or after injecting the liquid. Computing subsystem 110 may receive microseismic data at any suitable time. In some instances the computing subsystem 110 receives the microseismic data in real time (or substantially real time) during fracturing operations. For example, the microseismic data may be transmitted to the computing subsystem 110 immediately after the detection sensors 112. In some cases, individual computing subsystem 110 accepts some or all of microseismic data after hydraulic fracturing operations. Computing subsystem 110 may receive microseismic data in any suitable format. For example, computing subsystem 110 may receive microseismic data format produced microseismic sensors or detectors or computing subsystem 110 may receive microseismic data after formatting, packaging or other processing microseismic data. Computing subsystem 110 may take the microseismic data using any suitable means. For example, computing subsystem 110 may receive microseismic data over a wired or wireless link, a wired or wireless network, or from one or more disks or other tangible media.

[0067] the computing subsystem 110 may be used to construct a histogram on the basis of microseismic events. The histogram can be used, for example, to identify the predominant orientations of cracks in a subsurface zone 121. FIG. 2 shows an example of a histogram. The predominant fracture orientation can be identified, e.g., based on local maxima in the histogram data. The predominant fracture orientation may correspond to the orientations of the families of cracks in the subterranean zone 121. In some cases, the microseismic data corresponding to each of the dominant fracture orientation, is used to form one or more planes of fracture.

[0068] Some of the operations and methods described in this application can be implemented by computer subsystem configured to provide the described functionality. In various embodiments, the computing device may include a device of any of various types, including, but not limited to, personal computers, systems, desktop computers, portable computers, laptops, mainframes, handheld computers, workstations, graphic tablets, application servers, storage devices or computing or electronic device of any kind.

[0069] FIG. 1B is a block diagram of an exemplary computing subsystem 110 of FIG. 1A. The exemplary computing subsystem 110 may be located near or adjacent to one or more wells of the 100 wells of the system or on a remote site. All computer subsystem 110 or part of it can run independently of the system 100 wells or independently of any other components as shown in FIG. 1A. The exemplary computing subsystem 110 includes a processor 160, memory controller 150 and 170 IO connected bus 165. The memory may include, for example, random access memory (RAM), storage device (such as a read only memory (ROM) rewritable or others), a hard disk or other storage medium type. Computing subsystem 110 may be pre-programmed or can be programmed (and reprogrammed) by loading a program from another source (e.g., CD-ROM, read-only, with other computing devices over a data network or otherwise). Controller 170 input-output connected to the input-output devices (e.g., monitor 175, mouse, keyboard, or other input-output devices) and communication line 180. Input-output devices receive and transmit data in analog or digital form over communication lines such as a serial data line, wireless link (e.g., infrared, RF or otherwise), a parallel data line or other kind of line.

[0070] Communication line 180 may include any type of communication channel, a connector, a data network or another line. For example, 180 link may include a wireless or wired network, local area network (LAN), wide area network (WAN), private network, public network (such as the Internet), Wi-Fi network, a network that includes satellite link or a data network of another type.

[0071] The memory 150 may be stored commands (e.g., computer code) associated with the operating system, computer application programs and other resources. In addition, memory 150 may store data and application data objects that can be interpreted by one or more applications or virtual machines running on the computer based subsystem 110. As shown in FIG. 1B, the exemplary memory 150 includes 151 microseismic data, geological data 152, data 154 of cracks, and other data 155 and application programs 156. In some embodiments, the computing device memory includes additional or other information.

[0072] Microseismic data 151 may include information about the location microseisms in the underground area. For example, the microseismic data may include information based on the acoustic data detected in the observation well 104 on the surface 106 in the well 102 or treated in other places. Microseismic data 151 may include information collected by the sensors 112. In some cases, the microseismic data 151 is combined with other data, reformat, or otherwise processed. a microseismic event data may include any suitable information pertaining to microseismic events (location, size, uncertainty, times, etc.). Data on the microseismic events can include data collected in carrying out one or more fracturing operations, which may include data collected before, during and after the injection of the liquid.

