Method and device for evaluating influence of reservoir heterogeneous description scale on numerical simulation

Abstract

The invention discloses a method and a device for evaluating the influence of a heterogeneous description scale of a reservoir on numerical simulation. The method comprises the following steps: acquiring geological data of a plurality of heterogeneous description scales of a target block; for each scale, acquiring a plurality of geological maps drawn by a user by taking the geological data of the scale as a background, establishing a three-dimensional geological model, and performing attribute assignment; according to a set production well pattern, based on the three-dimensional geologic model after attribute assignment, obtaining a numerical simulation result corresponding to each set grid size; and screening the scale and the grid size meeting the requirements of the numerical simulation result and the numerical simulation time as the heterogeneous description scale and the grid size required by the numerical simulation of the research area where the target block is located. According to the method, geological models of different heterogeneous description scales of a typical target block are established based on man-machine interaction, numerical simulation calculation is performed according to the sizes of a plurality of grids, so that the most appropriate grid size and geological information needing to be reserved are determined, and modeling of a whole research area is effectively guided.

Description

Technical Field

[0001] The present invention relates to the technical field of geological modeling and numerical simulation calculation, and in particular to a method and device for evaluating the influence of reservoir heterogeneity description scale on numerical simulation. Background Art

[0002] Three-dimensional reservoir geological modeling provides a high-level overview of reservoir characterization research results, including reservoir type, geometry, size, fluid properties, and spatial distribution characteristics. It also quantitatively describes the changes in various reservoir geological characteristics in three dimensions. Since the 1960s, reservoir geological modeling has undergone three stages: initial understanding, rapid development, and mature understanding. A comprehensive set of theoretical methods and technical means has gradually emerged: guided by the theories of petroleum geology, structural geology, geostatistics, geophysics, reservoir engineering, and fractals, multidisciplinary and multi-disciplinary research is conducted on the basis of single-disciplinary research. The method integrates geological, seismic, well logging, and production dynamic data, guided by development geological theory, and using computers to apply deterministic and stochastic modeling techniques to conduct multidisciplinary integrated research on reservoir structure, sedimentation, stratigraphic sequence, fractures, reservoir parameters, and reservoir heterogeneity, thereby establishing a detailed three-dimensional geological model.

[0003] As is well known, the accuracy of geological information is gradually lost in the process of coarsening from well logging interpretation to geological models and then to numerical models. This is especially true when importing geological models into numerical simulation software for simulation. Due to computational time constraints, significant mesh coarsening is often performed. Parameters such as porosity and permeability in the original mesh are averaged across a larger mesh, reducing heterogeneity.

[0004] While the loss of geological information due to scale changes in the process from petrophysical log interpretation to static geological models and finally to the final numerical model grid is inevitable, optimization can be performed to maximize geological information retention, ultimately achieving a balance between computational efficiency and model representativeness. The question of how much geological information should be retained in the model to more reliably assess key metrics (such as recovery factor and sweep efficiency) is a crucial question for geological modelers and numerical simulation practitioners. Answering this question requires discussion in three areas: 1) How to effectively characterize different levels of heterogeneity during the geological modeling phase; 2) How to effectively retain geological information during the process from log interpretation to geological modeling and then to numerical simulation; and 3) How to effectively test the impact of varying levels of geological information on key metrics such as water cut and recovery factor through numerical simulation. Within the conventional workflow using mature commercial software, these questions can be investigated by establishing a closed-loop process. The process involves well logging interpreters submitting interpreted physical property parameters to geological modelers, who then submit their established geological models to numerical simulation personnel. If the numerical simulation personnel identify any issues through history matching, the modelers return the results to the geological modelers for debugging until a satisfactory numerical simulation result is achieved. However, this closed-loop model is time-consuming and labor-intensive. Summary of the Invention

