A method and apparatus for simulating the uplift process of ancient uplifts based on discrete element method.

Abstract

This invention discloses a method and apparatus for simulating the uplift process of ancient uplifts based on discrete element method (DEM) calculations. The method includes: determining the maximum slope of the fitted curve equation based on the upper boundary of the ancient uplift, thereby determining the initial overlap ratio of the particles; filling a rectangular box model of a second specified size with particles of a first specified size, ensuring the bottom particles have an initial overlap ratio, to obtain a first DEM model; determining the microscopic parameters of the granular materials of each stratum simulated using the first DEM model through biaxial compression experiments; setting the parameters of the first DEM model using the microscopic parameters of the granular materials and strata information to obtain a second DEM model; calculating the uplift vertical velocity of each particle at the bottom of the model based on the vertical velocity of the specified particles and the maximum value of the fitted curve; and simulating the uplift process of each particle at the upper boundary of the ancient uplift according to its uplift vertical velocity. This invention can simulate the uplift process of ancient uplifts with different geometric shapes.

Description

Technical Field

[0001] This invention relates to the field of geological structural deformation simulation research technology, and in particular to a method and apparatus for simulating the uplift process of ancient uplifts based on discrete element method. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] Uplifts are positive tectonic units formed by uplift tectonic movements on the Earth's crust. The sedimentary filling, tectonic deformation, and geological evolution of uplifted areas vary significantly laterally, forming stratigraphic unconformities and extensional tectonic deformation zones, providing important windows for studying crustal structure, continental properties, and evolution. Paleo-uplifts, on the other hand, are a relative concept, referring to uplifted structures at a specific geological stage in the formation and evolution of basins, playing a crucial role in the enrichment of oil and gas resources. Oil and gas exploration practice shows that oil and gas fields, especially large and super-large ones, are often associated with cratonic basins, and paleofrafts and paleo-uplifts play a vital role in the location of these fields. Simulating the uplift process of deep paleo-uplifts in cratonic basins and developing effective prediction techniques can fundamentally solve the challenges of deep structural research, guiding the study of the distribution and evolution of deep uplift and depression structural patterns, and has significant practical exploration value.

[0004] Previous paleouplift simulations have mostly used stable paleouplifts, and there is a lack of simulation studies on the uplift process of paleouplifts. Based on the study of craton margin evolution, accurately controlling the uplift process of paleouplifts and simulating the uplift process of deep paleouplifts in basins can further study the stress and strain distribution of paleouplift slopes and cores and their impact on reservoir properties. Summary of the Invention

[0005] This invention provides a discrete element method for simulating the uplift process of ancient uplifts, used to simulate the uplift process of ancient uplifts with different geometric shapes. This method addresses the challenges of deep structural research from a mechanistic perspective, guides the study of the distribution and evolution of deep uplift and depression structural patterns, and provides theoretical support for deep oil and gas exploration in oil and gas basins. The method includes:

[0006] Based on seismic data, determine the stratigraphic information of the area to be analyzed, as well as the point cloud data coordinates of the upper boundary of the ancient uplift;

[0007] Curve fitting was performed using the coordinates of the point cloud data to obtain the fitted curve equation for the upper boundary of the ancient uplift.

[0008] Based on the fitted curve equation, determine the maximum value of the slope of the fitted curve, and determine the initial overlap rate of the particles based on the maximum value of the slope; fill the rectangular box model of the second specified size with particles of the first specified size, and make the particles at the bottom of the rectangular box model have an initial overlap rate to obtain the first discrete element model.

[0009] Biaxial compression experiments were used to determine the microscopic parameters of granular materials in each stratum simulated by the first discrete element model. The parameters of the granular materials and the strata information of the area to be analyzed were used to set the parameters of the first discrete element model to obtain the second discrete element model.

[0010] The maximum value of the fitted curve is determined based on the fitted curve equation. The vertical velocity of the specified particle is set. The uplift vertical velocity of each particle at the bottom of the second discrete element model, which serves as the upper boundary of the ancient uplift, is calculated based on the vertical velocity of the specified particle and the maximum value of the fitted curve.