[0073] The geological data 152 may include information about the geological properties of the subterranean zone 121. For example, geological data 152 may include information about underground layers 122 of the boreholes information 101, 111 or information about other attributes of the subterranean zone 121. In some cases, the geological data 152 include information about lithology, fluid content, voltage profile, a pressure profile, spatial extent or other attributes of one or more rock formations in a subterranean zone. Geological data 152 may include information collected from the logs, rock samples, outcrops, microseismic images or other data sources.

[0074] The data of 154 fractures may include information about the plane of the crack in the subterranean zone. According to cracks 154 can identify the location, size, shape and other properties of the fracture zone in a subsurface model. These cracks of 154 may include information about the natural fractures hydraulically induced fractures or rupture of any other kind in the subterranean zone 121. These cracks about 154 may include calculated data for microseismic fracture plane 151. Each plane data crack 154 of cracks can include information (e.g., angle of stretch, incidence angle, etc.) identifying the orientation of a crack, information identifying the shape (e.g., curvature, aperture, etc.) crack, information identifying the boundary cracks or any other suitable information.

[0075] Applications 156 may include software applications, command files, programs, functions, or other executable files modules that are interpreted or executed by the processor 160. Such applications may include computer-readable instructions to perform one or more operations represented FIG. 4. Applications 156 may include computer readable instructions for education or graphics user interface, such as, for example, the histogram shown in FIG. 2. The application program 156 may receive input data, such as microseismic data, geologic data or other types of input data from the memory 150 from another local source or from one or more remote sources (e.g., communication lines 180). Applications 156 may generate output data and store the output data in the memory 150, on the other local storage media or in one or more remote devices (eg, by passing the output through line 180 data communications).

[0076] The processor 160 may execute instructions, for example, to generate output data based on input data. For example, processor 160 may drive the application programs 156 or by performing the interpretation software, command files, programs, functions, or other executable files modules contained in the application programs 156. The processor 160 may perform one or more operations shown in FIGS. 4, or form a histogram shown in FIG. 2. Input data received by the processor 160 or the output data generated by processor 160 may include any of the microseismic data 151, geological data 152, data 154 of cracks or other data 155.

[0077] FIG. 2 is a graph showing an exemplary histogram 200. The exemplary histogram 200 shown in FIG. 2 is a graphical representation of the distribution of the main orientations of the planes identified by a set of microseismic data. The histogram can be based on other types of data, and can display a histogram of another species.

[0078] An exemplary histogram 200 shown in FIG. 2, includes a surface plot 206 displaying the probability of cracks the orientations of planes. In some instances the histogram includes a graph of another type. For example, a histogram can display the same or similar information as the bar graph, chart or topographic chart of another species. In the example shown in FIG. 2, each crack plane orientation is represented by two variables, angle of strike and dip angle. The histogram can be used to display the quantitative distribution parameters for one variable, two variables, the variables three or more variables.

[0079] The surface 206 shown in FIG. 2 is shown in the spatial coordinate system. Some histogram depict in two dimensions (e.g., in the case of the distribution for a single variable), three dimensions (e.g., in the case of two variables distribution) or four dimensions (for example, in the case of two variables distribution in the dynamics over time). In the example shown in FIG. 2, spatial coordinate system is represented by the vertical axis 204a and two horizontal axes 204b and 204c. The horizontal axis represents the range 204b angles of incidence and the horizontal axis is represented 204c stretch range of angles (in units of degrees). The vertical axis represents the probability 204a range.

[0080] The parameters of the histogram 200 may be quantified, for example, by forming columns, each of which represents a different range of orientations. Ranges orientations may be adjacent, non-overlapping ranges of one or more variables orientation. For example, the column may range trending or range of angles of incidence angles. A histogram 200 shown in FIG. 2, each of the columns of the histogram correspond to the intersection of subbands along horizontal axes 240b and 204c.

