Multi-scale fracture simulation method for fractured oil reservoir and computer readable storage medium

Abstract

The present application provides a multi-scale fracture simulation method for fractured oil reservoirs and a computer-readable storage medium, the method comprising: obtaining matrix corner grid model data, matrix attribute model data, fracture network model data and fracture attribute model data; hierarchically dividing the fracture network model into primary fractures and secondary fractures; constructing an unstructured basic grid based on the corner grid model and the primary fractures; mapping the attributes of the unstructured basic grid using the matrix attribute model and the fracture attribute model; correcting the matrix attributes of the mapped unstructured basic grid; and calculating the conductivity of the unstructured basic grid after attribute correction to obtain an unstructured hybrid grid model. Using the simulation method, the polarity of the primary fractures can be discretized, which is conducive to accurately capturing the flow characteristics of these fractures and improving the accuracy of numerical simulation. The equivalent and coarsening methods are used for small and medium-scale fractures, which greatly improves the efficiency of numerical simulation.

Description

Technical Field

[0001] The present invention relates to the field of reservoir numerical simulation, and more specifically, to a multi-scale fracture simulation method for a fractured reservoir and a computer-readable storage medium. Background Art

[0002] Fractured reservoirs are a widely existing type of reservoir. According to incomplete statistics, fractured reservoirs account for more than 28% of the current proven geological reserves (Yuan Shiyi, Song Xinmin, Ran Qiquan. Fractured Reservoir Development Technology, Petroleum Industry Press, 2004). Usually, there are fractures of different sizes and properties in the reservoir. According to the characteristics of fractures, there are two existing methods: dual medium model (Warren, JE and PJ Root. The Behavior of Naturally Fractured Reservoirs. SPE Journal, 1963, 3 (3): 245-255) and discrete fracture model (Karimi-Fard, M., LJ Durlofsky and K. Aziz. An efficient discrete-fracture model applicable for general-purpose reservoir simulators. SPE Journal, 2004, 9 (2): 227-236) to describe fractures and provide models and parameters for subsequent numerical simulations.

[0003] These two models have different characteristics and adaptability: the dual-medium model is stable and efficient, but has low accuracy and is often only applicable to areas with developed small and medium-sized fractures. It is not suitable for situations where primary fractures have a significant impact on the flow of the entire reservoir. The discrete fracture model is characterized by detailed fracture characterization and high numerical simulation accuracy. However, due to its extremely high resolution, it cannot efficiently simulate reservoirs with developed small and medium-sized fractures.

[0004] (1) Ten-meter or even hundred-meter scale fractures or main fractures in reservoirs are usually large in size, strong in conductivity, and have a great impact on fluid seepage and reservoir development. In terms of distribution, the number of such fractures is small and sparsely distributed. Since a single fracture has a great impact on seepage and is sparsely distributed, for such fractures, the use of traditional dual-medium models will have a large error, and the use of discrete fracture models is more accurate and effective (Sarda, S., L. Jeannin, R. Basquet and B. Bourbiaux. Hydraulic characterization of fractured reservoirs: simulation on discrete fracture models. SPE Reservoir Evaluation & Engineering, 2002, 5 (2): 154-162).

[0005] (2) Some fractures such as secondary fractures and small-scale natural fracture networks are usually small in size and weak in conductivity. They are distributed in a grid-like manner and are suitable for simulation with a dual-media model. If a discrete fracture model is used, it will cause too many grids and slow calculation speed (Sarma, P. and K. Aziz. New transfer functions for simulation of naturally fractured reservoirs with dual porosity models. SPE Annual Technical Conference and Exhibition, Society of Petroleum Engineers, 2004).