[0005] The inventors discovered that in conventional geological modeling processes running in mature commercial software such as Petrel, the characterization of reservoir heterogeneity is largely limited by the statistical laws of well data, lacking the flexibility of human-computer interaction. The resulting models often differ from sedimentological models imagined by sedimentologists, resulting in insufficient geological conceptualization. Taking carbonate reservoirs as an example, they exhibit heterogeneity at varying scales, ranging from centimeter-scale bioburrows to kilometer-scale fractures and caves. Conventional modeling software modules struggle to simultaneously and effectively characterize these heterogeneities. Furthermore, the geological modeling and numerical simulation modules are highly specialized, operated by geological modelers and numerical simulation engineers, respectively. The stratigraphic framework and grid size must be determined in the initial stages of geological modeling. If the grid is found to be insufficiently accurate or too fine during later numerical simulations and requires adjustments, the initial stages of geological modeling must be revisited. This requires frequent back-and-forth between geological modelers, numerical simulation engineers, and even well logging interpreters, resulting in a significant waste of time and effort.

[0006] In order to at least partially solve the technical problems existing in the prior art, the inventors have made the present invention. Through specific implementation methods, they provide a method and device for evaluating the impact of reservoir heterogeneity description scale on numerical simulation, which can quickly determine the most appropriate grid size for reservoir modeling and the scale of geological information that needs to be retained.

[0007] In a first aspect, an embodiment of the present invention provides a method for evaluating the impact of reservoir heterogeneity description scale on numerical simulation, comprising:

[0008] Obtain geological data of multiple heterogeneous description scales for the target block;

[0009] For each scale, multiple geological maps drawn by the user using the geological data of that scale as the background are obtained, and a three-dimensional geological model is established based on the multiple geological maps, and attribute values ​​are assigned; according to the set production well pattern, the numerical simulation results corresponding to each set grid size are obtained based on the three-dimensional geological model after attribute assignment;

[0010] The numerical simulation results and numerical simulation time that meet the required scale and grid size are screened as the heterogeneous description scale and grid size required for the numerical simulation of the study area where the target block is located.

[0011] In a second aspect, an embodiment of the present invention provides a device for evaluating the impact of reservoir heterogeneity description scale on numerical simulation, comprising:

[0012] A geological data acquisition module is used to obtain geological data of multiple heterogeneous description scales of the target block;

[0013] The geological modeling module is used to obtain, for each scale, multiple geological maps drawn by the user using the geological data of that scale as the background, establish a three-dimensional geological model based on the multiple geological maps, and perform attribute assignment;

[0014] The numerical simulation module is used to obtain the numerical simulation results corresponding to each set grid size based on the set production well pattern and the three-dimensional geological model after attribute assignment;

[0015] The scale and grid size screening module is used to screen the scale and grid size that meet the requirements of numerical simulation results and numerical simulation time, as the heterogeneous description scale and grid size required for numerical simulation of the study area where the target block is located.

[0016] In a third aspect, an embodiment of the present invention provides a computer storage medium storing computer executable instructions, which, when executed by a processor, implements the above-mentioned method for evaluating the influence of reservoir heterogeneity description scale on numerical simulation.

[0017] In a fourth aspect, an embodiment of the present disclosure provides a server comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for evaluating the influence of the reservoir heterogeneity description scale on the numerical simulation is implemented.

[0018] The beneficial effects of the above technical solutions provided by the embodiments of the present invention include at least:

[0019] An embodiment of the present invention provides a method for evaluating the impact of reservoir heterogeneity description scales on numerical simulations, which obtains geological data of a target block at multiple heterogeneity description scales; for each scale, obtains multiple geological maps drawn by a user with the geological data of that scale as a background, establishes a three-dimensional geological model through human-computer interaction, and assigns attributes; according to a set production well pattern, obtains numerical simulation results corresponding to each set grid size based on the three-dimensional geological model after attribute assignment; and screens the scales and grid sizes that meet the requirements of numerical simulation results and numerical simulation time, and uses them as the heterogeneity description scales and grid sizes required for numerical simulation in the study area where the target block is located. The establishment of a human-computer interactive geological model uses surface-based reservoir modeling to convert geological heterogeneity into a series of surfaces of different scales and the geological bodies between them. This means that the geological model does not contain a grid. The grid is only generated in the initial stage of numerical simulation for subsequent calculations. This is different from the workflow of conventional modeling software that fixes the grid size at the beginning of the geological model. The method of this embodiment can set and change the grid size after the geological model is established, and then conduct numerical simulation tests in the same software to observe the impact of geological information of different scales on numerical simulation predictions, greatly saving the inefficient back-and-forth work time between traditional geological modeling engineers and numerical simulation engineers. Through this embodiment, the geological modeling engineer can independently complete the tasks such as model establishment, grid size setting, and numerical simulation testing, eliminating the most time-consuming grid changes and numerical simulation tests in the conventional workflow, and improving the efficiency of work that originally took several days to a few hours.

