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    • 专利摘要:
    The present invention relates to a computing device that facilitates the organization of a plurality of three-dimensional realizations of geographic data into respective one-dimensional tables of geological property values, each geological property value corresponding to a three-dimensional grid location of a three-dimensional realization. respective geological data. The computing device then facilitates the grouping of the one-dimensional tables into two or more table collections based on a comparison of geometric locations of the geological property values within the respective tables, and selects at least one embodiment of the plurality. three-dimensional realizations of geographic data for each of the two or more table groupings. The selected data realizations are then provided to a user interface.
    公开号:FR3034222A1
    申请号:FR1651051
    申请日:2016-02-10
    公开日:2016-09-30
    发明作者:Jin Fei；Genbao Shi；Jeffrey Marc Yarus；Richard L Chambers
    申请人:Landmark Graphics Corp；
    IPC主号:
    专利说明:

    [0001] 1 GROUPING ANALYSIS FOR SELECTING PETROLEUM LAYER MODELS FROM MULTIPLE GEOLOGICAL ACHIEVEMENTS BACKGROUND [0001] A virtual simulation can be performed on the basis of a model of a geological region to assist in understanding the features of the geological area represented by the model. For example, for a well, virtual simulation can assist a well operator in improving the production of fluids from an associated oil layer. The model of the geologic region can be composed of a grid of cells, each cell being associated with one or more geological properties (eg, porosity, permeability, etc.) that define the formation of geologic structures in the region. [0002] In traditional geological modeling, simulations are based on geological data values corresponding to the grid cells in a corresponding geological model. Due to the large number of grid cells in the model, a single simulation may require a significant amount of processing time and power. In addition, to address uncertainty in the interpretation of a geological model through simulation, a stochastic process can be used to produce multiple realizations of the same model, each with different values. Multiple simulations are then produced based on the achievements for evaluation by an operator. However, processing multiple implementations increases the amount of time and processing power required to produce the simulations. BRIEF DESCRIPTION OF THE DRAWINGS [0003] The following figures are included to illustrate certain aspects of the present invention and should not be considered as exclusive embodiments. The presented content is capable of considerable modifications, alterations, combinations and equivalences in form and function without departing from the scope of this invention. [0004] FIGS. 1A and 1B show three-dimensional grid matrices corresponding to respective virtual models. for example, used for the simulation of a geographical area. [0005] FIG. 2 represents an example of a data realization of a geographical area represented by an example of a three-dimensional grid matrix. FIG. 3 represents an example of a flowchart of a process for selecting realizations of geographical data. [0007] FIG. 4 illustrates an example of a user interface for selecting geographic data realizations in a dynamic execution environment on a computing device. FIG. 5 is an example of a diagram illustrating an electronic system to be used in conjunction with a selection process of geographic data realizations.
    [0002] DETAILED DESCRIPTION [0009] The detailed description set forth below is intended to be a description of various configurations of the present invention and is not intended to be the only configurations in which the present invention can be practiced. The accompanying drawings are incorporated in this description and constitute a part of the detailed description. The detailed description includes specific details for the purpose of providing a thorough understanding of the present invention. However, it should be apparent that the present invention can be practiced without these specific details. In some instances, the structures and components are shown in block diagram form to avoid obscuring the concepts of the present invention. Similar components are referenced by identical item numbers for ease of understanding. Submitted technology provides various mechanisms for automatically selecting geographic data realizations. For example, the submitted technology can be used to categorize a large number of geographic data realizations generated from a stochastic process into a smaller number of groups, and to facilitate the selection of the most appropriate realizations for a virtual simulation. Therefore, geological data corresponding to each geological realization is organized in a corresponding table of geological property values, each geological property value and each position in the table corresponding to a grid location of the original model structure. . In one or more implementations, the geological model - for example, a volumetric (three-dimensional) interpretation of the realization data - is reduced to a one-dimensional table according to a predetermined algorithm, each table location representing a coordinate space in the model. . In one or more implementations, the algorithm reduces the model according to the geometry so that a distance between cells in corresponding tables can be easily calculated when each cell of the one-dimensional tables is compared side by side. In one or more implementations, the tables corresponding to the realizations of data are grouped into groups of tables on the basis of the comparison of the geometric locations of similar values within the tables. In this regard, the distance between similar values of geological property in the respective tables can be determined. For example, an algorithm may compare a first table with other tables by searching for a cell index within the table and determining its offset with cell indices in other tables containing an identical or similar value. The offset is representative of the distance between these property values in the corresponding three-dimensional models (e.g., a Euclidean distance). Tables having identical property values (petrophysical property values, e.g., porosity, permeability, etc.) at the same indices or near the same indices in the table (e.g., small offsets) can be determined to be more similar and to be grouped together.