[0006] The existence of multi-scale fractures results in the inability to adapt to the computational efficiency of discrete fracture model numerical simulation. In the actual application of fractured reservoirs, only dual medium model can be used for modeling and numerical simulation. Therefore, the results of existing fracture reservoir modeling work are often a set of dual medium models, that is, without distinguishing the scale or flow characteristics of fractures, a specific method is used to calculate the numerical simulation model parameters of the fracture system of the entire reservoir: fracture porosity and permeability, and the cross-flow coefficient between the matrix and the fracture grid. Although there have been many improvements in the calculation method of dual medium model parameters in recent years, such as the use of flow-based coarsening method to calculate the permeability and cross-flow coefficient of fracture medium grids, no matter which method is used, the limitations of dual medium model are inevitable (Kazemi, H., LSMerrill Jr, KLPorterfield and PRZeman. Numerical simulation of water-oil flow in naturally fractured reservoirs. Society of Petroleum Engineers Journal, 1976, 16 (6): 317-326).

[0007] In summary, since fractured reservoirs usually have fractures of different causes, scales and distribution patterns, the above two models cannot meet the requirements of accuracy and efficiency at the same time. Therefore, it is necessary to develop a new modeling and numerical simulation technology for multi-scale fractured reservoirs to solve the contradiction between fine modeling and efficient numerical simulation of multi-scale fractured reservoirs. Summary of the invention

[0008] In response to the above-mentioned problems in the prior art, the present application proposes a multi-scale fracture simulation method for fractured oil reservoirs and a computer-readable storage medium, which starts from an existing dual-medium model and a primary fracture system, and uses a true discrete fracture modeling technology to perform a fine characterization of the primary fractures without changing the equivalent medium model of the secondary fractures, thereby greatly improving the model accuracy while ensuring the computational efficiency.

[0009] In the first aspect, the present application provides a multi-scale fracture simulation method for fractured reservoirs, including: obtaining matrix corner grid model data, matrix attribute model data, fracture network model data and fracture attribute model data from a dual-porosity medium model; hierarchically dividing the fracture network model into primary fractures and secondary fractures; constructing an unstructured basic grid based on the corner grid model and the primary fractures; using the matrix attribute model and the fracture attribute model to perform attribute mapping on the unstructured basic grid; correcting the matrix attributes of the mapped unstructured basic grid; and calculating the conductivity of the unstructured basic grid after attribute correction to obtain an unstructured hybrid grid model. Using this simulation method, the polarity of the primary fractures can be discretized, which is conducive to accurately capturing the flow characteristics of these fractures and improving the accuracy of numerical simulation. The equivalent and coarsening methods are used for small and medium-scale fractures, greatly improving the efficiency of numerical simulation.

[0010] In one embodiment of the first aspect, an unstructured basic grid is constructed based on the corner grid model and the main-level crack, including: inputting the corner grid model data, generating an outer envelope surface of the model as an outer constraint surface of the unstructured grid; extracting the main-level crack geometric polygons as the inner constraint surface of the unstructured grid; and dividing the unstructured grid to form the unstructured basic grid.

[0011] In one implementation of the first aspect, the fracture network model is divided into primary fractures according to the following formula:

[0012] F I ={f∈F|L f >L1 and d f >d1 and k f >k1}

[0013] Among them, F I is the main fracture set, L f is the crack length, L1 is the critical length of the crack, d f is the crack opening, d1 is the critical opening, k f The crack permeability, k1 is the critical permeability.

[0014] In one embodiment of the first aspect, the matrix attribute model data is obtained by performing attribute modeling on a corner point grid model, and the attribute modeling method includes a random simulation method, an interpolation method, and an expression evaluation method.

[0015] In one embodiment of the first aspect, the attribute data of the secondary fractures are obtained by an equivalent processing method, which includes an experimental measurement method, a digital core analysis method, and a numerical equivalent method based on flow simulation.

[0016] In one embodiment of the first aspect, attribute mapping is performed on the unstructured base grid using the matrix attribute model and the fracture attribute model, including: searching for all structured grids contained in the unstructured grid; calculating the volume and weight of each structured grid in the unstructured grid; and calculating the attributes of the unstructured grid according to the weight.