[0081] Additional parameters of the histogram 200 may be quantified, for example, by calculating the orientations of cracks quantitative parameter related to each column. A histogram 200 shown in FIG. 2, the quantitative parameter for each column is represented by the surface level 206 for each of the ranges of orientations represented in the graph. Quantitative parameters shown in FIG. 2 are the normalized values ​​of probability. Usually quantitative parameter for each column in the histogram may be normalized or non-normalized quantitative parameter quantitative parameter. For example, the quantity of the fracture plane for each column can be a value of probability, frequency value, the value of an integer or a value of another type.

[0082] The quantitative parameter fracture planes for each bar of the histogram can be determined, for example, by ascribing to each crack plane to the post, counting the number of planes of cracks with orientation within the range represented by each bar, or a combination of these and other methods. In some cases, cracks are main planes of the plane bounded microseismic data points, each of the main planes determines the orientation corresponding to one of the columns.

[0083] An exemplary histogram 200 represents the probability distribution of the main planes, associated with 180 microseismic events. In this example, each column displays stretch subband values ​​within the range of stretch, histogram 200 shown in (from 0 ° to 360 °), and the fall subband values ​​fall within the range shown in the histogram 200 (from 60 ° to 90 °). On the map the surface of the 206, there are several local maxima (peaks), five of which in FIG. 2 labeled as 208a, 208b, 208c, 208c and 208d.

[0084] The peaks in the histogram bars 200 are associated with a significant quantitative parameters than the surrounding columns. Columns represented peaks correspond to a set of planes of cracks that have the same or parallel orientation. In some individual cases, each local maximum (or peak) in the histogram can be considered relevant prevailing trend (ie, primary) orientation. The trend can be considered the predominant orientation of crack orientation, for example, when more major surfaces are aligned in this direction than in the adjacent or nearby lines. The predominant orientation of the fracture can reflect a statistically significant quantity of the main planes of which are parallel, or substantially parallel to the surface are on the same.

[0085] The example shown in FIG. 2 is a histogram based on the two angular parameters of each base plane (ie, at the corners of the strike and dip). The histogram may be based on other parameters main planes. For example, the third parameter of each main plane can be included in the histogram data. The third parameter may, for example the distance d from the start of the main plane. The histogram can be formed depending on the parameters for a distance dependent on the orientation parameters or a combination of these parameters. Some examples of a histogram may be formed for the value d · tan (θ) and d · tan (φ), for each base plane based on the distance d of each base plane from the beginning, the angle φ stretch each main plane and the angle θ of incidence of each base plane . In some cases a two-dimensional diagram may be formed on the basis of any two independent variables, such as tan (θ), tan (φ), the angle φ stretch, the angle of incidence θ, or others. The histogram may have a suitable configuration based on the size of the columns. For example, the histogram may be a histogram with bars of a fixed size, a histogram with bars of natural size, or other type of histogram. In some individual cases, for a given set of microseismic events may be optimal (non-uniform) histogram, which best shows the orientation of the plane of the crack.

[0086] In Figures 3A and 3B are diagrams showing an example of the orientation of the plane of the crack. FIG. 3A is a diagram 300a main plane 310 defined by three collinear microseismic events 306a, 306b and 306s. FIG. 3B shows a diagram 300b of the normal vector 308 for the main plane 310 of FIG. 3A. Figures 3A and 3B, the vertical axis shows 304a coordinate z, is represented by the horizontal coordinate axis x 304b and 304c is represented by the horizontal axis of the coordinate y. The diagrams 300a and 300b shown in rectilinear coordinate system; possible to use other types of coordinate system (e.g., spherical, elliptical, etc.).

[0087] As shown in FIG. 3A, the main plane 310 is a two-dimensional surface, which extends in a spatial system xyz-coordinates. The normal vector 308 indicates the orientation of the main plane 310. The normal vector may be a unit vector (a vector having a unit length) or normal vector can be nontrivial length.