    [0003] 100121 Based on the comparison of any property values of the cells in the tables, degrees of similarity can be determined between the geological property values or respective tables, and thus the data realizations. In one or more implementations, the degrees of similarity may be represented in numerical form (for example, a percentage). The number of table groups in which the tables of geological property values are grouped can be determined based on an application of a similarity threshold degree to the specified degrees of similarity between the tables representing the 3034222 4 data realizations . Therefore, the threshold can be set by a user via a user interface and, in response, the submitted technology can group the tables, and thus the corresponding data realizations, into a number of groups based on the threshold. For example, each group may comprise data realizations that are determined to be similar to each other by a degree of similarity at or above the set threshold. The degrees of similarity can also be represented visually as a virtual tree structure (for example, a dendrogram tree), each leaf of the tree being representative of a table and the leaf branches being representative of similar tables. The tree structure can have multiple levels of branches. Each branch of the tree may represent a similarity between the branches and / or the leaves it contains, and so on, with a degree of similarity between the leaves decreasing with each successive branch towards the root of the tree. The virtual tree structure may be presented visually in a graphical user interface in conjunction with a graphical representation of the property value tables, visually arranged side by side. The submitted technology can also automatically arrange the tables so that similar tables are close to each other in the user interface. A threshold indicator may be moved up or down on the branches of the tree to visually adjust the degree of similarity threshold used to determine the tables that are grouped into table groups. In this way, a user can visually move the threshold indicator and the user interface can automatically assign tables to groups of tables based on the position of the indicator in the tree. In some implementations, a geological property value at a particular table index may be expected to be similar to other property values at the same table index in other tables, or to nearby indices. of the table index in the other tables. In this regard, the subject technology can identify the degree of similarity between geological property values in cell indices across, for example, all tables. Clusters of cells can then be identified within the tables based on the degrees of similarity identified between the cells. The tables can then be separated into groups of cells in the table near each other table based on a user-defined degree of similarity threshold. A virtual threshold tree and threshold identifier can then be used in the same manner as previously described with respect to grouping the tables to identify the size of the cell groups. [0015] Once the cell groups are identified, the groups can be used by the algorithm, described above, used to determine the similarity between tables. In this regard, the distance between similar values of geological property in the respective tables can be determined, for example, on the basis of the groups of cells instead of the individual cell indices. For example, an algorithm may compare a first table with other tables by considering the location and / or size of a group of cells within the table and determining which of the other tables has groups of cells located in a similar way. The grouped tables groups can be visually displayed to the user, and the user can select one or more groups to perform a simulation. In one or more implementations, a realization of data corresponding to one of the tables within each group of tables grouped is selected for the simulation. In this regard, the number of data realizations on which a simulation is performed is significantly reduced, which reduces the time and processing power required to simulate all available realizations. The simulation representing each group can. then be ranked and / or compared to observed data. FIGS. 1A and 1B represent three-dimensional grid matrices 102, 104 corresponding to respective virtual models given by way of example, used for the simulation of a geographical zone, according to one or more aspects of the technology. submitted. Each grid matrix 102, 104 may be a volumetric (three-dimensional) model of construction data. Each of the grid cells 106 that make up each array may correspond to a geological property value for a geological area represented by the model.
    [0004] For example, gate cells 106 may be lined with values corresponding to a porosity so that a corresponding simulation illustrates the flow of a fluid through the geological area represented by the model. In the example shown, the dark cells 108 are pores while the empty cells 110 represent a non-porous medium such as a rock. In a soil geostatistical modeling (EM), there may be multiple oil layer achievements. Geologists and reserve assessment specialists may select a few candidate models from among hundreds of these property achievements. The submitted technology software selects candidate simulations from a statistical analysis of oil layer volumetrics. In this regard, embodiments may be classified according to various criteria including, for example, variables that may affect volume, such as porosity and permeability. The variables can be ordered by rank and candidate oil layer models selected from the ordered distribution. In this way, rankings can represent key thresholds, or quantiles, of interest. The quantiles of interest may relate to oil layer volumetrics, and the volumetrics may relate to contiguous oil layer volumes. For example, the first ten percent of ranked achievements (P10) may represent an overestimated result with a large connected volume, and the last ten percent of ranked achievements (P90) may represent a conservative result with a smaller connected volume. [0019] Some methods may consider quantiles of a distribution, but lack analysis on the physical geometrical information. For example, each of the cubes shown in Figures 1A and 1B is shown as having 6 * 2 * 4 cells for porosity simulation. If the dark cells 108 are considered to be pores, the cube of FIG. 1A and the cube of FIG. 1B can both represent 12/48 = 0.25 pu of porosity. Using a traditional volumetric analysis with a cutoff of 0.25 pu, the cube could be considered a candidate model. However, the embodiment of FIG. 1A has isolated pores and there is no continuity in the horizontal permeability nor in the vertical permeability. With regard to the cube of FIG. 1B, the horizontal permeability is higher. To select a model from the two corresponding models, geologists and reserve evaluators can load both outputs and compare them visually, for example, to select the model corresponding to Figure 1B as an optimal achievement. As described below, the subject technology applies clustering analysis to distinguish different embodiments to reduce uncertainty in selecting a candidate oil layer model for simulation. FIG. 2 represents an exemplary data embodiment of a geographic area represented by a three-dimensional grid matrix 200, given by way of example, according to one or more aspects of the subject technology. . Each cell 202 of the grid matrix 200 may represent one or more geological property values. The cells 202 may be arranged so that each cell location is at a coordinate index, for example, in a three-dimensional space. Each cell can be indexed by a coordinate system, such as Euclidean coordinates [i, j, k], which