[0017] In one embodiment of the first aspect, the weight of the structured grid is calculated by the following formula:

[0018]

[0019] Among them, G is an unstructured grid, g is a structured grid, and w g is the weight of the structured grid, V g is the volume of the structured grid, V i is the volume of the i-th structured grid;

[0020] The properties of the unstructured grid are calculated by the following equation:

[0021]

[0022] Among them, p G is a certain attribute value of the unstructured grid G, w i is the volume of the i-th structured grid, p i is a property value of the i-th structured grid.

[0023] In one embodiment of the first aspect, the matrix porosity is corrected according to the following formula:

[0024]

[0025] in, is the modified matrix grid porosity, φ f is the fracture porosity, V cell is the grid volume, A f is the crack area, e f is the average crack opening;

[0026] The matrix permeability was corrected according to the following formula;

[0027]

[0028] i and j represent the grid, k ij * is the corrected matrix permeability; F kk is an expression using the Einstein summation convention; k ij is the equivalent permeability of the fracture; δ ij is the Kronecker symbol, that is, when i=j, δij =1, i≠j when δ ij =0; T f is the crack conductivity; n if 、n jf is the projection of the plane normal vector of crack f on the i and j planes.

[0029] In a second aspect, the present application also provides a computer-readable storage medium, which stores one or more programs, and the one or more programs can be executed by one or more processors to implement a method for simulating multi-scale fractures in a fractured oil reservoir as described in the first aspect and any embodiment thereof.

[0030] Compared with the prior art, the simulation method and computer-readable storage medium for multi-scale fractures in fractured reservoirs provided in the present application distinguish and consider fractures with different effects on reservoir permeability, and process them into the final hybrid grid model through different methods. The discretization of main-level fractures is conducive to accurately capturing the flow characteristics of these fractures and improving the accuracy of numerical simulation. The equivalent and coarsening methods used for small and medium-scale fractures can greatly improve the efficiency of numerical simulation.

[0031] The above technical features can be combined in various suitable ways or replaced by equivalent technical features as long as the purpose of the present invention can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The present invention will be described in more detail below based on embodiments and with reference to the accompanying drawings, wherein:

[0033] Figure 1 A schematic flow chart of a method for simulating multi-scale fractures in a fractured oil reservoir according to an embodiment of the present invention is shown;

[0034] Figure 2 A schematic diagram showing the extraction of primary fractures and performing unstructured segmentation to obtain a basic grid according to an embodiment of the present invention is shown;

[0035] Figure 3 A schematic diagram of an attribute mapping algorithm according to an embodiment of the present invention is shown;

[0036] Figure 4 A schematic diagram of attribute mapping from structured grid attributes to unstructured base grid according to an embodiment of the present invention is shown;

[0037] Figure 5 A schematic diagram showing the calculation of conductivity between grids of arbitrary shapes according to an embodiment of the present invention is shown;

[0038] Figure 6 A schematic diagram showing a multi-scale fracture according to another embodiment of the present invention;

[0039] Figure 7 A schematic diagram of dividing an unstructured grid according to corner grid information and primary fractures according to another embodiment of the present invention is shown;

[0040] Figure 8 A schematic diagram showing attribute correction of an unstructured basic grid according to another embodiment of the present invention is shown;

[0041] Fig. 9 A schematic diagram of an unstructured hybrid grid model according to another embodiment of the present invention is shown;

[0042] Fig.10 A schematic diagram showing a comparison of oil saturation fields using three different simulation methods according to another embodiment of the present invention;

[0043] Fig.11 A schematic diagram showing a comparison of daily oil production curves of three different simulation methods according to another embodiment of the present invention;

[0044] Fig.12 A schematic diagram showing comparison of moisture content curves of three different simulation methods according to another embodiment of the present invention;

[0045] Fig.13 A schematic diagram showing comparison of numerical simulation times of three different simulation methods according to another embodiment of the present invention is shown.

[0046] In the drawings, the same reference numerals are used for the same components. The drawings are not drawn to scale. DETAILED DESCRIPTION

[0047] The present invention will be further described below in conjunction with the accompanying drawings.