[0088] As shown in FIG. 3B, the normal vector 308 has components (a, b, c) vector. Components (a, b, c) of the vector can be calculated, for example, under the provisions of microseismic events 306a, 306b, and 306c, based on the parameters of the main plane 310, or based on other information. The chart 300b x component of the normal vector 308 is represented as a length along the x-axis, y component of the normal vector 308 is represented as a length b along the y-axis and z components of a normal vector 308 is represented as a length along the z axis. (In the illustrated y-component b has a negative value, which means that the y-component of the normal vector opposite in direction 308 relative to the selected default positive direction of the horizontal axis 304c).

[0089] The orientation of the base plane 310 can be calculated based on the normal vector 308 itself microseismic events, parameters main plane 310, other data or any combination of them. For example, the fall of θ and φ stretch of the main plane 310 can be calculated based on the normal vector 308 in accordance with equations

<img file="00000006.tif" he="14" wi="119" img-format="tif" img-content="undefined" />

In some cases, computational methods can be taken into account to appropriately control the sensitivity of these equations in extreme situations, such as when a parameter or is very small.

[0090] In some cases, the orientation of one or more major surfaces can be used as input to generate histogram data. For example, a histogram of orientations of the major surfaces may be formed from a set of main planes. In some cases, the histogram data form by assigning to each base plane histogram of the pillar on the basis of the orientation (θ, φ) the main plane and calculating a quantitative parameter main planes associated with each column. In some cases, the histogram is displayed, or histogram information may be used or processed without displaying the histogram.

[0091] FIG. 4 is a flowchart of operations of an exemplary method 400 for identifying dominant fracture orientation. Some or all of the steps of method 400 may be implemented by one or more computing devices. In some embodiments, method 400 may include fewer, additional or different operations performed in the same or a different order. In addition, one or more subsets of individual actions or actions of method 400 may be performed separately or in other situations. Output data generated during execution of the method 400, including the output data generated when the intermediate action may include stored, displayed, printed, sent, transmitted or processed information.

[0092] In some embodiments, some or all steps of method 400 is performed in real time during the fracturing operation. For example, the action can be performed in real time by performing operations without substantial delay in response to the reception of data (for example, a sensor or monitoring systems). The action can be performed in real time, for example, by performing operation for additional monitoring microseismic data during fracturing operations. When you perform certain actions in real-time can receive input data and generate output data for operations on hydraulic fracturing; in some instances the output data made available to the user within a predetermined time interval, allowing the user to respond to the output data, for example, to adjust the fracturing operation.

[0093] In some cases, some or all of the steps of method 400 is performed dynamically during the fracturing operation. The action can be performed dynamically, for example, by performing an iterative or repeated action based on additional input, when input data becomes available. In some instances the dynamic actions performed in response to a data reception for the new microseismic events (or in response to the reception of data for a number of microseismic events, etc.).

[0094] In step 402, the microseismic data taken when the fracturing operation. For example, the microseismic data may be received from memory from a remote device or other source. of microseismic event data may include information on the location of numerous measurements of microseismic events, information about the measured magnitude of each microseismic event, information on the uncertainty associated with each microseismic event, the time information associated with each microseismic event, etc. Data of microseismic events may include microseismic data collected from observation wells processed downhole, at the surface or elsewhere in the well system. Microseismic data in step fracturing may include data on the microseismic events detected before, during or after the fracturing operation. For example, in some instances microseismic monitoring operation to begin fracturing, after an operation is complete fracturing.

[0095] In step 404 identifies subsets coplanar microseismic events. Coplanar subset of microseismic events may include three or microseismic events over three microseismic events. For example, each subset may be a triplet places microseismic events. In some cases, coplanar subsets identified by the identification of a set of triplets in microseismic event data. For example, in the case of N sites identifying microseismic events can be N (N-1) (N-2) / 6 triplets. In some cases, not all subsets of triples identified as. For example, some triplets (e.g., collinear or substantially collinear triplets) can be eliminated.