[0020] The embodiment of the present invention provides a method for evaluating the impact of reservoir heterogeneity description scale on numerical simulation. Human-computer interactive geological modeling greatly utilizes the human control of the modeler. Compared with conventional methods, the model can include heterogeneity information at various scales through drawing, which is closer to the actual underground property changes under the control of geological concepts.

[0021] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0022] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0024] Figure 1This is a flow chart of a method for evaluating the impact of reservoir heterogeneity description scale on numerical simulation in Example 1 of the present invention;

[0025] Figure 2 This is a flowchart of a specific implementation of a method for evaluating the impact of reservoir heterogeneity description scale on numerical simulation in Example 2 of the present invention;

[0026] Figure 3 The histogram of the study area and the schematic diagram of the selected target horizon in the second embodiment of the present invention;

[0027] Figure 4 Preliminary data preparation for reservoir heterogeneity at different scales in the geological model of the second embodiment of the present invention;

[0028] Figure 5 The three-dimensional geological bodies are the surfaces of different scales drawn in the geological modeling process of the second embodiment of the present invention and the surfaces and surfaces formed by the surfaces;

[0029] Figure 6 A geological model and a two-dimensional / three-dimensional internal configuration including heterogeneity at different scales according to an embodiment of the present invention;

[0030] Figure 7 The geological information of different grid sizes according to an embodiment of the present invention is as follows;

[0031] Figure 8 Attribute assignment of a geological model and numerical simulation under one injection and one production process according to an embodiment of the present invention;

[0032] Figure 9 Comparison of key numerical simulation parameters for heterogeneous geological models of different scales and different grid sizes according to an embodiment of the present invention;

[0033] Figure 10 Schematic diagram of the structure of the evaluation device for the influence of reservoir heterogeneity description scale on numerical simulation in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0035] It should be understood that the terms described herein are intended only to describe particular embodiments and are not intended to limit the present invention. In addition, for numerical ranges herein, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Each smaller range between any intermediate value within a stated value or stated range and any other stated value or intermediate value within the stated range is also encompassed by the present invention. The upper and lower limits of these smaller ranges may be independently included or excluded within the scope.

[0036] Unless otherwise indicated, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the invention belongs. Although the present invention describes only preferred methods and materials, any methods and materials similar or equivalent to those described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods and / or materials related to the documents. In the event of any conflict with any incorporated document, the content of this specification shall prevail.

[0037] Example 1

[0038] The first embodiment of the present invention provides a method for evaluating the impact of reservoir heterogeneity description scale on numerical simulation, the process of which is as follows: Figure 1 As shown, the following steps are included:

[0039] Step S11: Acquire geological data of multiple heterogeneous description scales of the target block.

[0040] The optimization of target blocks in the study area can be to select representative blocks with rich development of heterogeneous bodies at all levels in the study area. The block range should not be too large, as too large will increase the complexity of the research and the amount of calculation.

[0041] Furthermore, geological data of at least the following heterogeneity description scales are obtained for the target block:

[0042] First, geological data, including sedimentary facies description data;

[0043] second geological data, including first lithologic level description data;

[0044] The third geological data includes second lithology-level description data that is more detailed than the first lithology-level description data.

[0045] Optionally, according to the actual geological conditions in the study area and specific research needs, geological data of more scales may be obtained, such as fourth geological data, including third lithologic level description data that is finer than second lithologic level description data.