[0011] Each particle at the upper boundary of the ancient uplift is raised according to the calculated vertical uplift velocity until the designated particle reaches the designated position, thus completing the simulation of the ancient uplift process. The designated position is the position corresponding to the maximum value of the fitted curve.

[0012] This invention also provides a discrete element method (DEM) simulation device for the uplift process of ancient uplifts, used to simulate the uplift process of ancient uplifts with different geometric shapes. This addresses the challenges of deep structural research from a mechanistic perspective, guides the study of the distribution and evolution of deep uplift and depression structural patterns, and provides theoretical support for deep oil and gas exploration in oil and gas basins. The device includes:

[0013] The determination module is used to determine the stratigraphic information of the area to be analyzed, as well as the point cloud data coordinates of the upper boundary of the ancient uplift, based on seismic data.

[0014] The curve fitting module is used to perform curve fitting using the coordinates of the point cloud data to obtain the fitted curve equation of the upper boundary of the ancient uplift.

[0015] The determination module is also used to determine the maximum value of the slope of the fitted curve according to the fitted curve equation, and to determine the initial overlap rate of the particles according to the maximum value of the slope; the model filling module is used to fill the first specified size of particles into the second specified size rectangular box model, and to make the particles at the bottom of the rectangular box model have an initial overlap rate, so as to obtain the first discrete element model.

[0016] The determination module is also used to determine the microscopic parameters of the granular materials of each stratum simulated by the first discrete element model using biaxial compression experiments; the setting module is used to set the parameters of the first discrete element model using the microscopic parameters of the granular materials and the strata information of the area to be analyzed, so as to obtain the second discrete element model.

[0017] The determination module is also used to determine the maximum value of the fitted curve based on the fitted curve equation, set the vertical velocity of the specified particles, and calculate the uplift vertical velocity of each particle at the bottom of the second discrete element model as the upper boundary of the ancient uplift based on the vertical velocity of the specified particles and the maximum value of the fitted curve.

[0018] The simulation module is used to simulate the uplift process of each particle at the upper boundary of the ancient uplift according to the calculated vertical uplift velocity until the specified particle reaches the specified position. The specified position is the position corresponding to the maximum value of the fitted curve.

[0019] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for simulating the uplift process of ancient uplifts based on discrete element method.

[0020] This invention also provides a computer-readable storage medium storing a computer program that executes the above-described method for simulating the uplift process of ancient uplifts based on discrete element method.

[0021] In this embodiment of the invention, an initial first discrete element model is established using a random particle distribution method. This fully considers the geological characteristics of paleo-uplifts during geological history, determines the microscopic parameters of the particles, and uses these parameters to set the first discrete element model. A second discrete element model is then established, closely resembling the geological morphology of the area to be analyzed during geological history. This second discrete element model simulates the uplift process of the paleo-uplift, thereby studying the impact of this common geological phenomenon on the tectonic deformation of the region. Unlike existing technologies, this embodiment does not require pre-existing faults; instead, it uses discrete particles to construct the model, giving it a particle structure similar to real rock masses. Furthermore, considering that large-scale tectonic physics simulation experiments are often costly and time-consuming, this embodiment uses discrete element models to supplement and replace some experiments, saving time and money. Moreover, this method for studying tectonic evolution and deformation mechanisms based on discrete element simulation can obtain data that is difficult to measure experimentally, thereby improving existing theories to solve practical problems, such as tectonic evolution processes and deformation mechanisms, stress and strain distribution, and their impact on reservoir properties. This provides theoretical support for the evolution of deep paleo-uplifts in oil and gas basins and for oil and gas exploration. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0023] Figure 1 This is a flowchart of a method for simulating the uplift process of ancient uplifts based on discrete element method in an embodiment of the present invention;

[0024] Figure 2(a) is a fitting diagram of the geometric morphology of an ancient uplift in an embodiment of the present invention;

[0025] Figure 2(b) is a schematic diagram of a binary image of the upper boundary of an ancient uplift in an embodiment of the present invention;

[0026] Figure 3 This is a schematic diagram of particles being randomly filled into a rectangular box of a given size in an embodiment of the present invention;

[0027] Figure 4 This is a schematic diagram illustrating the definition of overlap ratio in an embodiment of the present invention;

[0028] Figure 5 This is a schematic diagram of a method for determining the overlap ratio in an embodiment of the present invention;

[0029] Figure 6 This is a schematic diagram of a second discrete element model in an embodiment of the present invention;

[0030] Figure 7 This is a schematic diagram of the uplift of ancient uplift particles for velocity value taking in an embodiment of the present invention;

[0031] Figure 8 This is a schematic diagram of stratigraphic deformation during the uplift of a paleo-uplift, as illustrated in an embodiment of the present invention.

