Multi-source constraint large-scale crack automatic modeling method and related equipment

Abstract

The invention discloses a multi-source constraint large-scale crack automatic modeling method and related equipment, and the method comprises the steps: setting the trend, length and length-height ratio distribution of a crack through the detection data of the crack, and building a crack density space distribution probability body; a crack network is obtained according to the trend, length and height distribution of the cracks and the crack density space distribution probability body, a crack model is established according to the crack network, and the large-scale discrete crack model can be established under the constraint of multi-source crack detection data. According to the method, priori knowledge such as seismic attributes, lengths and directions of fractures and drilling leakage and production dynamic data are combined, and the final result quantitatively represents the positions and flow attributes of the large-scale fractures in the natural fractured oil and gas reservoir. An accurate model is provided for effective development of fractured oil and gas reservoirs, it is guaranteed that the model established through the method better conforms to the understanding of geology and geophysical prospecting, and the dynamic historical fitting result can be met.

Description

Technical Field

[0001] The invention belongs to the technical field of oil extraction, and specifically relates to a multi-source constrained large-scale fracture automatic modeling method and related equipment. Background Art

[0002] For fractured oil and gas reservoirs, the geometry and flow characteristics of natural fractures, especially large-scale natural fractures, are crucial to the development of oil and gas reservoirs. The current method for large-scale fracture modeling mainly relies on the experience of modeling engineers and is added manually. This method that relies on the experience of engineers has the disadvantages of high uncertainty and subjectivity.

[0003] In the process of large-scale fracture modeling, the data that can reflect fracture information mainly include various seismic attributes, prior knowledge constraints brought by analyzing structural background characteristics, drilling leakage, and fracture information directly or indirectly reflected by production history. How to comprehensively consider these multi-source fracture information and generate a fracture model that meets the multi-source data constraints through an automated method is of great significance. At present, the research on this method is still in a blank stage. Summary of the invention

[0004] The present invention provides a multi-source constrained large-scale fracture automatic modeling method and related equipment, which solves the shortcomings of methods that rely on engineers' experience, such as large uncertainty and high subjectivity.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A multi-source constrained large-scale fracture automatic modeling method, comprising:

[0007] Set the crack direction, length and aspect ratio distribution according to the physical properties of the crack;

[0008] Establish a probability body of crack density spatial distribution based on crack detection data;

[0009] The fracture network is obtained based on the distribution of fracture direction, length and height and the probability body of fracture density spatial distribution;

[0010] A fracture model is established based on the fracture network.

[0011] Preferably, the fracture network satisfying the constraints of prior distribution, drilling loss and production test fracture position is obtained according to the distribution of fracture strike, length and height and the fracture density spatial distribution probability body:

[0012] According to the distribution of the crack direction, length and height, the crack direction, length, height and the position of the crack center are randomly sampled;

[0013] Generate discrete fracture slices based on the fracture density spatial distribution probability volume;

[0014] Acceptance conditions are set, and the random adoption and generation of discrete fracture slices are repeated, and the distances between the fracture slices and the leakage points and the fracture positions shown by the production test are calculated until the acceptance conditions are met and the fracture network is obtained.

[0015] Preferably, the acceptance condition is to calculate the distance between the fracture slice and the leakage point and the fracture position displayed by the production test according to the drilling leakage data and the production test data, and select a certain threshold as the acceptance condition.

[0016] Preferably, the fracture network satisfies a priori distribution, drilling loss, and production test fracture location constraints.

[0017] Preferably, obtaining the fracture model according to the fracture network specifically includes randomly assigning values ​​to fracture permeabilities according to the fracture network, performing numerical simulation until a matching rate condition is satisfied, and obtaining the fracture model.

[0018] Preferably, the matching rate condition is:

[0019] 1-(|Dsim-Dobs|) / Dobs>σ

[0020] Among them, Dsim is the simulation data, Dobs is the historical data, and σ is the matching rate.

[0021] Preferably, the fracture detection data includes: seismic coherence volume attributes, drilling loss data and production history data.

[0022] A multi-source constrained large-scale fracture automatic modeling system, comprising:

[0023] Setting module: Set the crack direction, length and aspect ratio distribution according to the physical properties of the crack;

[0024] Establishing module: establishing crack density spatial distribution probability body according to crack detection data;

[0025] Fracture network acquisition module: obtain the fracture network based on the distribution of fracture direction, length and height and the probability body of fracture density spatial distribution;

[0026] Modeling module: Establish a fracture model based on the fracture network.

[0027] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for automatic modeling of large-scale fractures with multi-source constraints are implemented.

[0028] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for automatic modeling of large-scale fractures with multi-source constraints are implemented.

