Numerical simulation method and system for carbonate rock sedimentation process

Abstract

The present invention provides a method and system for numerical simulation of carbonate rock deposition, comprising the following steps: step 1, constructing a planar grid model including multiple grid points based on the actual study area; step 2, obtaining environmental physical parameters, population parameters, and the population size of each grid point at the current deposition simulation time, and determining the current population size of each grid point at the current deposition simulation time based on a Generalized Lotka-Volterra model applicable to multiple species; step 3, determining the carbonate rock deposition thickness based on a carbonate rock vertical yield model; step 4, determining the depositional topography at the previous deposition simulation time, and obtaining the current depositional landform; step 5, using the current depositional landform as the depositional topography at the next deposition simulation time, using the current population size as the population size at the next deposition simulation time, and repeating steps 2 to 4 until the deposition simulation ends. The present invention improves the rationality and accuracy of numerical simulation of carbonate rock deposition.

Description

Technical Field

[0001] The present invention relates to the technical field of carbonate rock deposition, and in particular to a method and system for numerical simulation of carbonate rock deposition process. Background Art

[0002] In traditional geological research, carbonate reservoirs, as one of the important types of petroleum reservoirs, have important research significance for petroleum exploration and development. Modern sedimentary surveys have shown that the carbonate rock deposition process is closely related to biological activities.

[0003] Existing numerical simulation technologies for carbonate rock deposition only use random methods or consider only the relationship between a single organism and its environment, without considering the internal competition among the same biological population and the impact of interactions among multiple species on the carbonate rock deposition process. This results in a lack of rationality in the numerical simulation of the carbonate rock deposition process and inaccurate simulation results.

[0004] Therefore, there is an urgent need to propose a numerical simulation method and system for carbonate rock deposition process to solve the technical problems in the existing technology of unreasonable numerical simulation of carbonate rock deposition process and inaccurate simulation results. Summary of the Invention

[0005] In view of this, it is necessary to provide a method and system for numerical simulation of carbonate rock deposition process to solve the technical problems existing in the prior art of unreasonable numerical simulation of carbonate rock deposition process and inaccurate simulation results.

[0006] In one aspect, the present invention provides a method for numerically simulating carbonate rock deposition, comprising:

[0007] Step 1: constructing a plane grid model according to the actual research area, wherein the plane grid model includes a plurality of grid points;

[0008] Step 2: Obtain environmental physical parameters and population parameters at the current deposition simulation time, as well as the population size of each grid point at the previous deposition simulation time, and determine the current population size of each grid point at the current deposition simulation time based on a Generalized Lotka-Volterra model applicable to multiple species, the environmental physical parameters, the population parameters, and the population size at the previous deposition simulation time;

[0009] Step 3: determining the carbonate rock biological productivity at the current deposition simulation time based on the carbonate rock vertical productivity model and the current population size, and determining the carbonate rock deposition thickness at the current deposition simulation time based on the carbonate rock biological productivity;

[0010] Step 4: Determine the sedimentary topography at the last sedimentary simulation time, superimpose the carbonate rock deposition thickness on the sedimentary topography, and obtain the current sedimentary landform at the current sedimentary simulation time;

[0011] Step 5: Use the current sedimentary landform as the sedimentary landform at the next sedimentary simulation moment, use the next sedimentary simulation moment as the current sedimentary simulation moment, use the current population size as the population size at the next sedimentary simulation moment, and repeat steps 2 to 4 until the end of the sedimentary simulation to obtain the carbonate rock deposition process in the actual study area.

[0012] In some possible implementations,

[0013] The population parameters include the inherent birth rate and inherent mortality rate of each species, the carrying capacity of the environment for each species, the population migration rate of each species, and a community matrix describing the interactions between species, wherein each element in the population matrix is ​​the competition coefficient between two species; the second step includes:

[0014] Determining a grid evolution rule based on the inherent birth rate, inherent death rate, environmental carrying capacity for each species, population migration rate of each species, the community matrix, and the population size of each grid point at the last sedimentation simulation time;

[0015] The population size of each grid point in the plurality of grid points at the current deposition simulation moment is determined based on the Generalized Lotka-Volterra model and the grid evolution rule.

[0016] In some possible implementations, the environmental physical parameter includes environmental carrying capacity; and the Generalized Lotka-Volterra model is:

[0017]

[0018] Where N i is the population size of species i at each grid point at the last deposition simulation moment; t is time; R i is the intrinsic birth rate of species i; K i is the carrying capacity of the environment for the i-th species; N is the number of species; A ij is the competition coefficient of the jth species to the ith species; M i is the intrinsic mortality rate of species i; I i is the population migration rate of species i.

[0019] In some possible implementations, species include predators and prey, and the grid evolution rule is:

[0020]

[0021]

[0022]

[0023] Where X is the grid point occupied by prey; Y is the grid point occupied by prey; S is the grid point not occupied by any species; p1 is the predation rate of predators on prey; p2 is the intrinsic mortality rate of predators; p3 is the intrinsic birth rate of prey; p1, p2, and p3 are real-time satisfied by the Generalized Lotka-Volterra model.

[0024] In some possible implementations, the vertical carbonate rock yield model includes a benthic organism carbonate rock yield model, and the carbonate rock deposition thickness includes a benthic organism carbonate rock deposition thickness; the benthic organism carbonate rock yield model is:

[0025] E(x,y)=e x,y *t s *R x,y

[0026]

[0027] Where E(x,y) is the thickness of benthic carbonate sediments; e x,y is the carbonate accumulation rate of benthic organisms; t s is the current deposition compensation; R x,y is the yield coefficient; e m is the maximum accumulation rate of the lithofacies at the (x, y) grid point; I0 ​​is the surface light intensity; I k is the saturation light intensity; k e is the biological extinction coefficient; wd (x,y) is the water depth at the (x,y) grid point.