designate the geometric location of the cell and the geometric location of the corresponding property value. The subject technology organizes a geological model of an embodiment - for example, a grid array 200 - into respective tables of the geological property values represented by the model. Each index of the table can store a geological property value corresponding to a grid location of a respective grid matrix 200. In this regard, the subject technology can reform data realizations from a first form into a second form. according to a predetermined algorithm, and then compare the data from the embodiments while using their second form. In one or more implementations, the submitted technology algorithm reduces the geological model to a one-dimensional table according to the geometry of the model so that a distance between cells in corresponding tables can be easily calculated when each cell of the one-dimensional tables is compared. The grid matrix 200, given by way of example, shown has a volume of 50 * 50 * 50 cells. In one or more implementations, the algorithm of the subject technology may reform the data so that the index of a cell at coordinates [i, j, k] is translated to an index k * 50 * 50 + j * 50 + i in a one-dimensional table. Therefore, the exemplary cell 204, at, for example, cell location [0, 16, 4] becomes the 1800th element of the corresponding one-dimensional table. In one or more implementations, the Euclidean distance between a pair of embodiments can be calculated. Each embodiment can be reformed into a corresponding one-dimensional table with 50 * 50 * 50 elements, denoted Simj, where i is the third embodiment. According to an algorithm given by way of example, the distance between any two embodiments can be illustrated by: distance = Ec (Sim_i [c] - Simj [c]) 2, with c being the index of the cell (1) With a brief reference to FIGS. 1A and 1B, if each dark zone 10 indicates a porosity equal to 1 and empty cells indicate a porosity of 0, then the distance between the embodiment of FIG. 1A and the realization of FIG. Figure 1B may be a value of 24, although the respective porosities of each embodiment are both calculated to be 0.25 pu. Therefore, the exemplary algorithm indicates a real geometric difference between the two embodiments without a user having to visually compare them. Figure 3 shows a flow chart of an exemplary process for selecting geographic data achievements, according to various aspects of the subject technology. For purposes of explanation, the various blocks of the exemplary process 300 are described herein with reference to the three-dimensional grid matrix 200 of FIG. 2 and the data tables, given by way of example, represented in the exemplary user interface of FIG. 4. One or more of the blocks of the process 300 may be implemented, for example, by a computing device 406, including, for example, one or more In some implementations, one or more of the blocks may be implemented separately from other blocks and by one or more different processors or computing devices. In addition, for reasons of explanation, the blocks of the exemplary process 300 are described as occurring in series or linearly. However, multiple blocks of the exemplary process 300 may occur in parallel. In addition, the blocks of the exemplary process 300 should not be performed in the order shown and / or one or more of the blocks of the exemplary process 300 may not be performed. According to the exemplary process 300, multiple realizations of geographic data (e.g., virtual models) are organized in respective tables of geological property values, each geological property value corresponding to a geological property value. grid location of a respective realization of geological data (302). Each of the geographic data embodiments may be representative of a geological area of interest and may be a three-dimensional grid matrix 200 based on a result of a stochastic process to estimate actual geological conditions in the area. According to the foregoing description, each three-dimensional grid matrix 200 may be reformed and reduced to a one-dimensional table according to a predetermined algorithm. The table contains the geological location of the data and each element of the table can be mapped to a single cell indexed by, for example, the value of the coordinates of the cell (for example, [i, j, k]). In one or more implementations, after all the 15 realizations of data are reformed and reduced into tables, the tables are placed in a two-dimensional matrix. Each table may be represented by each respective column of the matrix and each row of the matrix may indicate a single cell of the prior three-dimensional grid matrix 200. A bidirectional hierarchical cluster analysis may be applied. The tables are grouped into two or more table groups based on a comparison of geometric locations of similar values within respective tables of geological property values (3-04). In this regard, the geometric location comparison may include, for example, determining a distance between geological property values in a first of the respective tables and geological property values in a second of the respective tables. Property values can be petrophysical properties such as porosity, permeability or total organic carbon. However, the subject technology is not limited to porosity, permeability or total organic carbon. Any property that can garnish cells of the three-dimensional grid matrix 200 can be used. The distance can be based on some or all of the geological property values in the corresponding tables. The distance between property values can be based on cell volumetric coordinates of the property values. For example, the distance can be a geometric distance or a distance in Euclidean space. According to various implementations of the subject technology, the total distance between any two realizations of any data can be illustrated by equation 1 previously described. In one or more implementations, respective degrees of similarity between respective tables of geological property values may be determined based on the previous comparison of property value locations. The degrees of similarity can be represented in a numeric form, such as a percentage, or by a virtual hierarchy. The number of table groups in which the geological property value tables are grouped can then be determined based, for example, on an application of a similarity threshold degree to the specified degrees of similarity between the tables. According to the description given below with respect to FIG. 4, the threshold can be set by a user via a user interface. In this regard, once the threshold is set, each group of tables may have tables that are determined to be similar to each other table according to a degree of similarity at or above the threshold. In some implementations, groupings of cells in respective tables of geological property values can be identified. For example, each row of cells that crosses the same index of all tables in a two-dimensional matrix can be compared to other rows / indices to identify cell row groupings across tables that have similar values. of geological property forming a whole. In this regard, respective degrees of similarity between cells at respective indexes of the geologically valuable value tables can be determined and a size of the clusters determined based on an application of a degree of degree similarity threshold. determined similarity between the cells. Once clusters are identified, they can be used by the previously described algorithm used to determine the similarity between tables. In this regard, the geometric similarity of cell clusters within the tables can be determined. The Euclidean distance between similar values of geological property in the respective tables can be