[0046] At the same time, the second geological data may also include first typical geological body description data that matches the scale of the first lithology level description data; the third geological data may also include second typical geological body description data that matches the scale of the second lithology level description data.

[0047] The typical geological bodies here are those with matching scales, as distinguished from laterally larger, layered lithologies. For example, in carbonate reservoirs, these could be massive stromatolites developed near granular limestone bodies or karst caves of a certain size. The first and second typical geological bodies can be of the same type at different scales, or they can be of different types.

[0048] Step S12: For each scale, obtain multiple geological maps drawn by the user with the geological data of that scale as the background, establish a three-dimensional geological model based on the multiple geological maps, and assign attributes; according to the set production well network, based on the three-dimensional geological model after attribute assignment, obtain the numerical simulation results corresponding to each set grid size.

[0049] The geological data obtained in step S11 can be multiple geological maps or digital data. Ultimately, they are presented to the user (geological modeler) in the form of images in the geological map drawing interface for reference when drawing the geological map. Through human-computer interaction, multiple cross-sectional geological maps and XY-plane geological maps drawn by the user using the geological data at the current scale as the background are obtained. The cross-sectional geological maps are drawn in the order of deposition from the earliest to the latest.

[0050] Based on multiple geological maps, a three-dimensional geological model is established through a set interpolation method, and attributes are assigned to the established geological model.

[0051] Specifically, if the geological data corresponding to the three-dimensional geological model is the first geological data, the same average attribute value is assigned to the same sedimentary facies; if the geological data corresponding to the three-dimensional geological model is the second geological data or the third geological data, the same average attribute value is assigned to the same lithology.

[0052] The attribute assignment here can be the assignment of porosity and permeability.

[0053] Based on the three-dimensional geological model after attribute assignment and the numerical simulation calculation of the steady-state flow field, the numerical simulation results corresponding to each set grid size are obtained, including the simulation results of at least one parameter among the recovery factor, cumulative oil production and sweep efficiency.

[0054] Step S13: Filter the numerical simulation results and numerical simulation time that meet the required scale and grid size, and use them as the heterogeneous description scale and grid size required for the numerical simulation of the study area where the target block is located.

[0055] According to the numerical simulation results of multiple grid sizes of each scale geological model, based on the research accuracy requirements and time requirements, the heterogeneous description scale and grid size required for numerical simulation suitable for the study area are determined.

[0056] A method for evaluating the influence of reservoir heterogeneity description scale on numerical simulation provided in Example 1 of the present invention obtains geological data of multiple heterogeneity description scales of a target block; for each scale, obtains multiple geological maps drawn by a user with the geological data of that scale as a background, establishes a three-dimensional geological model through human-computer interaction, and assigns attributes; according to a set production well network, obtains numerical simulation results corresponding to each set grid size based on the three-dimensional geological model after attribute assignment; and screens the scales and grid sizes whose numerical simulation results and numerical simulation times meet the requirements as the heterogeneity description scales and grid sizes required for numerical simulation of the study area where the target block is located. The establishment of a human-computer interactive geological model uses surface-based reservoir modeling to convert geological heterogeneity into a series of surfaces of different scales and the geological bodies between them. This means that the geological model does not contain a grid. The grid is only generated in the initial stage of numerical simulation for subsequent calculations. This is different from the workflow of conventional modeling software that fixes the grid size at the beginning of the geological model. The method of this embodiment can set and change the grid size after the geological model is established, and then conduct numerical simulation tests in the same software to observe the impact of geological information of different scales on numerical simulation predictions, greatly saving the inefficient back-and-forth work time between traditional geological modeling engineers and numerical simulation engineers. Through this embodiment, the geological modeling engineer can independently complete the tasks such as model establishment, grid size setting, and numerical simulation testing, eliminating the most time-consuming grid changes and numerical simulation tests in the conventional workflow, and improving the efficiency of work that originally took several days to a few hours.

[0057] The method for evaluating the influence of reservoir heterogeneity description scale on numerical simulation provided in Example 1 of the present invention is a human-computer interactive geological modeling method that greatly utilizes the human control of the modeler. Compared with conventional methods, the model can include heterogeneity information at various scales through drawing, which is closer to the actual underground property changes under the control of geological concepts.