[0048] Embodiment 1

[0049] Figure 1 Schematic diagram of the simulation method according to the present invention. Figure 1 As shown, the simulation method includes:

[0050] S110, acquiring matrix corner grid model data, matrix attribute model data, fracture network model data, and fracture attribute model data from the dual-porosity medium model;

[0051] S120, hierarchically dividing the fracture network model into primary fractures and secondary fractures;

[0052] S130, constructing an unstructured basic grid based on the corner point grid model and the primary cracks;

[0053] S140, performing attribute mapping on the unstructured basic grid using the matrix attribute model and the fracture attribute model;

[0054] S150, modifying the matrix properties of the mapped unstructured basic grid; and

[0055] S160, calculating the conductivity of the unstructured basic grid after property correction, and obtaining an unstructured hybrid grid model.

[0056] In S110, the data that needs to be read from the existing dual-porosity medium model in the present invention includes the following types:

[0057] (1) Geological grid data

[0058] Corner grid models can generally be generated by 3D geological modeling software and exported into Eclipse corner grid files (*.GRDECL) format files. Commonly used 3D geological modeling software include Petrel, SKUA / GOCAD, RMS, etc.

[0059] (2) Bedrock medium property model

[0060] The matrix attribute model is established after the corner grid model is generated. It is usually completed in 3D geological modeling software, or with the help of professional geological statistics software such as GsLib. To establish each attribute model, hard data is required as input data. Hard data can be divided into core data, logging data, seismic data, etc. according to its source. Under the constraint of hard data, the attribute model corresponding to the grid is established through a specific attribute modeling method, that is, assigning attributes to each grid unit. Commonly used attribute modeling methods include random simulation methods (such as Gaussian sequential simulation method), interpolation methods (such as ordinary kriging method) and expression evaluation methods. The matrix attribute model is based on the corner grid model in (1), including the three attributes of matrix porosity, permeability and net-to-gross ratio. It is particularly important to note that the attribute model here needs to distinguish between the two attributes of matrix and fracture.

[0061] (3) Fracture network model

[0062] The fracture network model is generally established by professional fracture modeling software. Common fracture modeling software include Fraca, FracMan, etc. With the deepening and promotion of fracture model research, many 3D geological modeling software (such as Petrel, GOCAD, etc.) also support fracture network modeling. After modeling, it is exported and saved as FAB format file of Fraca / FracMan / Petrel or TS format file of GOCAD.

[0063] (4) Fracture medium property model

[0064] The fracture property model is usually established by the fracture network model. For micro-scale fractures, an equivalent treatment method is generally adopted to take the seepage properties of the fracture medium into account in the bedrock medium. Equivalent methods include experimental measurement, digital core analysis, and numerical equivalent methods based on flow simulation. Here, the Oda method is used as an example for introduction.

[0065] The equivalent porosity is:

[0066]

[0067] Among them, φ f is the fracture porosity, V f is the volume of the fracture system, V cell is the grid volume, A f is the crack area, e f is the average crack opening.

[0068] For the crack surface density P 32 The established discrete fracture network can also be approximately calculated by the following formula:

[0069] φ f =P 32 e

[0070] Among them, P 32 is the crack surface density, and e is the average crack opening.

[0071] The equivalent permeability tensor of fractured media is:

[0072]

[0073]

[0074] Among them, i and j represent grids, k ij is the fracture equivalent permeability tensor; δ ij is the Kronecker symbol, that is, when i=j, δ ij =1, i≠j when δ ij =0; T f is the crack conductivity; n if ·n jf is the projection of the plane normal vector of the crack f on the i and j planes; F ij is the crack tensor, F kk is the expression using the Einstein summation convention, for a 3rd-order tensor, that is

[0075] F kk =F 11 +F 22 +F 33

[0076] In S120, Figure 2 As shown, the fracture network model obtained in S110 needs to be graded, that is, the main fractures are extracted from the fracture network model for subsequent discretization. Figure 2 All the cracks in (a) are extracted based on the crack scale (such as height, width and opening), crack filling rate, crack conductivity and crack distribution and communication data, such as Figure 2 As shown in (b), the primary cracks are marked, and the remaining cracks are marked as secondary cracks. Generally speaking, secondary cracks are fractures generated by hydraulic fracturing and small-scale natural cracks.