determined, for example, on the basis of cell groupings of the tables instead of individual cell indices. For example, an algorithm may compare a first table with other tables by considering the location and / or size of a grouping of cells within the table and determining which of the other tables has groupings. located in a similar way. In addition, while examples of grouping tables are provided, other grouping algorithms may also be in conjunction with the subject technology. Such algorithms include hierarchical grouping algorithms including, for example, a single link, a complete link, and so on. [0034] Once the table groups are determined, the table groups are provided to a user interface (306). According to the description given below with respect to FIG. 4, the groups of tables can be presented for selection by a user in the user interface (for example, in a desktop application or a web page). Using the user interface, a geologist, engineer, or other user of the software can examine the table groups and select a sample data realization from one or more of the groups for purposes simulation in a geological simulator. The user can also use the user interface to make selections in order to better define the groups of determined tables. The bundling analysis of the submitted technology, further defined through the operation of the user interface, facilitates the initial determination as to the membership of the data realizations to each group so that it is not necessary. the user to perform the initial determination to differentiate the realizations from each other. In one or more implementations, the subject technology may also automatically select a sample data realization in each group of tables and provide it as a candidate selection. In this respect, the submitted technology can select the realization of data on the basis of predetermined criteria. For example, the selected table may be the first table in the group, the last table may be randomly selected or may be closest to the group average. One or more data embodiments corresponding to the groups of tables provided are provided to a geological model simulator, for example, 3034222 12 to simulate a flow of fluid within a geological area corresponding to the plurality of embodiments geographic data (308). In this regard, selected sample data implementations may be processed by a corresponding geological simulator. In one or more implementations, the software of the subject technology may function as an interface to the simulator so that, when selecting the sample data realizations, the selected sample realizations may be automatically sent. to the simulator by activating a command, for example, on the user interface. Many of the above described features of the exemplary process 300 and related features and applications may be implemented as a specified software process as a set of instructions recorded on a medium of the same. computer readable storage (also known as computer readable medium). When these instructions are executed by one or more processing units (for example, one or more processors, processor cores, or other processing units), they cause the processing unit (s) to perform the actions indicated in the instructions. Examples of computer readable media include, but are not limited to, CD-ROMs, flash drives, RAM chips, hard drives, EPROMs, and so on. The computer readable media do not include carrier waves or electrical signals transmitted wirelessly or through wired connections. [0038] Fig. 4 shows an exemplary user interface 402 for selecting geographic data realizations in a dynamic execution environment 404 on a computing device 406, according to one or more aspects of the subject technology. During operation of the computing device 406, executable instructions 408 are loaded into a runtime environment 404 and executed. Instructions 408, when executed, create a user interface 402 and may perform a number of operations on data provided to the display device in the user interface 402. Executable instructions 408 may include properties and / or their corresponding property values which may change in response to specific user-initiated navigation paths and / or to an input associated with the user interface 402. In one or more implementations, after all the geographic data realizations are reformed and reduced into tables, the tables are placed in a two-dimensional matrix 410 which can be displayed graphically in the user interface 402. The matrix tables 410 are represented by the respective columns 412 of the matrix while the rows 414 of the matrix can indicate individual cells s tables, each cell corresponding to a grid location of the prior three-dimensional grid matrix 200. The subject technology can also automatically arrange the tables so that similar tables are in close proximity to each other based on the clustering analysis. The exemplary matrix 410 of FIG. 5 is represented as a density map that shows the poolings of porosity simulations. Each cell represented by the density map can be a color coded on the basis of the value of the cell. For example, all the red cells displayed in the matrix 410 may have the same property value (or a similar value). Twenty-five realizations of data are represented in the user interface 402 as side-by-side cell structures (e.g., visually represented tables). Each of the exemplary geographic data implementations represented by the tables is visually labeled 416 in the user interface 402 as Sim_ / at Sirn25. It should be understood that many more achievements can be displayed or otherwise represented by the user interface. In the example shown, Sim_1 is represented by the first column of the matrix 410 with all the grid cells that are mapped to the different groups. The exemplary cell 204 of Fig. 1 is shown mapped to one row across all tables with, for example, the same property value at the same index in almost all the tables (represented, for example, , with the color red). A clustering analysis is performed on the columns (referred to as, for example, "R mode") to determine the similarity of different tables and, thus, of data realizations.
    [0005] The results of the analysis can be graphically represented using one or more hierarchical virtual trees 418 (for example, a dendrogram tree). According to the foregoing description, degrees of similarity can be determined between respective tables of geological property values based on the comparison of all the property values of the cells within the tables. In the example shown, the degrees of similarity between tables are visually represented by the tree 418, each leaf of the tree being representative of a respective table and the leaf branches being representative of similar tables. The exemplary tree 418 has multiple levels of branches, each branch representing a similarity between the branches and / or the leaves it contains etc., and the degree of similarity between leaves decreasing with each branch. next to the root of the tree. In certain implementations, a threshold indicator 420 can be moved up and down on the branches of the tree in order to visually adjust the degree of similarity threshold used to determine the tables that are grouped together in a set of parameters. groups of tables. In this manner, a user can visually move threshold flag 420 and the user interface can automatically assign tables to table groups based on the position of the flag in the tree. With the aid of the user interface 402 (and, for example, the threshold indicator 420), a geologist can select candidate realizations by following the hierarchies of the tree 418. At the top of the tree, Sim_1 is in a first grouping, the rest of the data realizations form a second grouping. Sim_1 can be selected as a candidate template. If it is