[0058] Example 2

[0059] The second embodiment of the present invention provides a specific application of a method for evaluating the impact of reservoir heterogeneity description scale on numerical simulation. Taking the xx stratigraphic group as an example, scholars have published a large number of studies on its sequence stratigraphy, lithofacies associations, reservoir geometry and structure, rock fabric and thin section characteristics. The Khuff Formation is a typical case of carbonate slope deposition, with supratidal and subtidal dolomite, limestone and a large number of beach facies complexes. The upper Khuff is the application object of this embodiment due to its rich sedimentary patterns and relevant published data. See. Figure 2As shown in Figure 2, the evaluation of the impact of reservoir heterogeneity description scale on numerical simulation includes the following steps:

[0060] Step S21: Preparation of geological model data based on well data such as cores and well logging data and outcrop data.

[0061] Considering the representativeness of the developmental lithofacies and the operating efficiency of the geological modeling software, the upper Khuff ( Figure 3 The target (in the Target) was used as the application target, covering four fifth-order cycles and a variety of lithologies and sedimentary facies, from grainstone to micritic limestone. The Upper Khuff Formation exhibits rich heterogeneity, ranging from kilometer-scale layered foreshore sediments to hundred-meter-scale high-permeability grainstone tongues, and finally to centimeter-scale bioburrows and boreholes. This information was summarized and designed into three sedimentary models, specifically characterizing reservoir characteristics at the kilometer, hundred-meter, and meter-centimeter scales, with increasing heterogeneity. The three models maintained consistent sizes: 1 km, 1 km, and 50 m in the X, Y, and Z directions, respectively.

[0062] See also Figure 4 The following table shows the preliminary data preparation for the reservoir heterogeneity of the three models. Model 1 considers two types of sedimentary facies, the beach facies and the foreshore facies, with lateral and vertical variations at the level of hundreds of meters and tens of meters, respectively. The main architectural feature is the frequent interbedding of the beach facies and the foreshore facies due to the changes of marine transgression and regression. Compared with Model 1, Model 2 is more refined in the Z direction, reaching the meter level, and is basically consistent in the XY direction. The geological body classification reaches the lithological level. The beach facies is further subdivided, mainly consisting of well-sorted oolitic limestone 1 and oolitic / spherulitic limestone 2 (see Figure 4 The foreshore facies is further subdivided into pelitic limestone 3 and pelitic-micrite limestone 4 (see Figure 4 Model 3 further adds two geological bodies, depicting the decimeter-meter-scale massive stromatolites 5 that are widely developed near the granular limestone body. The granular mud-mircrystal limestone 4 is further divided into granular mudstone 6 and micritic limestone 7. At the same time, the changes between lithologies are more frequent, such as the frequent interbedding between mud-grained limestone 3 and granular mudstone 6, see Figure 4 Enlarged view of the 3-1 and 3-2 bodies. The heterogeneity accuracy in the model is improved to the decimeter level in the vertical direction and to the 10m level in the horizontal direction. In summary, Figure 4 The increasing heterogeneity from Model 1 to Model 3 in the cross-sectional view is shown, and the horizontal and vertical scales are given to provide a reference for the subsequent interactive geological modeling. Table 1 shows the geological bodies depicted by different models and their corresponding relationships.

[0063] Table 1 Geological bodies of different models and their corresponding relationships

[0064]

[0065] Step S22: Using the PRM geological modeling module, a plurality of geological models including structural styles and sedimentary configurations of different scales are drawn in a human-computer interaction manner.