[0096] In step 406 main plane coplanar identified for each subset of microseismic events. For example, the main plane can be identified by calculating the parameters of the main plane axes Considerations triplet locations of microseismic events. In some cases, a plane can be determined by three parameters a, b and c of the base plane model. These parameters can be calculated based on the coordinates x, y and z of three non-collinear points in the subset, for example, by solving a system of linear equations for the three parameters. For example, the parameters of the plane defined by the three collinear events (x₁, y₁, z₁), (X₂, y₂, z₂) And (x₃, y₃, z₃) Can be calculated on the basis of the solution of the following system of equations:

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[0097] At step 408, calculate quantity of the main planes of each of the plurality of orientations ranges. Ranges orientations may correspond to the histogram column. In some cases, the orientations ranges together cover the full range of orientations of the principal planes, and each individual orientation range corresponding to the solid angle in three dimensional space. The solid angle can be set, for example, the range of angles of incidence and range of strike angles or range of angles, based on the angle of strike combinations, and the angle of incidence.

[0098] A quantitative parameter main plane orientations in each range can be calculated, for example, by identifying the orientation of each base plane and to determine the range in which the main orientation is the orientation of the plane. In some cases, the normal vectors are calculated for all major surfaces, and the main orientation plane is calculated based on the orientations of the normal vectors. In some cases, each base plane orientation includes angle of strike and dip angle for one of the main planes. For example, the main planes of orientation can be calculated using Equation 1, above. Other methods may be used to calculate the orientation of the base plane.

[0099] In some embodiments, the orientation ranges are pre-computed values. For example, ranges of orientations can be defined independently of the orientation of the main planes. In some embodiments, the orientations determined based on the ranges of basic orientations of the planes identified in step 406. For example, as shown in FIG. 4, in step 408 can sort values ​​orientations main planes and orientations may be identified ranges in step 410 based on the sorted values ​​of basic orientations of planes (for example, using any clustering methodology nearest neighbor schemes, etc.).

[0100] In some instances the ranges of orientations were identified on the basis of the clustered sets of sorted values ​​orientations. For example, the orientation of the ranges can be identified by sorting the corners stretch, identifying clusters of assorted corners of the strike, the sort of angles of incidence, identify clusters of assorted angles of incidence and determine the range of orientations on the basis of clusters of assorted corners and stretch clusters assorted angles of incidence. Examples of ways to identify orientations of the ranges described in the provisional application №61 / 710,582 US patent, filed October 5, 2012.

[0101] In step 412, calculate quantity of the basic orientation of the planes in each range. Quantitative parameters of the main orientations of the planes may be the probability, frequency, an integer value of planes or other species. For example, the quantitative parameters of the main orientations of the planes in a given range can be among the main planes with the orientation of the main plane in a predetermined range of orientations. In another example, the quantitative parameters of the main orientations of the planes in a given range can be among the main planes with the orientation of the main plane in the specified range of orientations, divided by the total number of identified major planes. Quantitative parameters may be normalized, for example, quantitative parameters to sum to one (or the other fiducial value). Examples of ways to identify quantitative parameters described in the provisional application №61 / 710,582 US patent, filed October 5, 2012.

[0102] In step 414, the dominant fracture orientation is identified based on quantitative parameters calculated in step 412. The dominant fracture orientation can be identified, such as orientation ranges having higher local maxima main plane orientations. In some instances the dominant fracture orientation is identified based on local maxima in the histogram data formed on the basis of quantitative parameters. It is possible to identify a single predominant orientation of crack or it is possible to identify many dominant fracture orientation. In some instances cracks predominant orientation is identified based on the height, width and other parameters of a peak of histogram data. Dominant fracture orientation can be identified as the center point of a range of orientations, dominant fracture orientation can be calculated as the average orientation of the major plane in a range of orientations or crack orientation bias can be calculated in another way. In some instances the confidence level may be assigned to a peak of histogram data. The confidence level may indicate the extent to which the certainty associated with the peak. The confidence level can be set, for example, proportional to the amount of input data for a particular column of the histogram peak that supports, or other suitable means.