necessary to choose another candidate, the user can traverse the tree 418 to the next level or branch of the tree. According to the foregoing description, a sample realization can be selected from a cluster formed using the clustering analysis of the submitted technology. In the example shown, Sim2 can be selected randomly as the second candidate in its grouping {Sim_2, Sim_20, Sim_17, Sim_5, Sim_21, Sim_23, Sim24, Sim25}. Similarly, Sim_3 can be selected as the third candidate in the third grouping shown. Sim3 and Sim4 are located at the same distance from the root of the tree 412 (for example, indicating that they are more similar to each other than other embodiments of other branches). In this case, once Sim_3 is chosen, Sim_4 can not be selected. The grouping of the rows (designated, for example, "Q mode") can determine groups of different cells within the tables. According to the foregoing description, the subject technology can identify the degree of similarity between geological property values in cell indices across, for example, all data realizations. Clusters of cells can then be identified in the tables based on the identified degrees of similarity between the cells. The tables can then be separated into groups of cells in close proximity to one another (for example, blocks of cells) based on a user-defined degree of similarity threshold. In this regard, a second hierarchical virtual tree 422 (for example, a dendrogram tree) may be displayed in the user interface 402, for example, to the right of the matrix 410. A second identifier 424 may be used from the same manner as previously described with respect to grouping tables to identify the size of the groups of cells. Once the cell groupings within the tables are identified, the groupings can be used by the algorithm described above, used to determine the similarity between tables. For example, the distance between similar values of geological property in the respective tables can be determined (for example, the Euclidean distance between coordinate indices), for example, based on the clusters instead of the individual cell clues. For example, an algorithm can compare a first table with other tables by considering the location and / or size of a grouping of cells within the table and determining other tables that have groupings of similar way. As a result, the user interface 402 provides a mechanism for applying a bidirectional hierarchical grouping analysis on a group of data realizations. The two types (e.g., R mode and Q mode) of the cluster analysis can be implemented in the technology submitted, for example, to evaluate both an intergroup of simulations and an intergroup of cells. A first type of grouping (for example, R mode grouping) can be used to determine and display the similarity of different data realizations (and thus, for example, corresponding simulations), and to organize data realizations into groups . On the other hand, a second grouping type (e.g., Q mode grouping) can be used to determine and display a grouping of different cells. FIG. 5 is a diagram illustrating an exemplary electronic system for use in conjunction with a process for selecting 5 realizations of geographic data, according to one or more aspects of the subject technology. The electronic system 500 may be a computing device for executing software associated with one or more parts or steps of the process 300. In various implementations, the electronic system 500 may be representative of the computing device 406 or any other kind of electronic device. The electronic system 500 may include various types of computer readable media and interfaces for various other types of computer readable media. In the example shown, the electronic system 500 comprises a bus 508, one or more processing units 512, a system memory 504, a read only memory (ROM) 510, a permanent storage device 502, a device interface of input 514, an output device interface 506 and one or more network interfaces 516. In some implementations, the electronic system 500 may include or be integrated with other computer devices or circuits to operate the various devices. components and processes previously described. The bus 508 collectively represents all the system buses, peripheral buses and chipset buses that communicatively connect the many internal devices of the electronic system 500. For example, the bus 508 communicatively connects the at least one unit. 512 to the ROM 510, the system memory 504 and the permanent storage device 502. From these various memory units, the processing unit (s) 512 retrieve instructions to be executed and data to be processed. process in order to perform the processes of the subject invention. The processing unit or units may be a single processor or a multicore processor according to the different implementations. The ROM 510 stores data and static instructions that are necessary for the processing unit (s) 512 and other modules of the electronic system. The permanent storage device 502, on the other hand, is a read-write memory device. This device is a nonvolatile memory unit which stores instructions and data even when the electronic system 500 is de-energized. Certain implementations of the subject invention utilize a mass storage device (such as a magnetic or optical disk and its corresponding disk drive) as a permanent storage device 502. 10052] Other implementations use a removable storage device (such as a floppy disk, a flash disk and their corresponding disk drive) as a permanent storage device 502. Like the permanent storage device 502, the system memory 504 is a read memory device -writing.
    [0006] However, unlike the storage device 502, the system memory 504 is a volatile read-write memory, such as a random access memory. System memory 504 stores some of the instructions and data that the processor needs at runtime. In some implementations, the processes of the subject invention are stored in the system memory 504, in the permanent storage device 502 and / or in the ROM 510. From these various memory units, the one or more units Processing 512 retrieves instructions to execute and data to be processed in order to execute the processes of certain implementations. [0053] The bus 508 also connects to the input and output device interfaces 514 and 506. The input device interface 514 allows the user to communicate information and select commands for the system. electronic. Input devices used with the input device interface 514 include, for example, alphanumeric keypads and pointing devices (also referred to as "slider control devices"). The output device interface 506 allows, for example, the display of images generated by the electronic system 500. Output devices used with the output device interface 506 include, for example, printers and display devices, such as cathode ray tube (CRT) devices or liquid crystal display (LCD) devices. Some implementations include devices such as a touch screen that operates both as an input device and an output device. Finally, as shown in FIG. 5, the bus 508 also couples the electronic system 500 to a network (not illustrated) via network interfaces 516. The network interfaces 516 may comprise, for example, a point 3034222 18 wireless access (for example, Bluetooth or WiFi). The network interfaces 516 may also include hardware (eg Ethernet hardware) for connecting to a computer part of a computer network such as a local area network ("LAN"), a WAN ("WAN") or an intranet or network of networks, such as the Internet. Some or all of the components of the electronic system 500 may be used in conjunction with the subject invention. These functions described above can be implemented by computer software, firmware or hardware. The techniques can be implemented using one or more computer program products.