[0029] Compared with the prior art, the present invention has the following beneficial effects: the present invention provides a method for automatic modeling of large-scale fractures with multi-source constraints, which sets the direction, length and aspect ratio distribution of the fractures through the detection data of the fractures, and establishes a probability body for the spatial distribution of fracture density, and then obtains a fracture network based on the distribution of the direction, length and height of the fractures and the probability body for the spatial distribution of fracture density, and finally establishes a fracture model based on the fracture network, so that a large-scale discrete fracture model can be established under the constraints of multi-source fracture detection data. The model established by this method is more in line with the knowledge of geology and geophysical exploration, and can meet the results of dynamic historical fitting. The method proposed by this invention fills the gap in the automatic modeling of multi-source constrained fractures, and realizes the demand for efficient and automatic establishment of accurate fracture models. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of a method for automatic modeling of large-scale fractures with multi-source constraints according to an embodiment of the present invention;

[0031] Figure 2 The relative fracture density distribution and drilling loss diagram of the present invention;

[0032] Figure 3 A discrete fracture model that satisfies multi-source constraints in the present invention;

[0033] Figure 4 The comparison between the numerical simulation results of the present invention and the historical results;

[0034] Figure 5 This is a flow chart of a multi-source constrained large-scale fracture automatic modeling method of the present invention;

[0035] Figure 6 This is a block diagram of a multi-source constrained large-scale fracture automatic modeling system of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0037] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0039] In the description of the embodiments of the present invention, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product of the invention is usually placed when in use, it is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply 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. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0040] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", which does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0041] In the description of the embodiments of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0042] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0043] like Figure 5 The present invention provides a multi-source constrained large-scale fracture automatic modeling method, comprising:

[0044] S101 sets the direction, length and aspect ratio distribution of the crack according to the physical properties of the crack;

[0045] S102: establishing a probability body of crack density spatial distribution according to crack detection data;

[0046] S103 obtains a fracture network according to the distribution of fracture directions, lengths and heights and a fracture density spatial distribution probability body;

[0047] S104 establishes a fracture model according to the fracture network.

[0048] According to the distribution of fracture direction, length and height and the probability body of fracture density spatial distribution, the fracture network that satisfies the constraints of prior distribution, drilling loss and production test fracture location is obtained as follows:

[0049] According to the distribution of the crack direction, length and height, the crack direction, length, height and the position of the crack center are randomly sampled;

[0050] Generate discrete fracture slices based on the fracture density spatial distribution probability volume;

[0051] Acceptance conditions are set, and the random adoption and generation of discrete fracture slices are repeated, and the distances between the fracture slices and the leakage points and the fracture positions shown by the production test are calculated until the acceptance conditions are met and the fracture network is obtained.

[0052] The acceptance condition is to calculate the distance between the fracture slice and the leakage point and the fracture position shown by the production test based on the drilling leakage data and production test data, and select a certain threshold as the acceptance condition

[0053] The fracture network satisfies the prior distribution, drilling loss and production test fracture location constraints.

[0054] The method of obtaining the fracture model according to the fracture network specifically includes randomly assigning values ​​to the fracture permeabilities according to the fracture network, performing numerical simulation until the matching rate condition is met, and obtaining the fracture model.

[0055] The matching rate condition is:

[0056] 1-(|Dsim-Dobs|) / Dobs>σ

[0057] Among them, Dsim is the simulation data, Dobs is the historical data, and σ is the matching rate.

[0058] like Figure 1 As shown, the specific implementation method of the present invention is:

[0059] A. Based on the prior knowledge of the crack direction, length and height, define the crack direction distribution A~U(a,b), L~P(c,d) and the length and height ratio distribution: H~R(e,f)

[0060] B. Define the probability of cracks existing at spatial locations by earthquake attributes: D~F(x,y,z)

[0061] C. Random sampling: According to the probability distribution defined by A and B, the crack direction, length, height and the position of the crack center are sampled respectively.

[0062] D. Generate discrete crack slices: Generate discrete crack slices based on the crack parameters sampled in step C.

[0063] E. Define the acceptance conditions: According to the drilling loss data and production test data, the fracture acceptance conditions are divided on the wellbore: the distance between the fracture slice and the loss point and the fracture position shown by the production test is calculated, and a certain threshold θ value is selected as the acceptance condition.

[0064] Repeat steps C to D n times to obtain a fracture network that satisfies the prior distribution, as well as drilling loss and production test fracture location constraints.

[0065] F. Define the permeability distribution K~U(α,β) of each crack in the fracture network, and assign a permeability value to each crack by random sampling.

[0066] G. Run numerical simulation of the reservoir and dynamically adjust the permeability value based on the numerical simulation results.

[0067] H. Run m numerical simulations to achieve the condition that the simulation data Dsim, the historical data Dobs, and the matching rate σ meet 1-(|Dsim-Dobs|) / Dobs>σ, and obtain the final crack model.

[0068] The fracture detection data include: seismic coherence volume attributes, drilling loss data and production history data.