[0077] The standard for extracting primary fractures is: setting primary fracture classification parameters, including critical length L1, critical opening d1, and critical permeability k1, then in the fracture network F, subset F I That is the main level crack collection.

[0078] F I ={f∈F|L f >L1 and d f >d1 and k f >k1}

[0079] Among them, L f is the crack length, d f Critical opening, k f Critical permeability.

[0080] Next, in S130, the primary fracture is discretized, that is, based on the extracted primary fracture and combined with the geometric information of the structural model, an unstructured grid is divided as a basic grid, such as Figure 2 and Figure 6 shown.

[0081] Specifically, the unstructured subdivision to form a basic grid includes the following sub-steps:

[0082] Input the corner point mesh model data obtained in S110 to generate an outer envelope surface of the model as an outer constraint surface of the unstructured mesh;

[0083] Extracting primary fracture geometry polygons as constraint surfaces within the unstructured grid; and

[0084] The unstructured grid is divided to form the unstructured basic grid.

[0085] In this way, the basic grid can be used as a carrier of the final hybrid grid, that is, a hybrid grid model for numerical simulation is finally obtained based on the basic grid.

[0086] Since the establishment of the existing geological attribute model has integrated the sedimentary phase model information and has been corrected by the well data, after completing the unstructured grid modeling step, there is no need to perform geological attribute modeling based on Kriging interpolation or Gaussian sequential simulation again. Instead, the geological attribute model can be directly mapped to the geological grid.

[0087] The mapping algorithm can adopt a volume-weighted average algorithm, such as Figure 3 As shown, for any unstructured grid G, the attribute calculation steps are:

[0088] (1) Search for all structured grids contained in the unstructured grid G;

[0089] (2) Calculate the volume of each structured grid in the unstructured grid G ​​and calculate its weight. For example, for the structured grid g, its weight calculation formula is:

[0090]

[0091] In the formula, w g is the structured grid g weight, V g is the volume of structured grid g, V i is the volume of the i-th structured grid;

[0092] (3) Using the weights obtained in (2), calculate the properties of the grid G:

[0093]

[0094] In the formula, p G is a certain attribute value of the unstructured grid G, w i is the volume of the i-th structured grid, p i is a property value of the i-th structured grid.

[0095] Figure 4 (a) shows the structured grid properties, and (b) shows the unstructured grid properties mapped from the structured grid.

[0096] In S150, since the original dual-pore model fracture medium attributes already include the attributes of the main fracture, after the main fracture is fully characterized by the unstructured grid, the attributes of the fracture medium model need to be corrected, that is, the contribution of the main fracture is subtracted from the attributes of the original fracture medium model.

[0097] The calculation formula is the inverse operation of attribute equivalence, taking the Oda method as an example.

[0098] Correct the matrix medium porosity, the calculation formula is:

[0099]

[0100] in, is the corrected fracture medium grid porosity.

[0101] Corrected matrix permeability, the calculation formula is:

[0102]

[0103] i and j represent the grid, k ij * is the corrected matrix permeability; F kk is an expression using the Einstein summation convention; k ij is the equivalent permeability of the fracture; δ ij is the Kronecker symbol, that is, when i=j, δ ij =1, i≠j when δ ij =0; T f is the crack conductivity; n if 、n jf is the projection of the plane normal vector of crack f on the i and j planes.

[0104] In this embodiment, the present application further includes the following step S160: calculating the conductivity of the unstructured basic grid after property correction to obtain an unstructured hybrid grid model.

[0105] Specifically, the calculation method adopts the two-point flow conductivity calculation formula of arbitrary shape grid (Karimi-Fard, Durlofsky et al. 2004). Specifically, Figure 5 As shown in Figure 2, the conductivity formula between any adjacent unstructured grids is:

[0106]

[0107] Among them: A i is the area of ​​the intersection between grid i and adjacent grid j, k i is the permeability of grid i, D i is the length from the center point of grid i to the center point of the intersection surface, is the unit normal vector of the intersection surface pointing to the i grid, It is the unit direction vector from the center point of the intersection surface to the center point of the i grid.