    [0007] Programmable processors and computers may be included in mobile devices or formed as mobile devices. Logic processes and flows can be performed by one or more programmable processors and one or more programmable logic circuits. Computer devices and general purpose and special purpose storage devices may be interconnected through communication networks. Some implementations include electronic components, such as microprocessors, storage devices, and memories that store computer program instructions on a machine-readable medium or a computer-readable medium (alternatively designated as computer readable storage media, machine readable media or machine readable storage media). Some examples of such computer readable media include RAMs, ROMs, compact discs (CD-ROMs), recordable compact discs (CD-Rs), rewritable compact discs (CDRWs), digital versatile discs (for example, DVD-ROM, DVD-ROM 25 dual layer), a large number of recordable / rewritable DVDs (eg DVD-RAM, DVD-RW, DVD + RW etc.), flash memories (eg, SD cards, cards mini-SD, micro-SD cards, etc.), magnetic and / or electronic hard drives, Blu-Ray® discs and recordable Blu-Ray® discs, high-density optical discs, any other optical or magnetic media, and floppy disks. The computer readable media can store a computer program that is executable by at least one processing unit and includes instruction sets for performing various operations. Examples of computer programs or computer codes include machine codes, as they are produced by a compiler, and files with higher level code that are executed by a computer, an electronic component, or a microprocessor using an interpreter. While the discussion above refers mainly to microprocessors or multi-core processors that execute software, some implementations are performed by one or more integrated circuits, such as application-specific integrated circuits (ASICs). ) or programmable gate array integrated circuits (FPGAs). In some implementations, such integrated circuits execute instructions that are stored on the same circuit. [0058] To facilitate a better understanding of the present invention, the following examples of preferred or representative embodiments will be described below. In no case should the following examples be considered to limit or define the scope of the invention. Embodiments presented herein include: A. A method for selecting realizations of geographic data, comprising: organizing a plurality of geographic data realizations into respective tables of geological property values each geological property value corresponding to a grid location of a respective realization of geological data; grouping the tables into two groups of 20 or more tables based on a comparison of geometric locations of similar values within the respective tables of geological property values; and providing the two or more table groups to a user interface. Other aspects include corresponding computer systems, apparatuses and computer program products for implementing the computer implemented method. B. A system, comprising one or more processors and a memory. The memory includes instructions which, when executed by the one or more processors, cause the processor (s) to facilitate the steps of: organizing a plurality of spatial data realizations into respective tables of geological property values, each geological property value corresponding to a grid location of a respective realization of geological data; grouping tables into two or more table groups based on a comparison of geometric locations of values similar to within the respective tables of geological property values; and providing the two or more groups of tables to a user interface. Other aspects include corresponding computer systems, apparatus, and computer program products for implementing the computer implemented method.
    [0008] Other aspects include corresponding methods, apparatus and computer program products for implementing the computer implemented method. C. A computer program product made manifestly in a computer readable storage device and including instructions which, when executed by a computing device, cause the computing device to: organize a plurality of embodiments three-dimensional geographic data in respective one-dimensional tables of geological property values, each geological property value corresponding to a three-dimensional grid location of a respective three-dimensional realization of geological data; grouping the one-dimensional tables into two or more table collections based on a comparison of geometric locations of the geological property values within the respective tables; selecting at least one of the plurality of three-dimensional realizations of geographic data for each of the two or more table pools; and provide the selected 20 realizations of data to a user interface. Other aspects include methods, apparatus, and systems for implementing the computer-implemented computer program product. Each of Embodiments A, B and C may have one or more of the following additional elements in any combination: [0064] Element 1: further comprising providing one or more data realizations corresponding to the two or more groups of tables provided to a geological model simulator for simulating a flow of fluid within a geological area corresponding to the plurality of geographic data realizations. Element 2: further comprising automatically selecting one data realization for each of the table groups. Element 3: wherein the geometric location comparison comprises determining the distance between a first geological property value in a first of the respective geological property value tables and a second geological property value in a second of the respective geological property tables. geological property values. Element 4: wherein the distance is based on cell volumetric coordinates of the first and second geological property values. Element 5: in which the distance is a Euclidean distance. Element 6: 5 further comprising determining respective degrees of similarity between respective tables of geological property values based on geometric location comparison, and determining the number of table groups in which the property value tables. are grouped based on an application of a degree of similarity threshold to the respective respective degrees of similarity between the respective tables. Element 7 further comprising determining respective degrees of similarity between cells at respective indices of the respective tables based on a comparison of the geological property values with the respective indices, and determining cell clusters in the respective tables. on the basis of the respective determined degrees of similarity and a degree of similarity threshold. Element 8: wherein the grouping of tables in two or more table groups based on the comparison of geometric locations of similar values includes determining a geometric similarity of cell clusters within the respective tables of values of values. geological property. Element 9: wherein each of the plurality of spatial data embodiments is based on a result of a stochastic process. Therefore, the systems and methods presented are well suited to achieve the stated objectives and advantages as well as those inherent therein. The particular embodiments presented above are illustrative only, since the teachings of the present invention may be modified and practiced in different but equivalent ways, obvious to those skilled in the art from the teachings described. right here. Furthermore, no limitations are desired as to the details of construction or design shown herein other than those described in the claims hereinafter. It is therefore apparent that the particular illustrative embodiments set forth above may be altered, combined or modified and such variations are considered to remain within the scope of the present invention. The systems and methods, given by way of illustration, presented herein may be conveniently implemented in the absence of any element not specifically presented herein and / or any optional element presented here. Although compositions and methods have been described with the terms "comprising", "containing" or "comprising" various components or steps, the compositions and methods may also be "essentially constituted" or "made up" of the various components and steps. All numbers and ranges presented above may vary in any amount. Whenever a numeric range having a lower limit and an upper limit is presented, any number and range within said range is specifically presented. In particular, each range of values (of the form, "from about a to about b" or, equivalently, "from approximately a to b" or, equivalently, "from approximately ab") presented herein must be understood to expose each number and range encompassed within a wider range of values. Likewise, the terms in the claims have their overt, ordinary meaning unless otherwise stated and clearly defined by the applicant. On the other hand, the undefined articles "a" or "an", as used in the claims, are defined herein to mean an element or more than one of the elements they introduce. If there is a conflict regarding the use of a word or term in this specification and in one or more patents or other documents that may be incorporated herein by reference, then we should adopt definitions that are consistent with this specification. 