[0032] Figure 9 This is a schematic diagram of strata deformation during the uplift of an ancient uplift, using another discrete element model in this embodiment of the invention.

[0033] Figure 10 This is a schematic diagram of the structure of a discrete element method-based simulation device for the uplift process of ancient uplifts in an embodiment of the present invention.

[0034] Figure 11 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0036] The discrete element method treats geological bodies as discrete units, allowing for large relative displacements between particles. It can better simulate high-degree deformation and is suitable for studying the discontinuous mechanical behavior of brittle deformations such as faults and fault-related folds in sedimentary strata. It is an important method for studying the uplift process of ancient uplifts.

[0037] This invention provides a method for simulating the uplift process of ancient uplifts based on discrete element method, such as... Figure 1 As shown, the method includes the following steps 101 to 106:

[0038] Step 101: Based on the seismic data, determine the stratigraphic information of the area to be analyzed, as well as the point cloud data coordinates of the upper boundary of the ancient uplift.

[0039] Stratigraphic information includes details such as the type and thickness of strata within the area to be analyzed. Besides seismic data, stratigraphic information can also be determined through observation.

[0040] Specifically, determining the point cloud coordinates of the upper boundary of an ancient uplift based on seismic data can be performed as follows: Analyze the seismic data to obtain a seismic analysis map, and then obtain the geometric shape of the ancient uplift in the area to be analyzed from the seismic analysis map; next, binarize the geometric shape map to obtain a binary image of the ancient uplift; based on the binary image, using boundary recognition technology in image processing, the upper boundary of the ancient uplift and its point cloud coordinates can be determined.

[0041] For example, Figure 2(a) is a fitting image of the geometry of an ancient uplift, and the binary image obtained from the fitting image is shown in Figure 2(b).

[0042] Step 102: Use the point cloud data coordinates to perform curve fitting to obtain the fitted curve equation of the upper boundary of the ancient uplift.

[0043] Among them, a suitable curve is selected for fitting based on the morphology of the upper boundary of the ancient uplift. Specifically, the following curve equation can be selected for fitting:

[0044] ① Polynomial: y = a n (x-x0) n +a n-1 (x-x0) n-1 +...+a1(x-x0) 1 +a0+y0

[0045] ② Circle: (x-x0) 2 +(y-y0) 2 =r 2

[0046] ③ Sine curve: y=Asin[ω(x-x0)]+y0

[0047] Where x represents the x-coordinate, y represents the y-coordinate, (x0, y0) is the coordinate value of the starting point of the left end of the upper boundary of the ancient uplift, and n represents the degree of the polynomial, a1, a2…a n Let ω represent the coefficients of the polynomial, r represent the radius of the circle, and A and ω are constants.

[0048] Step 103: Determine the maximum value of the slope of the fitted curve according to the fitted curve equation, and determine the initial overlap rate of the particles according to the maximum value of the slope; fill the rectangular box model of the second specified size with particles of the first specified size, and make the particles at the bottom of the rectangular box model have an initial overlap rate to obtain the first discrete element model.

[0049] The first specified size of particles includes two sizes. In this embodiment of the invention, 60 μm and 80 μm particles are selected. To better simulate the uplift process of the ancient uplift, the two sizes of particles can be filled into a rectangular box model of the second specified size according to a set ratio. The set ratio can be set according to the actual observation needs, such as setting the ratio of 80 μm particles to 60 μm particles to 1:1, 2:1, 3:1, etc.

[0050] The second specified size can be set by the user. The larger the second specified model, the larger the model of the region to be analyzed can be constructed. The specific size of the model of the region to be analyzed is determined by the number of particles filled in, which is determined by the user according to actual needs.