[0108] Note that each unstructured grid has two attributes: bedrock medium and fracture medium. Therefore, this step needs to be calculated for each medium grid. According to the matrix type of the adjacent grid ij, the conductivity can be subdivided into T MM , There are several types, among which M represents bedrock medium, F I represents the primary fracture grid (discrete fracture grid), FII Represents the fracture medium grid (equivalent fracture grid).

[0109] The final model obtained by the present invention is a hybrid grid model of a dual medium model and a discrete fracture model.

[0110] Embodiment 2

[0111] In this example, an example of a multi-scale fractured reservoir is shown. Figure 6 As shown in the figure, primary fractures and secondary fractures are extracted according to the fracture network geometry data read in the present invention, wherein (a) is a schematic diagram of the multi-scale fracture model in the model, (b) is a schematic diagram of the extracted primary fractures, and (c) is a schematic diagram of the extracted secondary fractures. For the primary fractures, the method described in step S130 is used to divide the unstructured grid and the method described in step S140 is used to perform attribute mapping, as shown in FIG. Figure 7 As shown, (a) is a corner point grid and a primary fracture model diagram, and (b) is an unstructured grid diagram obtained based on the corner point grid and the primary fracture decomposition. For secondary fractures, the method described in step S150 is used to perform attribute equivalent correction. Figure 8 As shown, (a) is the secondary fracture model diagram, and (b) is the permeability equivalent attribute diagram after correction of the original model.

[0112] Fig. 9 The schematic diagram of the full-scale model and the well location are shown in the figure. In order to better compare the effect of the patented method, a full unstructured grid model is designed as a reference model, and a traditional double-hole model is designed as a comparison model. Fig.10 The three models are from left to right: (a) is the simulation result of the full unstructured grid model (reference model), (b) is the simulation result of the traditional dual-medium model, and (c) is the simulation result of the model proposed in this application; it is obvious that the simulation method provided in this application can more accurately and comprehensively simulate the multi-scale fractures in the fractured reservoir.

[0113] Figure 11 to Figure 13 For comparison of test results using the method of the present invention, the simulation time of the full unstructured grid model (reference model) is 56 minutes, the simulation time of the traditional dual-medium model is 14 minutes, and the simulation time of the model proposed in the patent is 18 minutes. Compared with the traditional dual-pore medium model, the simulation time increases by 4 minutes, and the relative error is reduced from the original 17% to 3%.

[0114] The simulation method for multi-scale fractures in fractured reservoirs provided by the present invention distinguishes and considers fractures with different effects on reservoir permeability, and processes them into the final hybrid grid model through different methods, wherein the discretization processing of main-level fractures is conducive to accurately capturing the flow characteristics of these fractures and improving the accuracy of numerical simulation. The equivalent and coarsening methods used for small and medium-scale fractures can greatly improve the efficiency of numerical simulation.

[0115] Embodiment 3

[0116] Some embodiments of the present application also provide a computer-readable storage medium storing one or more programs, which can be executed by one or more processors to implement the simulation method for multi-scale fractures in fractured oil reservoirs as described above.

[0117] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of boxes in the block diagram and / or the flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0118] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0119] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a laptop, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code. It should be noted that in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variation thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0120] The processor may be an integrated circuit chip with signal processing capabilities. The above-mentioned processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention may be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0121] The memory may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc. The memory is also used to store programs, and the processor executes the program after receiving the execution instruction. The method executed by the server of the process definition disclosed in any embodiment of the present invention described below can be applied to the processor or implemented by the processor.

[0122] Although the present invention has been described with reference to preferred embodiments, various modifications may be made thereto and parts thereof may be replaced by equivalents without departing from the scope of the present invention. In particular, the various technical features mentioned in the various embodiments may be combined in any manner as long as there are no structural conflicts. The present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

[0123] In the description of the present invention, it is necessary to understand that the terms "upper", "lower", "bottom", "top", "front", "back", "inside", "outside", "left", "right", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0124] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the present invention. It should therefore be understood that many modifications may be made to the exemplary embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in a manner different from that described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be used in other described embodiments.