10066] As used herein, the expression "at least one of" preceding a series of articles, with the words "and" or "or" to separate any of the articles, modifies the list in in its entirety, rather than each member of the list (i.e., each article) .The phrase "at least one of" permits a meaning that includes any of the articles and / or any combinations of the articles, and / or one of each of the articles By way of example, the phrases "at least one of A, B and C" or "at least one of A, B or C" refer to each of only A, only B or only C, any combination of A, B and C, and / or at least one of each A, B and C. 10067] As used in this specification and in claims of this application, the terms "computer", "server", "processor" and "memory" all refer to electronic devices or 3034222 23 other technological devices. These terms exclude individuals or groups of people. For the purposes of the specification, the terms "display" or "display means" mean the display on an electronic device. As used in this specification and in claims of this application, the terms "computer readable medium" and "computer readable media" are entirely restricted to tangible, physical objects which store information in a form which is readable by a computer. These terms exclude any wireless signals, wireless download signals, and other ephemeral signals. In order to provide interaction with a user, implementations of the content described in this specification may be implemented on a computer having a display device, for example a cathode ray tube (CRT) monitor or a liquid crystal monitor. (LCD), for displaying information to the user, and a keyboard and pointing device, for example, a mouse or a trackball, whereby the user can provide input to the computer. Other types of devices may also be used to provide interaction with a user; for example, feedback provided to the user may be any form of feedback from a sensor system, for example, visual feedback, auditory feedback or tactile feedback; and a user input may be received in any form, including an acoustic, voice or tactile input. In addition, a computer may interact with a user by sending documents to a device and receiving documents from the device that is being used by the user; for example, sending web pages to a web browser on a user's client device in response to requests received from the web browser. Embodiments of the content described in this specification can be implemented in a computer system that includes a main component, for example, as a data server, or that includes a mediating component, for example, a server or a front-end component, for example, a client computer having a graphical user interface or a web browser through which a user can interact with an implementation of the content described in this specification, or any combination thereof. one or more components such as a main component, mediator or front end. The system components may be interconnected by any form or any means of digital data communication, for example, a communication network. Examples of communication networks include a local area network ("LAN") and a wide area network ("WAN"), an inter-network (for example, the Internet) and peer-to-peer networks (eg ad hoc peer-to-peer networks). The computer system may include clients and servers. A client and a server are generally remote from one another and typically interact through a communication network. The client and server relationship occurs because of computer programs running on the respective computers and having a client-server relationship between them. In some embodiments, a server transmits data (e.g., an HTML page) to a client device (e.g. for purposes of displaying data to a user and receiving user input from a user). user interacting with the client device). Data generated in the client device (e.g., a result of user interaction) may be received from the client device in the server from the client device. Those skilled in the art will appreciate that the various blocks, modules, elements, components, methods, and illustrative algorithms described herein can be implemented as electronic hardware, computer software, or combinations of both. To illustrate this interchangeability of hardware and software, various illustrative blocks, modules, elements, components, methods, and algorithms have been described above generally with respect to their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design constraints imposed on the entire system. Those skilled in the art can implement the described functionality in a variety of ways for each particular application. Various components and blocks may be arranged differently (for example, arranged in a different order or partitioned in a different manner), all without departing from the scope of the subject technology. It should be understood that the specific order or hierarchy of steps in the presented processes is an illustration of exemplary approaches. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the processes can be re-arranged.
    [0009] Some of the steps can be performed simultaneously. The appended process claims have elements of the various steps in an exemplary order and are not limited to the specific order or hierarchy presented. The foregoing description is provided to enable those skilled in the art to practice the various aspects described herein. The foregoing description provides various examples of the subject technology and the subject technology is not limited to these examples. Various modifications applied to these aspects will become readily apparent to those skilled in the art and the generic principles defined herein can be applied to other aspects. Thus, the claims do not intend to limit the aspects shown herein, but must be granted in a scope consistent with the language claims, a reference to a singular element not being made with intent to mean "one and only one", unless otherwise specifically indicated, but rather "one or more". Unless specifically indicated otherwise, the term "some" refers to one or more. Of the 15 masculine pronouns (eg, sound) include the feminine gender (eg, sa) and vice versa. Headings and sub-titles, if any, are used for convenience only and do not limit the claims. [0074] An expression such as "aspect" does not imply that such an aspect is essential to the subject technology or that such an aspect applies to all the configurations of the subject technology. An aspect of an aspect may apply to all configurations or one or more configurations. One aspect may provide one or more examples. An expression such as appearance can refer to one or more aspects and vice versa. An expression such as "embodiment" does not imply that such an embodiment is essential to the subject technology or that such an embodiment applies to all configurations of the subject technology. An embodiment disclosure may apply to all embodiments or to one or more embodiments. One embodiment may provide one or more examples. An expression such as "embodiment" may refer to one or more embodiments and vice versa. An expression such as "configuration" does not imply that such a configuration is essential to the subject technology or that such a configuration applies to all configurations of the subject technology. A configuration statement may apply to all configurations or 3034222 26 to one or more configurations. A configuration can provide one or more examples. An expression such as "configuration" can refer to one or more configurations and vice versa. The word "example" is used here to mean "serving as an example 5 or illustration". Any aspect or design described here as an "example" need not be considered a preferred or advantageous aspect or design over other aspects or designs.