[0051] For example, a rectangular box-shaped model filled with particles, such as Figure 3 As shown. The particles filling the rectangular box-shaped model accumulate at the bottom of the model under gravity, possessing an initial overlap ratio. The initial overlap ratio is defined as:

[0052] cratio = 1.0 - |AO| / (r A +r O )

[0053] Where |AO| represents the distance between the centers of particles A and O, r A Let r represent the radius of particle A. O Represents the radius of particle O, (r A +r O ) indicates the equilibrium distance.

[0054] Theoretically, the initial overlap ratio ranges from 0.0 to 1.0. See [link / reference]. Figure 4 As the overlap area of ​​the two particles increases, the overlap rate also increases.

[0055] In this embodiment of the invention, to avoid the increase in the gaps between particles due to the uplift process, thereby preventing the occurrence of... Figure 5As shown, when particle A moves to position A', particle A completely separates from particle O. Therefore, it is necessary to limit the initial overlap ratio of the particles filled into the rectangular box model, and also limit the displacement and rotational angular velocity of the particles constituting the ridge. Specifically, the minimum overlap ratio C of the particles is calculated according to the following formula:

[0056]

[0057] Where k represents the maximum slope of the fitted curve at the upper boundary of the ancient uplift.

[0058] Since the overlap ratio ranges from 0.0 to 1, any value can be arbitrarily selected from the minimum overlap ratio C to 1 as the initial overlap ratio of the particles.

[0059] The first discrete element model can be a contact model provided in the prior art, such as the Hertz-Mindlin model.

[0060] Step 104: Use biaxial compression experiments to determine the microscopic parameters of the granular materials in each stratum simulated by the first discrete element model; use the microscopic parameters of the granular materials and the strata information of the area to be analyzed to set the parameters of the first discrete element model to obtain the second discrete element model.

[0061] Microscopic parameters of granular materials are used to simulate rock deformation in actual strata. These parameters include particle radius, particle density, particle shear modulus, particle Poisson's ratio, particle friction coefficient, local damping coefficient, and interparticle bonding parameters. Among these, interparticle bonding parameters include bonded Young's modulus, bonded shear modulus, bonded tensile strength, and bonded shear strength.

[0062] Microscopic parameters of granular materials can be obtained using biaxial compression tests. For example, the parameters used in this embodiment of the invention are: particle radii of 60 μm and 80 μm, and particle density of 2500 km / m³. 3 The elastic modulus of the particles is 2.9e9 Pa, the Poisson's ratio is 0.2, the local damping coefficient is 0.4, the particle friction coefficient in the deposition stage is 0.0, and the particle friction coefficient in the uplift stage is set to 0.3.

[0063] The interparticle bonding parameters are as follows: the Young's modulus of bonding is 2.0e8 Pa, the shear modulus of bonding is 2.0e8 Pa, the tensile strength of bonding ranges from 0.0 to 4.0e7 Pa, and the shear strength of bonding ranges from 0.0 to 8.0e7 Pa. The initial bonding condition between particles is |AO|-(r A +r O )≤tolerate, where tolerate is 1e-6.

[0064] The second discrete element model reflects the actual stratigraphic characteristics of the area to be analyzed where the ancient uplift is located. It simulates the area to be analyzed where no uplift has occurred, such as... Figure 6 The diagram shown is a schematic of a second discrete element model, in which different strata are identified by different colors.

[0065] Step 105: Determine the maximum value of the fitted curve based on the fitted curve equation, set the vertical velocity of the specified particles, and calculate the uplift vertical velocity of each particle at the bottom of the second discrete element model, which serves as the upper boundary of the ancient uplift, based on the vertical velocity of the specified particles and the maximum value of the fitted curve.

[0066] The specified particle is the particle at the location where the fitted curve reaches its maximum value.

[0067] Since the uplift of the bottom particles naturally drives the uplift of the upper particles, in this embodiment of the invention, it is only necessary to calculate the vertical uplift velocity of each particle at the bottom of the second discrete element model, which serves as the upper boundary of the ancient uplift. For example, Figure 7 A schematic diagram of the bottom particle elevation is provided.