[0069] Example:

[0070] Take a block in K gas field as an example. The reservoir is a fractured carbonate reservoir. The existing fracture detection data include seismic coherence attributes, drilling loss data, and production history data:

[0071] Step 1: Define the distribution of crack direction, length and height, which are A~U(150,200), L~P(c,d) and H~R(1,4);

[0072] Step 2: Establish the probability body F(x, y, z) of crack density spatial distribution according to the coherence body attributes;

[0073] Step 3: Randomly sample crack parameters to generate discrete crack slices;

[0074] Step 4: Select θ = 50 meters as the receiving condition and receive those fractures within 50 meters from the drilling leakage point.

[0075] Step 5: Repeat steps 3 and 4 for 1000 times to get the final crack result.

[0076] Step 6: Randomly assign values ​​to the fracture permeability in the range of 1000-1000000 mD, and run 100 numerical simulations. Compare the relationship between the 100 numerical simulation results and the production history to determine the final fracture permeability.

[0077] like Figure 6 As shown, the present invention also provides a multi-source constrained large-scale fracture automatic modeling system, comprising:

[0078] Setting module: Set the crack direction, length and aspect ratio distribution according to the physical properties of the crack;

[0079] Establishing module: establishing crack density spatial distribution probability body according to crack detection data;

[0080] Fracture network acquisition module: obtain the fracture network based on the distribution of fracture direction, length and height and the probability body of fracture density spatial distribution;

[0081] Modeling module: Establish a fracture model based on the fracture network.

[0082] A terminal device is provided in one embodiment of the present invention. The terminal device of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0083] The computer program may be divided into one or more modules / units, and the one or more modules / units are stored in the memory and executed by the processor to accomplish the present invention.

[0084] The terminal device may be a computing device such as a desktop computer, a notebook, a palmtop computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0085] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0086] The memory may be used to store the computer programs and / or modules, and the processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory.

[0087] If the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0088] Although the embodiments of the present invention are described above in conjunction with the accompanying drawings, the present invention is not limited to the above-mentioned specific embodiments and application fields, and the above-mentioned specific embodiments are only illustrative and instructive, rather than restrictive. Under the guidance of the specification, a person skilled in the art can also make many forms without departing from the scope of protection of the claims of the present invention, all of which belong to the scope of protection of the present invention.

Claims

1. A multi-source constrained large-scale fracture automatic modeling method, characterized in that: include: Set the crack direction, length and aspect ratio distribution according to the physical properties of the crack; Establish a probability body of crack density spatial distribution based on crack detection data; The fracture network is obtained based on the distribution of fracture direction, length and height and the probability body of fracture density spatial distribution; A fracture model is established based on the fracture network.

2. The multi-source constrained large-scale fracture automatic modeling method according to claim 1 is characterized in that: According to the distribution of fracture direction, length and height and the probability body of fracture density spatial distribution, the fracture network that satisfies the constraints of prior distribution, drilling loss and production test fracture location is obtained as follows: According to the distribution of the crack direction, length and height, the crack direction, length, height and the position of the crack center are randomly sampled; Generate discrete fracture slices based on the fracture density spatial distribution probability volume; Acceptance conditions are set, and the random adoption and generation of discrete fracture slices are repeated, and the distances between the fracture slices and the leakage points and the fracture positions shown by the production test are calculated until the acceptance conditions are met and the fracture network is obtained.

3. The multi-source constrained large-scale fracture automatic modeling method according to claim 2 is characterized in that: The acceptance condition is to calculate the distance between the fracture slice and the leakage point and the fracture position displayed by the production test according to the drilling leakage data and the production test data, and select a certain threshold as the acceptance condition.

4. The multi-source constrained large-scale fracture automatic modeling method according to claim 1 is characterized in that: The fracture network satisfies the prior distribution, drilling loss and production test fracture location constraints.

5. The multi-source constrained large-scale fracture automatic modeling method according to claim 1 is characterized in that: The method of obtaining the fracture model according to the fracture network specifically includes randomly assigning values ​​to the fracture permeabilities according to the fracture network, performing numerical simulation until the matching rate condition is met, and obtaining the fracture model.

6. The multi-source constrained large-scale fracture automatic modeling method according to claim 5, characterized in that: The matching rate condition is: 1-(|Dsim-Dobs|) / Dobs>σ Among them, Dsim is the simulation data, Dobs is the historical data, and σ is the matching rate.

7. The multi-source constrained large-scale fracture automatic modeling method according to claim 1, characterized in that: The fracture detection data includes: seismic coherence body attributes, drilling loss data and production history data.

8. A multi-source constrained large-scale fracture automatic modeling system, characterized in that: include: Setting module: Set the crack direction, length and aspect ratio distribution according to the physical properties of the crack; Establishing module: establishing crack density spatial distribution probability body according to crack detection data; Fracture network acquisition module: obtain the fracture network based on the distribution of fracture direction, length and height and the probability body of fracture density spatial distribution; Modeling module: Establish a fracture model based on the fracture network.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for automatic modeling of large-scale fractures with multi-source constraints as claimed in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for automatic modeling of large-scale fractures with multi-source constraints as claimed in any one of claims 1 to 7 are implemented.

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