Claims

1. A method for simulating multi-scale fractures in a fractured oil reservoir, characterized in that: include: Obtaining matrix corner grid model data, matrix attribute model data, fracture network model data, and fracture attribute model data from the dual-porosity medium model; The fracture network model is hierarchically divided into primary fractures and secondary fractures; Constructing an unstructured basic grid based on the corner point grid model and the primary cracks, wherein the basic grid is a carrier of the final hybrid grid; Performing attribute mapping on the unstructured base grid using the matrix attribute model and the fracture attribute model; Modifying the matrix properties of the mapped unstructured base grid; The step of correcting the matrix properties of the mapped unstructured basic grid includes: The matrix porosity was corrected according to the following formula: in, is the modified matrix grid porosity, φ f is the fracture porosity, V cell is the grid volume, A f is the crack area, e f is the average crack opening; The matrix permeability was corrected according to the following formula; Among them, i and j represent grids, k ij * is the corrected matrix permeability; F kk is an expression using the Einstein summation convention; k ij is the equivalent permeability of the fracture; δ ij is the Kronecker symbol, that is, when i=j, δ ij =1, i≠j when δ ij =0; T f is the crack conductivity; n if 、n jf is the projection of the plane normal vector of crack f on the i, j plane; and calculating the conductivity of the unstructured basic grid after property correction to obtain an unstructured hybrid grid model; The conductivity formula between any adjacent unstructured grids is: Among them: A i is the area of ​​the intersection between grid i and adjacent grid j, k i is the permeability of grid i, D i is the length from the center point of grid i to the center point of the intersection surface, is the unit normal vector of the intersection surface pointing to the i grid, The unit direction vector from the center point of the intersection surface to the center point of the i grid; Among them, each unstructured grid has two attributes of bedrock medium and fracture medium, and each medium grid performs conductivity calculation.

2. The simulation method according to claim 1, characterized in that: An unstructured basic grid is constructed based on the corner point grid model and the primary cracks, including: Input the corner point grid model data to generate the model outer envelope surface as the outer constraint surface of the unstructured grid; Extracting primary fracture geometry polygons as constraint surfaces within the unstructured grid; and The unstructured grid is divided to form the unstructured basic grid.

3. The simulation method according to claim 1, characterized in that: The fracture network model is divided into primary fractures according to the following formula: F I ={f∈F|L f >L1 and d f >d1 and k f >k1} Among them, F I is the main fracture set, L f is the crack length, L1 is the critical length of the crack, d f is the crack opening, d1 is the critical opening, k f The crack permeability, k1 is the critical permeability.

4. The simulation method according to claim 1, characterized in that: The matrix attribute model data is obtained by performing attribute modeling on the corner point grid model, and the attribute modeling methods include random simulation method, interpolation method and expression evaluation method.

5. The simulation method according to claim 1, characterized in that: The attribute data of the secondary fractures are obtained through an equivalent processing method, which includes an experimental measurement method, a digital core analysis method, and a numerical equivalent method based on flow simulation.

6. The simulation method according to claim 1, characterized in that: Using the matrix attribute model and the crack attribute model to perform attribute mapping on the unstructured basic grid includes: Search for all structured grids contained in the unstructured grid; Calculating the volume and weight of each structured grid in the unstructured grid; Attributes of the unstructured grid are calculated according to the weights.

7. The simulation method according to claim 6, characterized in that: Also includes: The weight of the structured grid is calculated by the following formula: Among them, G is an unstructured grid, g is a structured grid, and w g is the weight of the structured grid, V g is the volume of the structured grid, V i is the volume of the i-th structured grid; The properties of the unstructured grid are calculated by the following equation: Among them, p G is a certain attribute value of the unstructured grid G, w i is the weight of the i-th structured grid, p i is a property value of the i-th structured grid.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the method for simulating multi-scale fractures in a fractured oil reservoir as described in any one of claims 1-7.

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