[0068] Specifically, the vertical uplift velocity v of the i-th particle at the bottom of the second discrete element model, which serves as the upper boundary of the ancient uplift, is calculated according to the following formula. i :

[0069]

[0070] Among them, v j Indicates the vertical velocity of a specified particle; y i This represents the maximum value of the fitted curve; y i This indicates that when the x-coordinate is x i At that time, the ordinate value of the fitted curve at the upper boundary of the ancient uplift, x i y0 represents the x-coordinate of the i-th particle's location when using the same coordinate system with the same origin; y0 represents the y-coordinate of the starting point at the left end of the upper boundary of the ancient uplift.

[0071] Where the x-coordinate is x i When (i=1,2,...,n), the ordinate value y of the fitted curve of the upper boundary of the ancient uplift i Calculate using the following formula:

[0072] ① Polynomial: y i =a n (x i -x0) n +a n-1 (x i -x0) n-1 +...+a1(x i -x0) 1 +a0+y0

[0073] ② Circle:

[0074] ③ Sine curve: y i =Asin[ω(x) i -x0)]+y0

[0075] Step 106: Uplift each particle at the upper boundary of the ancient uplift according to the calculated vertical uplift velocity until the designated particle reaches the designated position, thus completing the simulation of the ancient uplift process.

[0076] The designated location corresponds to the maximum value of the fitted curve. As each particle at the upper boundary of the paleo-uplift rises, it interacts with particles in the strata above it. The calculation stops when the particles at the upper boundary of the paleo-uplift reach the designated location, thus completing the simulation of the entire uplift process.

[0077] To limit the uplift process of the particles, displacement boundary conditions can be set based on the geometry of the paleo-uplift obtained in step 101, and compression, deposition and erosion can be added to make the particles uplift within the displacement boundary conditions, thereby simulating real geological events.

[0078] For example, see Figure 8 and Figure 9 , Figure 8 This is a schematic diagram of stratigraphic deformation during the uplift of a paleo-uplift using a discrete element model. Figure 9 This is a schematic diagram of stratigraphic deformation during the uplift of an ancient uplift using another discrete element model. The simulation of the ancient uplift process is complete when the height of the grain uplift at the bottom of the second discrete element reaches the height of the upper boundary of the ancient uplift.

[0079] In this embodiment of the invention, an initial first discrete element model is established using a random particle distribution method. This fully considers the geological characteristics of paleo-uplifts during geological history, determines the microscopic parameters of the particles, and uses these parameters to set the first discrete element model. A second discrete element model is then established, closely resembling the geological morphology of the area to be analyzed during geological history. This second discrete element model simulates the uplift process of the paleo-uplift, thereby studying the impact of this common geological phenomenon on the tectonic deformation of the region. Unlike existing technologies, this embodiment does not require pre-existing faults; instead, it uses discrete particles to construct the model, giving it a particle structure similar to real rock masses. Furthermore, considering that large-scale tectonic physics simulation experiments are often costly and time-consuming, this embodiment uses discrete element models to supplement and replace some experiments, saving time and money. Moreover, this method for studying tectonic evolution and deformation mechanisms based on discrete element simulation can obtain data that is difficult to measure experimentally, thereby improving existing theories to solve practical problems, such as tectonic evolution processes and deformation mechanisms, stress and strain distribution, and their impact on reservoir properties. This provides theoretical support for the evolution of deep paleo-uplifts in oil and gas basins and for oil and gas exploration.

[0080] This invention also provides a device for simulating the uplift process of ancient uplifts based on discrete element method (EMI), as described in the following embodiments. Since the principle by which this device solves the problem is similar to the method for simulating the uplift process of ancient uplifts based on discrete element method, the implementation of this device can refer to the implementation of the method for simulating the uplift process of ancient uplifts based on discrete element method; repeated details will not be elaborated further.

[0081] like Figure 10 As shown, the device 1000 includes a determination module 1001, a curve fitting module 1002, a model filling module 1003, a setting module 1004, and a simulation module 1005.

[0082] Among them, the determination module 1001 is used to determine the stratigraphic information of the area to be analyzed, as well as the point cloud data coordinates of the upper boundary of the ancient uplift, based on the seismic data.

[0083] The curve fitting module 1002 is used to perform curve fitting using point cloud data coordinates to obtain the fitted curve equation of the upper boundary of the ancient uplift.