[0103] The predominant orientation of the fracture identified based on quantitative parameters calculated in step 412 may represent the physical orientation of fractures in a subterranean zone. In certain rock formations cracks generally form sets (or family), or the like having a parallel orientation. Some reservoirs include multiple sets of cracks. For example, the reservoir may include a first set of cracks having a primary orientation which may be due to the direction of maximum stress. Formation may also include a second set of cracks having a secondary orientation, which is different from the primary orientation. Secondary orientation may be rejected from the primary orientation, for example, at an angle of 90 ° or another angle. In some cases, each of the dominant fracture orientation corresponds to the orientation set in a subterranean fracture zone.

[0104] In some instances identify dominant fracture orientation in accordance with an algorithm or method that can search for any preferred orientation, for example, on the basis of physical properties, or any other information. Using the algorithm can identify whether data strongly indicate a predominance of the orientation (e.g., based on the reliability value between 0 and 1), and taking into account the time of formation of various primary orientation trend information can be used in the algorithm.

[0105] In step 416, a histogram of values ​​orientations of the main planes. The histogram shows the quantity of the main orientations of the plane of each of the ranges of orientations. An example histogram is shown in FIG. 2. Quantitative parameters may be displayed in a different format, or a histogram of another species. The histogram can be represented, for example, in two dimensions or three dimensions. In some cases, the histogram is depicted as a continuous line or surface in the form of discrete groups of symbolic characters (such as a bar chart), in the form of topographic regions or in the form of a graphical representation of another species. In addition to presenting a histogram or alternatively a histogram representation can display the main plane of orientation values ​​as numerical values, values ​​of algebraic, numeric or in another table format.

[0106] In step 418 form a plane cracks. Plane cracks can be formed, for example, based on the microseismic data points and the prevailing orientations cracks identified in step 414. In some cases, the cluster identified microseismic events associated with each of the dominant fracture orientation, and form the crack plane at the base of each cluster. In some individual cases, crack plane is identified on the basis of location and other parameters measured microseismic events. For example, the crack plane can be formed by adjusting the individual clusters of microseismic events to the plane. For the formation of crack plane may use other methods. Examples of methods of cracking planes on the basis of microseismic data described in the provisional application №61 / 710,582 US patent, filed October 5, 2012.

[0107] In some instances in the algorithm can enter the external input data (e.g., from the user of the other physical considerations, etc.). External inputs may include information such as, for example, "probably, this orientation should be the primary orientation" (and therefore has a predetermined validity indication), "it is less likely that the orientation is plane in this direction" (and therefore has very small or even zero confidence level). Input these species can change calculation planes contained in the microseismic data set to reflect these parameters.

[0108] In some individual cases, the histogram is displayed in real time during the operation on hydraulic fracturing, and the histogram can be dynamically updated with additional detection of microseismic events. For example, every time you receive a new microseismic events can be identified additional fundamental plane and therefore can update quantity of the basic orientations of the planes in each range. In some cases, the orientations of ranges dynamically updated upon receipt of microseismic data. Examples of ways to update the histogram on the basis of additional microseismic data described in the provisional application №61 / 710,582 US patent, filed October 5, 2012.

[0109] In some cases, the crack plane update in real time, for example, in response to collection of microseismic data. Examples of ways to upgrade the planes of cracks on the basis of microseismic data described in the provisional application №61 / 710,582 US patent, filed October 5, 2012. In some cases, the confidence level for each plane of the crack can be changed (for example, to raise, to lower) on the basis of new microseismic data. In some individual cases can form a new plane cracks or fissures formed before the plane can be excluded on the basis of new microseismic data.