[0066] First, import the 2D sedimentary configuration maps of different scales from S21 into the geological modeling module as the drawing background. Draw the interface in the XZ and XY view windows from bottom to top according to the deposition order. When drawing the interface, it is necessary to consider the contact relationship between each other, the vertical and horizontal scales and other specific parameters. Figure 5 The figure shows the surfaces of different scales drawn during the geological modeling process (top and bottom right) and the three-dimensional geological body formed by the surfaces (bottom left). After the interface drawing is completed, the geological body is uniformly generated between the interfaces. Repeat the above steps to build three geological models. Model 3 takes the longest time because it contains the most geological information. The model built in this way reflects the sedimentary structure and the contact relationship between them under the guidance of geologists to the greatest extent, and can also better reflect the heterogeneity down to the centimeter-decimeter level. See Figure 6 Shown are geological models including heterogeneity at different scales and 2D / 3D internal configurations.

[0067] Step S23: assigning attributes according to the geological bodies in the multiple models, and setting different grid sizes for the multiple models.

[0068] First, assign attributes to each geological body in the three models established by S22. Different sedimentary facies / rock types have different physical properties. Based on the statistics of core and logging data, the same type of sedimentary facies / lithology is assigned average porosity and permeability values. Secondly, different grid sizes are set for these three models for the next step of numerical simulation. Taking model 3 as an example, the results of the four grid sizes of 10*10*20, 20*20*80, 40*40*100 and 100*100*300 are as follows: Figure 7 Naturally, the finer the grid, the better the geological information is preserved.

[0069] Step S24: By performing calculations and comparing the changing patterns of key parameters such as the recovery factor, the appropriate geological model and grid size are finally determined.

[0070] Calculate and compare the recovery rate variation pattern to determine the appropriate model and corresponding grid size: import the S23 model into the numerical simulation module, and calculate the recovery rate curve ( Figure 8 ). See Figure 9As shown in Figure 2, comparing the overall recovery curves of the three models reveals that the predicted recovery gradually decreases with increasing geological information. The prediction curves of Models 2 and 3 overlap significantly, but the modeling time for Model 3 increases significantly due to the increased sophistication. Therefore, Model 2 is the optimal choice after weighing technical prediction accuracy and efficiency.

[0071] For each model, the grid size also affects the predicted recovery factor. Models with richer geological information are more sensitive to grid size. The predicted recovery factor errors (per pore volume injected) for Models 1, 2, and 3 are 1.6%, 4.4%, and 4.5%, respectively. Based on the selected Model 2, applying a finer grid can also achieve predictive performance comparable to that of Model 3.

[0072] By refining the horizontal and vertical grid accuracy, we observed how the predicted permeability changed. Beyond a certain accuracy, the effect of grid refinement became less noticeable. The optimal grid size was determined to be 100*100*100.

[0073] In summary, the final recommended geological modeling should characterize four types of lithologies: well-sorted oolitic limestone, oolitic / pelitic limestone, pelitic limestone, and pelitic-micrite limestone, with a grid size of 10m*10m*0.5m.

[0074] The second embodiment of the present invention is applicable to the rapid evaluation of suitable geological models for porous carbonate rocks with high heterogeneity during carbonate reservoir development. This method, utilizing a modeling and digital-analysis integrated module through human-computer interaction, can rapidly evaluate geological models that effectively preserve reservoir heterogeneity. This embodiment of the present invention has significant application prospects for rapid geological model evaluation, dynamic analysis, and development plan formulation and adjustment in porous carbonate rocks with high heterogeneity.

[0075] Based on the inventive concept of the present invention, an embodiment of the present invention further provides an evaluation device for the influence of reservoir heterogeneity description scale on numerical simulation, the structure of the device is as follows: Figure 10 As shown, including:

[0076] The geological data acquisition module 101 is used to acquire geological data of multiple heterogeneous description scales of the target block;

[0077] The geological modeling module 102 is used to obtain, for each scale, multiple geological maps drawn by the user using the geological data of the scale as the background, establish a three-dimensional geological model based on the multiple geological maps, and perform attribute assignment;

[0078] The numerical simulation module 103 is used to obtain the numerical simulation results corresponding to each set grid size according to the set production well pattern and based on the three-dimensional geological model after attribute assignment;

[0079] The scale and grid size screening module 104 is used to screen the scale and grid size that meet the requirements of numerical simulation results and numerical simulation time, as the heterogeneous description scale and grid size required for numerical simulation of the study area where the target block is located.