[0084] The determination module 1001 is also used to determine the maximum value of the slope of the fitted curve according to the fitted curve equation, and to determine the initial overlap rate of the particles according to the maximum value of the slope; the model filling module 1003 is used to fill the first specified size of particles into the second specified size of the rectangular box model, and to make the particles at the bottom of the rectangular box model have an initial overlap rate, so as to obtain the first discrete element model.

[0085] The determination module 1001 is also used to determine the microscopic parameters of the granular materials of each stratum simulated by the first discrete element model by using biaxial compression experiments; the setting module 1004 is used to set the parameters of the first discrete element model by using the microscopic parameters of the granular materials and the stratum information of the area to be analyzed, so as to obtain the second discrete element model.

[0086] The determination module 1001 is also used to determine the maximum value of the fitting curve according to the fitting curve equation, set the vertical velocity of the specified particle, and calculate the uplift vertical velocity of each particle at the bottom of the second discrete element model as the upper boundary of the ancient uplift according to the vertical velocity of the specified particle and the maximum value of the fitting curve.

[0087] The simulation module 1005 is used to simulate the uplift process of each particle at the upper boundary of the ancient uplift according to the calculated vertical uplift velocity until the specified particle reaches the specified position. The specified position is the position corresponding to the maximum value of the fitted curve.

[0088] In one implementation of this invention, the determining module 1001 is configured to:

[0089] Seismic data is analyzed to obtain seismic analysis maps, which determine the geometric morphology of ancient uplifts in the area to be analyzed.

[0090] The geometric morphology image is binarized to obtain a binary image of the ancient uplift;

[0091] Based on the binary image, determine the upper boundary of the ancient uplift and the point cloud data coordinates of the upper boundary of the ancient uplift.

[0092] In one implementation of this invention, the determining module 1001 is configured to:

[0093] according to Calculate the minimum overlap rate C, where k represents the maximum slope;

[0094] Choose any value from the minimum overlap rate to 1 as the initial overlap rate of the particles.

[0095] In one implementation of this invention, the microscopic parameters of the particulate material include the particle radius, particle density, particle shear modulus, particle Poisson's ratio, particle friction coefficient, local damping coefficient, and interparticle bonding parameters; wherein, the interparticle bonding parameters include the bonding Young's modulus, bonding shear modulus, bonding tensile strength, and bonding shear strength.

[0096] In one implementation of this invention, the determining module 1001 is configured to:

[0097] according to Calculate the vertical uplift velocity v of the i-th particle at the bottom of the second discrete element model, which serves as the upper boundary of the ancient uplift. i ;

[0098] Among them, v j Indicates the vertical velocity of a specified particle; y i This represents the maximum value of the fitted curve; y i This indicates that when the x-coordinate is x i At that time, the ordinate value of the fitted curve at the upper boundary of the ancient uplift, x i y0 represents the x-coordinate of the i-th particle's location when using the same coordinate system with the same origin; y0 represents the y-coordinate of the starting point at the left end of the upper boundary of the ancient uplift.

[0099] In one implementation of this invention, the first specified size of particles includes two sizes of particles, and the model filling module is used for:

[0100] Two sizes of particles are filled into a rectangular box-shaped model of a second specified size according to a set ratio.

[0101] In this embodiment of the invention, an initial first discrete element model is established using a random particle distribution method. This fully considers the geological characteristics of paleo-uplifts during geological history, determines the microscopic parameters of the particles, and uses these parameters to set the first discrete element model. A second discrete element model is then established, closely resembling the geological morphology of the area to be analyzed during geological history. This second discrete element model simulates the uplift process of the paleo-uplift, thereby studying the impact of this common geological phenomenon on the tectonic deformation of the region. Unlike existing technologies, this embodiment does not require pre-existing faults; instead, it uses discrete particles to construct the model, giving it a particle structure similar to real rock masses. Furthermore, considering that large-scale tectonic physics simulation experiments are often costly and time-consuming, this embodiment uses discrete element models to supplement and replace some experiments, saving time and money. Moreover, this method for studying tectonic evolution and deformation mechanisms based on discrete element simulation can obtain data that is difficult to measure experimentally, thereby improving existing theories to solve practical problems, such as tectonic evolution processes and deformation mechanisms, stress and strain distribution, and their impact on reservoir properties. This provides theoretical support for the evolution of deep paleo-uplifts in oil and gas basins and for oil and gas exploration.