[0110] Some embodiments of the invention, the object and the actions discussed in this description may be implemented by digital electronic circuits or computer software, middleware or hardware, including the structures disclosed in this specification and their structural equivalents, or a combination of them . Some embodiments of the subject invention, discussed in this application may be implemented as one or more computer programs, i.e., in the form of one or more modules of commands to a computer program encoded on a computer storage media intended for the execution of data processing equipment or control the operation of the processing equipment. computer storage media may be implemented as or included in the computer readable storage device, a computer readable memory card, or memory array device with random access or sequential, or a combination of them. Furthermore, although the computer storage medium is not a propagated signal, a computer storage medium can be a source or receiver to the computer program instructions encoded in an artificially formed by the propagating signal. In addition, computer storage media may be implemented as or included in one or more separate physical components of carriers (such as multiple CDs, disks, or other storage device).

[0111] The term "data processing apparatus" encompasses all kinds of apparatus, devices, and machines for processing data, including, for example, a programmable processor, a computer, a system on a chip or multiple agents listed, or their combinations. The apparatus may include specialized logic circuits such as gate array, programmable (VMPP) or application specific integrated circuit (ASIC). Furthermore, in addition Maintenance equipment can include code that creates the execution environment for the current computer program, that is, code that constitutes the firmware of the processor means, a protocol stack, a database management system, an operating system, cross-platform runtime environment, a virtual machine, or a combination of one or more of them. The equipment and the runtime can be implemented many different computing model infrastructure, such as web services, distributed computing, and network computing infrastructures.

[0112] A computer program (also known as a program, software, software application, program, or shell code) can be written in the programmable language of any kind, including compiled or interpreted languages, declarative or procedural language. The computer program may, but need not, correspond to a file in the file system. The program may be stored in a portion of a file that holds other programs or data (e.g., one or more command processor program stored in the document in a markup language), in a single file specifically designed for the current program, or in multiple coordinated files (e.g., files, in which are stored one or more modules, routines or portions of code). The computer program may be arranged to run on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

[0113] Some methods and logical streams discussed in this description may be performed by one or more programmable processors executing one or more computer programs to perform operations on input data and generating output data. Furthermore, the methods and logic flows can be executed, and the apparatus can also be realized by the specialized logic, such as a gate array, programmable (VMPP) or application specific integrated circuit (ASIC).

[0114] Processors suitable for the execution of a computer program include, for example, general purpose microprocessors and specialized as well as processors of any kind of digital computer. Typically, the processor receives instructions and data from a read-only memory or a random access memory or both. The computer includes a processor to perform actions in accordance with instructions and one or more memory devices for storing instructions and data. Additionally, the computer may include one or more mass storage devices such as magnetic, magneto-optical disks, or optical disks for data reception or data transmission, or may be operatively associated with them. However, the computer does not necessarily have such devices. Devices suitable for storing instructions to a computer program and data include nonvolatile memory, storage media and storage devices of all kinds, including, for example, semiconductor memory devices (e.g., programmable ROM, electrically erasable programmable read-only memory, flash memory, etc.), magnetic disks (such as internal hard drives, removable drives, etc.), magneto-optical disks, compact discs, read-only, and digital versatile disks, read-only. The processor and memory are implemented with dedicated logic circuitry or incorporated therein.

[0115] In order to ensure interaction with the user actions can be performed on a computer having a display device (such as a monitor or display device of another type) to display information to the user and a keyboard and a pointing device (eg, mouse, trackball, tablet, a touch screen or another type of pointing device) by which the user can provide input to the computer. Furthermore, for interaction with the user can use other types of devices; for example, feedback to the user may be sensory feedback of any kind, such as visual feedback, audio feedback, or tactile feedback; and input from the user can be received in any form, including as acoustic, speech, or tactile input. In addition, the user's interaction with the computer may be in the shipment documents to the device, which uses the user, or receive a document from the device, sending Web pages to a web browser user of the client device in response to a request received from the web browser.

[0116] The client and server are generally remote from each other and typically interact through a communication network. Examples of communication networks include a local area network (LAN) and a wide area network (WAN), internetwork (e.g., the Internet), the network comprising a satellite link, and ad hoc networks (e.g., specialized ad hoc networks). client and server interaction occurs with the help of computer programs running on the respective computers and having a client-server relationship to each other.