[0080] In some embodiments, the geological data acquisition module 101 acquires geological data of a plurality of heterogeneous description scales of the target block, including acquiring geological data of at least the following heterogeneous description scales of the target block:

[0081] The first geological data includes sedimentary facies description data; the second geological data includes first lithology level description data; and the third geological data includes second lithology level description data that is more detailed than the first lithology level description data.

[0082] In some embodiments, the second geological data further includes first typical geological body description data that matches the scale of the first lithology level description data; and the third geological data further includes second typical geological body description data that matches the scale of the second lithology level description data.

[0083] In some embodiments, if the geological data corresponding to the three-dimensional geological model is first geological data, the geological modeling module 102 performs attribute assignment to:

[0084] Assign the same average attribute value to the same sedimentary facies;

[0085] If the geological data corresponding to the three-dimensional geological model is the second geological data or the third geological data, the geological modeling module 102 performs attribute assignment for:

[0086] The same average attribute value is assigned to the same lithology.

[0087] In some embodiments, the geological modeling module 102, performing attribute assignment, is used to:

[0088] Assign porosity and permeability.

[0089] In some embodiments, the geological modeling module 102 obtains multiple geological maps drawn by the user based on the geological data of the scale, for:

[0090] A plurality of cross-sectional geological maps and XY-plane geological maps drawn by the user with the geological data of the scale as the background are obtained. The cross-sectional geological maps are drawn in the order of deposition from earliest to latest.

[0091] In some embodiments, the numerical simulation results are numerical simulation results based on a steady-state flow field.

[0092] In some embodiments, the numerical simulation results include at least one of the following:

[0093] Recovery factor, cumulative oil production and sweep efficiency.

[0094] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0095] Based on the inventive concept of the present invention, an embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and when the computer executable instructions are executed by a processor, the above-mentioned method for evaluating the influence of the reservoir heterogeneity description scale on numerical simulation is implemented.

[0096] Based on the inventive concept of the present invention, an embodiment of the present invention further provides a server, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for evaluating the influence of the reservoir heterogeneity description scale on the numerical simulation is implemented.

[0097] Unless otherwise specifically stated, terms such as process, calculate, compute, determine, display, and the like may refer to the actions and / or processes of one or more processing or computing systems, or similar devices, that manipulate and convert data represented as physical (e.g., electronic) quantities within registers or memories of a processing system into other data similarly represented as physical quantities within the memories, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals may be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0098] It should be understood that the specific order or hierarchy of steps in the disclosed processes is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process can be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in an exemplary order and are not intended to be limited to the specific order or hierarchy described.

[0099] In the foregoing detailed description, various features are grouped together in a single embodiment to simplify the disclosure. This method of disclosure should not be interpreted as reflecting an intention that embodiments of the claimed subject matter require more features than are recited in each claim. On the contrary, as reflected in the appended claims, the invention comprises less than all the features of any individual disclosed embodiment. The appended claims are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate preferred embodiment of the invention.

[0100] Those skilled in the art will also appreciate that the various illustrative logic blocks, modules, circuits, and algorithmic steps described in conjunction with the embodiments herein may be implemented as electronic hardware, computer software, or a combination thereof. In order to clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described around their functions. Whether such functions are implemented as hardware or software depends on the specific application and the design constraints imposed on the entire system. A skilled person may implement the described functions in an adaptable manner for each specific application, but such implementation decisions should not be interpreted as departing from the scope of protection of this disclosure.

[0101] The steps of the methods or algorithms described in conjunction with the embodiments herein may be directly embodied as hardware, software modules executed by a processor, or a combination thereof. The software module may be located in a RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, register, hard disk, removable disk, CD-ROM, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium may also be an integral part of the processor. The processor and storage medium may be located in an ASIC. The ASIC may be located in a user terminal. Of course, the processor and storage medium may also be present in a user terminal as discrete components.

[0102] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. These software codes can be stored in a memory unit and executed by a processor. The memory unit can be implemented within the processor or external to the processor. In the latter case, it is communicatively coupled to the processor via various means, which are well known in the art.