[0102] This invention also provides a computer device. Figure 11 This is a schematic diagram of a computer device in an embodiment of the present invention. This computer device is capable of implementing all steps in the discrete element method for simulating the uplift process of ancient uplifts in the above embodiments. Specifically, the computer device includes the following components:

[0103] Processor 1101, memory 1102, communications interface 1103, and communication bus 1104;

[0104] The processor 1101, memory 1102, and communication interface 1103 communicate with each other through the communication bus 1104; the communication interface 1103 is used to realize information transmission between related devices.

[0105] The processor 1101 is used to call the computer program in the memory 1102. When the processor executes the computer program, it implements the discrete element method for simulating the uplift process of ancient uplifts in the above embodiments.

[0106] This invention also provides a computer-readable storage medium storing a computer program that executes the above-described method for simulating the uplift process of ancient uplifts based on discrete element method.

[0107] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0108] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0109] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0110] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0111] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for simulating the uplift process of ancient uplifts based on discrete element method, characterized in that, The method includes: Based on seismic data, determine the stratigraphic information of the area to be analyzed, as well as the point cloud data coordinates of the upper boundary of the ancient uplift; Curve fitting was performed using the coordinates of the point cloud data to obtain the fitted curve equation for the upper boundary of the ancient uplift. Based on the fitted curve equation, determine the maximum value of the slope of the fitted curve, and determine the initial overlap rate of the particles based on the maximum value of the slope; fill the rectangular box model of the second specified size with particles of the first specified size, and make the particles at the bottom of the rectangular box model have an initial overlap rate to obtain the first discrete element model. Biaxial compression experiments were used to determine the microscopic parameters of granular materials in each stratum simulated by the first discrete element model. The parameters of the granular materials and the strata information of the area to be analyzed were used to set the parameters of the first discrete element model to obtain the second discrete element model. The maximum value of the fitted curve is determined based on the fitted curve equation. The vertical velocity of the specified particle is set. The uplift vertical velocity of each particle at the bottom of the second discrete element model, which serves as the upper boundary of the ancient uplift, is calculated based on the vertical velocity of the specified particle and the maximum value of the fitted curve. Each particle at the upper boundary of the ancient uplift is raised according to the calculated vertical uplift velocity until the designated particle reaches the designated position, thus completing the simulation of the ancient uplift process. The designated position is the position corresponding to the maximum value of the fitted curve.

2. The method according to claim 1, characterized in that, Based on seismic data, the point cloud coordinates of the upper boundary of the ancient uplift were determined, including: Seismic data is analyzed to obtain seismic analysis maps, which determine the geometric morphology of ancient uplifts in the area to be analyzed. The geometric morphology image is binarized to obtain a binary image of the ancient uplift; Based on the binary image, the upper boundary of the ancient uplift and the point cloud data coordinates of the upper boundary of the ancient uplift are determined.

3. The method according to claim 1, characterized in that, The initial overlap ratio of the particles is determined based on the maximum slope, including: according to Calculate the minimum overlap rate C, where k represents the maximum slope; Choose any value from the minimum overlap rate to 1 as the initial overlap rate of the particles.

4. The method according to claim 1, characterized in that, The microscopic parameters of particulate materials include particle radius, particle density, particle shear modulus, particle Poisson's ratio, particle friction coefficient, local damping coefficient, and interparticle bonding parameters; among which, interparticle bonding parameters include bond Young's modulus, bond shear modulus, bond tensile strength, and bond shear strength.

5. The method according to any one of claims 1 to 4, characterized in that, The uplift vertical velocity of each particle at the bottom of the second discrete element model, which serves as the upper boundary of the paleo-uplift, is calculated based on the vertical velocity of the specified particles and the maximum value of the fitted curve. This includes: according to Calculate the vertical uplift velocity v of the i-th particle at the bottom of the second discrete element model, which serves as the upper boundary of the ancient uplift. i ; Among them, v j Indicates the vertical velocity of a specified particle; y i This represents the maximum value of the fitted curve; y i This indicates that when the x-coordinate is x i At that time, the ordinate value of the fitted curve at the upper boundary of the ancient uplift, x i y0 represents the x-coordinate of the i-th particle's location when using the same coordinate system with the same origin; y0 represents the y-coordinate of the starting point at the left end of the upper boundary of the ancient uplift.