[0117] According to some aspects of which are described in this application, prevailing orientation enclosed in cracks sets associated with microseismic events can be identified dynamically during fracturing operations. For example, the plane of the crack can be obtained in real time on the basis of microseismic events collected from the field. Plane cracks can be identified on the basis of information about the microseismic events, comprising events location measurement uncertainty event locations, the magnitude of moments events, points of time when events and others. At each time point the data may be associated with the previously calculated main planes including microseismic reference set of events.

[0118] According to some aspects of which are described in this application, the histogram or probability distribution of the basic planes can be built on the basis of the collected microseismic events and histogram or distribution can be used to obtain the prevailing orientations of cracks. In some instances the distribution or histogram may be iterative in the sense that when the next iteration can be displayed peaks histogram distribution or better resolution (e.g., through the use of a suitable size histogram bars or any other suitable method). In some instances from iteration to iteration, the number of columns in each of the components of orientation and the grouping can be changed, improved, or optimized updated. Cracks selected along the prevailing attitudes in some instances may be in real time to ensure optimal compliance with the microseismic events. The histogram or distribution and prevailing orientation can have a significant sensitivity to the new upcoming microseismic events. In this regard, some plane identified during a comparison of MS data can not be accurate when compared with the results based on the following microseismic events.

[0119] According to some aspects described herein, accurate reliability parameter may provide a measure of accuracy in real time identifiable surfaces. Factors influencing the precise accuracy of the planes, can include custom properties of events, the relationship between the reference plane and the events and weight, reflecting the trends orientations of cracks in the data on the follow-microseismic events. In some instances cracks in the end plane fracturing operation having a high reliability which have been identified in real time is compared with the fracture planes, based on the data obtained subsequent events.

[0120] In some aspects, some or all of the features described in this application may be combined separately or implemented in one or more software programs from a system for automatic real-time mapping of cracks. The software can be implemented as a computer program product, installed application program, a client-server application program, the application program of the Internet or any other software suitable type. In some cases, the program automatically in real-time mapping of cracks can dynamically in real-time to show users the spatial and temporal evolution of the identifiable plane cracks with the gradual accumulation of microseismic fracture. For example, a speaker may include the formation of new cracks spreading and growth of existing cracks or other dynamic characteristics. In some cases, the program automatically in real-time mapping of cracks may provide users with the ability to monitor in real time the identifiable planes cracks at many levels of reliability. In some instances, users can monitor the spatial and temporal evolution of the cracks with a high level of confidence that may be prevailing trends in the complete data on microseismic events. In some cases, a program for automatic real-time mapping of cracks may estimate the exact accuracy of cracks, for example for estimating fracture planes identified certainty. For example, the exact values ​​of reliability can help the user to better understand and analyze the changes in the histogram or probability distribution of orientations, which can vary continuously with the accumulation of real-time microseismic events. In some cases, the program automatically in real-time mapping of cracks may produce results that are consistent with the mapping of cracks on postdannym. For example, after fracturing operation results obtained by using a program mapping automatically in real time can be statistically consistent with the results obtained using the program for automatic mapping postdannym cracks running on those same data. These characteristics may allow fishing engineers, operators and interpreters to dynamically visualize and control the spatial and temporal evolution of fracturing cracks to analyze the complexity of the geometry of the fracture and reservoir, to evaluate the effectiveness of fracturing operations, and improve the performance of wells.

[0121] Although this description contains many details, they should not be construed as limiting the claimed amount, but as a description of the character of specific examples. Furthermore, there may be incorporated some features which are considered in this specification with reference to specific embodiments. Conversely, various features that are described in relation to one embodiment may also be implemented in multiple embodiments separately or in any suitable subcombination.

[0122] described several embodiments. Nevertheless, it should be understood that various modifications may be made. Accordingly, other embodiments are within the scope of the following claims.