[0103] The above description includes examples of one or more embodiments. Of course, it is not possible to describe all possible combinations of components or methods for the purpose of describing the above embodiments, but it will be appreciated by those skilled in the art that the various embodiments may be further combined and arranged. Therefore, the embodiments described herein are intended to encompass all such changes, modifications and variations that fall within the scope of protection of the appended claims. Furthermore, with respect to the term "comprising" used in the specification or claims, the word is encompassed in a manner similar to the term "including," as explained in terms of "including," used as a transitional word in the claims. Furthermore, any term "or" used in the specification of the claims is intended to mean "non-exclusive or." The terms "first," "second," and "third" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance.

Claims

1. A method for evaluating the impact of reservoir heterogeneity description scale on numerical simulation, characterized in that: include: Obtain geological data of multiple heterogeneous description scales for the target block; For each scale, multiple geological maps drawn by the user using the geological data of the scale as the background are obtained, and a three-dimensional geological model is established based on the multiple geological maps to perform attribute assignment; According to the set production well pattern, based on the three-dimensional geological model after attribute assignment, the numerical simulation results corresponding to each set grid size are obtained; The numerical simulation results and numerical simulation time that meet the required scale and grid size are screened as the heterogeneous description scale and grid size required for the numerical simulation of the study area where the target block is located.

2. The method according to claim 1, characterized in that The obtaining of geological data of multiple heterogeneous description scales of the target block includes obtaining geological data of at least the following heterogeneous description scales of the target block: First, geological data, including sedimentary facies description data; second geological data, including first lithologic level description data; The third geological data includes second lithology-level description data that is more detailed than the first lithology-level description data.

3. The method according to claim 2, characterized in that The second geological data further includes first typical geological body description data that matches the scale of the first lithologic level description data; The third geological data also includes second typical geological body description data that matches the scale of the second lithology level description data.

4. The method according to claim 2, characterized in that If the geological data corresponding to the three-dimensional geological model is first geological data, the attribute assignment includes: Assign the same average attribute value to the same sedimentary facies; If the geological data corresponding to the three-dimensional geological model is the second geological data or the third geological data, the attribute assignment includes: The same average attribute value is assigned to the same lithology.

5. The method according to claim 1, wherein The attribute assignment includes: Assign porosity and permeability.

6. The method according to claim 1, characterized in that The method of obtaining multiple geological maps drawn by the user based on the geological data of the scale includes: A plurality of cross-sectional geological maps and XY-plane geological maps drawn by the user with the geological data of the scale as the background are obtained. The cross-sectional geological maps are drawn in the order of deposition from earliest to latest.

7. The method according to claim 1, characterized in that The numerical simulation results are based on steady-state flow fields.

8. The method according to any one of claims 1 to 7, characterized in that: The numerical simulation results include at least one of the following: Recovery factor, cumulative oil production and sweep efficiency.

9. An evaluation device for the impact of reservoir heterogeneity description scale on numerical simulation, characterized in that: The device comprises: A geological data acquisition module is used to obtain geological data of multiple heterogeneous description scales of the target block; The geological modeling module is used to obtain, for each scale, multiple geological maps drawn by the user using the geological data of that scale as the background, establish a three-dimensional geological model based on the multiple geological maps, and perform attribute assignment; The numerical simulation module is used to obtain the numerical simulation results corresponding to each set grid size based on the set production well pattern and the three-dimensional geological model after attribute assignment; The scale and grid size screening module is used to screen the scale and grid size that meet the requirements of numerical simulation results and numerical simulation time, as the heterogeneous description scale and grid size required for numerical simulation of the study area where the target block is located.

10. A computer storage medium, characterized in that The computer storage medium stores computer executable instructions, which, when executed by a processor, implement the method for evaluating the influence of reservoir heterogeneity description scale on numerical simulation according to any one of claims 1 to 8.

11. A server, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for evaluating the influence of reservoir heterogeneity description scale on numerical simulation as claimed in any one of claims 1 to 8 is implemented.

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