6. The method according to claim 1, characterized in that, The first specified size of particles includes two sizes of particles. The particles of the first specified size are filled into a rectangular box-shaped model of the second specified size, including: Two sizes of particles are filled into a rectangular box-shaped model of a second specified size according to a set ratio.

7. A device for simulating the uplift process of ancient uplifts based on discrete element method, characterized in that, The device includes: The determination module is used to determine the stratigraphic information of the area to be analyzed, as well as the point cloud data coordinates of the upper boundary of the ancient uplift, based on seismic data. The curve fitting module is used to perform curve fitting using the coordinates of the point cloud data to obtain the fitted curve equation of the upper boundary of the ancient uplift. The determination module is also used to determine the maximum value of the slope of the fitted curve according to the fitted curve equation, and to determine the initial overlap rate of the particles according to the maximum value of the slope; the model filling module is used to fill the first specified size of particles into the second specified size rectangular box model, and to make the particles at the bottom of the rectangular box model have an initial overlap rate, so as to obtain the first discrete element model. The determination module is also used to determine the microscopic parameters of the granular materials of each stratum simulated by the first discrete element model using biaxial compression experiments; the setting module is used to set the parameters of the first discrete element model using the microscopic parameters of the granular materials and the strata information of the area to be analyzed, so as to obtain the second discrete element model. The determination module is also used to determine the maximum value of the fitted curve based on the fitted curve equation, set the vertical velocity of the specified particles, and calculate the uplift vertical velocity of each particle at the bottom of the second discrete element model as the upper boundary of the ancient uplift based on the vertical velocity of the specified particles and the maximum value of the fitted curve. The simulation module is used to simulate the uplift process of each particle at the upper boundary of the ancient uplift according to the calculated vertical uplift velocity until the specified particle reaches the specified position. The specified position is the position corresponding to the maximum value of the fitted curve.

8. The apparatus according to claim 7, characterized in that, The determination module is used for: Seismic data is analyzed to obtain seismic analysis maps, which determine the geometric morphology of ancient uplifts in the area to be analyzed. The geometric morphology image is binarized to obtain a binary image of the ancient uplift; Based on the binary image, the upper boundary of the ancient uplift and the point cloud data coordinates of the upper boundary of the ancient uplift are determined.

9. The apparatus according to claim 7, characterized in that, The determination module is used for: according to Calculate the minimum overlap rate C, where k represents the maximum slope; Choose any value from the minimum overlap rate to 1 as the initial overlap rate of the particles.

10. The apparatus according to claim 7, characterized in that, The microscopic parameters of particulate materials include particle radius, particle density, particle shear modulus, particle Poisson's ratio, particle friction coefficient, local damping coefficient, and interparticle bonding parameters; among which, interparticle bonding parameters include bond Young's modulus, bond shear modulus, bond tensile strength, and bond shear strength.

11. The apparatus according to any one of claims 7 to 10, characterized in that, The determination module is used for: according to Calculate the vertical uplift velocity v of the i-th particle at the bottom of the second discrete element model, which serves as the upper boundary of the ancient uplift. i ; Among them, v j Indicates the vertical velocity of a specified particle; y i This represents the maximum value of the fitted curve; y i This indicates that when the x-coordinate is x i At that time, the ordinate value of the fitted curve at the upper boundary of the ancient uplift, x i y0 represents the x-coordinate of the i-th particle's location when using the same coordinate system with the same origin; y0 represents the y-coordinate of the starting point at the left end of the upper boundary of the ancient uplift.

12. The apparatus according to claim 7, characterized in that, The first specified particle size includes two particle sizes, and the model filling module is used for: Two sizes of particles are filled into a rectangular box-shaped model of a second specified size according to a set ratio.

13. 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, it implements the method of any one of claims 1 to 6.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that performs the method of any one of claims 1 to 6.

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