    权利要求:
    Claims (20)
    [0001]
    REVENDICATIONS1. A method of selecting realizations of geographic data, comprising: organizing a plurality of spatial data realizations into respective tables of geological property values, each geological property value corresponding to a grid location of a respective realization of geological data; grouping tables into two or more table groups based on a comparison of geometric locations of similar values within respective tables of geological property values; and providing the two or more table groups to a user interface.
    [0002]
    The method of claim 1, further comprising: providing one or more data outputs, corresponding to the two or more table groups provided, to a geological model simulator to simulate a fluid flow at the within a geological area corresponding to the plurality of geographic data realizations.
    [0003]
    The method of claim 1, further comprising: automatically selecting one data realization for each of the table groups.
    [0004]
    The method of claim 1, wherein the geometric location comparison comprises: determining the distance between a first geological property value in a first of the respective tables of geological property values and a second geological property value in a second respective tables of geological property values. 30
    [0005]
    The method of claim 4, wherein the distance is based on volumetric cell coordinates of the first and second geological property values. 3034222 28
    [0006]
    The method of claim 4, wherein the distance is a Euclidean distance.
    [0007]
    The method of claim 1, further comprising: determining respective degrees of similarity between respective tables of geological property values based on the geometric location comparison, and determining the number of table groups in which the geological property value tables are grouped on the basis of an application of a similarity threshold degree to the respective respective degrees of similarity between the respective tables.
    [0008]
    The method of claim 1, further comprising: determining respective degrees of similarity between cells at respective indices of the respective tables based on a comparison of geological property values with the respective indices; and determining cell clusters in the respective tables based on the respective determined degrees of similarity and a degree of similarity threshold.
    [0009]
    The method of claim 8, wherein the grouping of tables into two or more table groups based on the comparison of geometric locations of similar values comprises: determining a geometric similarity of cell clusters to the within the respective tables of geological property values.
    [0010]
    The method of claim 1, wherein each of the plurality of spatial data embodiments is based on a result of a stochastic process.
    [0011]
    11. System, comprising: one or more processors; and a memory having instructions which, when executed by the one or more processors, cause the processor (s) to facilitate the steps of: organizing a plurality of realizations of geographic data into respective tables of property values geological, each geological property value corresponding to a grid location of a respective realization of geological data; grouping tables into two or more table groups based on a comparison of geometric locations of similar values within respective tables of geological property values; and providing the two or more groups of tables to a user interface. 10
    [0012]
    The system of claim 11, wherein the instructions, when executed, further causes the processor (s) to facilitate the step of: providing one or more data realizations corresponding to the two groups of tables or more provided, to a geological model simulator for simulating a flow of fluid within a geological area corresponding to the plurality of geographic data realizations.
    [0013]
    The system of claim 11, wherein the instructions, when executed, further causes the processor (s) to facilitate the step of: automatically selecting one data realization for each of the table groups.
    [0014]
    The system of claim 11, wherein the geometric location comparison comprises: determining the distance between a first geological property value in a first of the respective tables of geological property values and a second geological property value in a second respective tables of geological property values.
    [0015]
    The system of claim 14, wherein the distance is based on volumetric cell coordinates of the first and second geological property values. 3034222 30
    [0016]
    The system of claim 14, wherein the distance is a Euclidean distance,
    [0017]
    The system of claim 11, wherein the instructions, when executed, further causes the processor (s) to facilitate the steps of: determining respective degrees of similarity between respective tables of geological property values on the basis of the geometric location comparison, and determining the number of table groups in which the geological property value tables are grouped based on an application of a similarity threshold degree to the respective respective degrees of similarity between the respective tables.
    [0018]
    The system of claim 11, wherein the instructions, when executed, further causes the processor (s) to facilitate the steps of: determining respective degrees of similarity between cells at respective indices of the respective tables on the basis of a comparison of geological property values with the respective indices; and determining cell clusters in the respective tables based on the respective 20 degrees of similarity of similarity and a degree of similarity threshold.
    [0019]
    The system of claim 18, wherein the grouping of tables into two or more table groups based on the comparison of geometric locations of similar values comprises: determining a geometric similarity of cell clusters at the same time; within the respective tables of geological property values.
    [0020]
    20. A computer program product tangibly embodied in a computer readable storage device and including instructions which, when executed by a computing device, cause the computing device to: organize a plurality of three-dimensional realizations of geographic data in respective one-dimensional tables of geological property values, each geological property value corresponding to a three-dimensional grid location of a respective three-dimensional realization of geological data; grouping the one-dimensional tables into two or more table groups based on a geometric location comparison of the geological property values within the respective tables; selecting at least one of the plurality of three-dimensional realizations of geographic data for each of the two or more table pools; and provide selected data realizations to a user interface. 10
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    PCT/US2015/022134|WO2016153482A1|2015-03-24|2015-03-24|Cluster analysis for selecting reservoir models from multiple geological realizations|
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