[0028] In some possible implementations, the carbonate rock vertical yield model further includes a deep-sea pelagic zone carbonate rock yield model, and the carbonate rock deposition thickness further includes a deep-sea pelagic zone carbonate rock deposition thickness; the deep-sea pelagic zone carbonate rock yield model is:

[0029]

[0030] Where P(x,y) is the thickness of carbonate sediments in the deep-sea pelagic zone; P max The maximum carbonate production in the deep-sea pelagic zone; P f is the exponential decay coefficient.

[0031] In some possible implementations, determining the depositional topography at the last deposition simulation time includes:

[0032] Obtaining a simulated terrain grid model corresponding to the actual study area at the last deposition simulation moment, the simulated terrain grid model including a plurality of terrain grids and settlement values ​​and uplift values ​​of each terrain grid;

[0033] The sedimentary topography at the last sedimentation simulation moment is determined according to the settlement value and the uplift value.

[0034] In some possible implementations, before step 5, the method further includes:

[0035] Determine the sea level at the last deposition simulation moment;

[0036] The water depth at each grid point is determined based on the sea level at the last deposition simulation time and the deposition topography at the last deposition simulation time.

[0037] In some possible implementations, determining the sea level at the last deposition simulation time includes:

[0038] Obtain simulated sea level models;

[0039] The sea level height at the last deposition simulation time is determined based on the sea level model.

[0040] On the other hand, the present invention also provides a numerical simulation system for carbonate rock deposition process, comprising:

[0041] A grid model construction unit, configured to construct a plane grid model according to an actual research area, wherein the plane grid model includes a plurality of grid points;

[0042] a biological community determination unit, configured to obtain environmental physical parameters and population parameters at a current deposition simulation time, and the population size of each grid point at a previous deposition simulation time, and determine a current population size of each grid point at the current deposition simulation time based on a Generalized Lotka-Volterra model applicable to multiple species, the environmental physical parameters, the population parameters, and the population size at the previous deposition simulation time;

[0043] a carbonate rock deposition thickness determination unit, configured to determine the carbonate rock biological yield at a current deposition simulation time based on a carbonate rock vertical yield model and the current population size, and to determine the carbonate rock deposition thickness at the current deposition simulation time based on the carbonate rock biological yield;

[0044] a current sedimentary landform determination unit, configured to determine the sedimentary landform at the last sedimentary simulation moment, superimpose the carbonate rock deposition thickness onto the sedimentary landform, and obtain the current sedimentary landform at the current sedimentary simulation moment;

[0045] The sedimentation process determination unit is used to use the current sedimentary landform as the sedimentary landform at the next sedimentation simulation moment, the next sedimentation simulation moment as the current sedimentation simulation moment, and the current population size as the population size at the next sedimentation simulation moment, and repeat steps 2 to 4 until the end of the sedimentation simulation, thereby obtaining the carbonate rock sedimentation process in the actual study area.

[0046] The beneficial effects of the above-described embodiment are as follows: the numerical simulation method for carbonate rock deposition provided by the present invention determines the population size of each grid point at the current deposition simulation moment through a Generalized Lotka-Volterra model applicable to multiple species. Since the Generalized Lotka-Volterra model can be used to simulate direct competition and nutritional relationships between any number of species, the internal competition relationships within the same biological population and the effects of interactions between multiple species can be considered during the carbonate rock deposition process, thereby improving the rationality and accuracy of the resulting carbonate rock deposition process. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 work.

[0048] Figure 1 A schematic flow chart of an embodiment of the numerical simulation method for carbonate rock deposition process provided by the present invention;

[0049] Figure 2 A schematic structural diagram of an embodiment of the plane grid model provided by the present invention;

[0050] Figure 3 For the present invention Figure 1 A schematic flow chart of an embodiment of S102;

[0051] Figure 4 For the present invention Figure 1 A schematic flow chart of an embodiment of determining the depositional topography at the last deposition simulation moment in S104;

[0052] Figure 5 A schematic structural diagram of an embodiment of a simulated terrain grid model provided by the present invention;

[0053] Figure 6 A schematic diagram of a flow chart of an embodiment of determining the water depth at each grid point provided by the present invention;

[0054] Figure 7For the present invention Figure 6 A schematic flow chart of an embodiment of S601;

[0055] Figure 8 This is a schematic structural diagram of an embodiment of the numerical simulation system for carbonate rock deposition process provided by the present invention. DETAILED DESCRIPTION

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0057] It should be understood that the schematic drawings are not drawn to scale. The flowcharts used in the present invention illustrate operations implemented according to some embodiments of the present invention. It should be understood that the operations in the flowcharts may be implemented out of sequence, and steps that do not have a logical contextual relationship may be reversed or performed simultaneously. In addition, those skilled in the art, guided by the present disclosure, may add one or more additional operations to the flowcharts or remove one or more operations from the flowcharts.

[0058] Some of the blocks shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor systems and / or microcontroller systems.

[0059] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0060] The embodiments of the present invention provide a method and system for numerical simulation of carbonate rock deposition process, which are described below.

[0061] Figure 1 A flow chart of an embodiment of the numerical simulation method for carbonate rock deposition process provided by the present invention is shown as follows: Figure 1 As shown in Figure 2, the numerical simulation methods for carbonate rock deposition process include:

[0062] S101. construct a plane grid model according to the actual research area, where the plane grid model includes multiple grid points;

[0063] S102, obtaining environmental physical parameters and population parameters at the current deposition simulation time, as well as the population size of each grid point at the previous deposition simulation time, and determining the current population size of each grid point among the multiple grid points at the current deposition simulation time based on a Generalized Lotka-Volterra (GLV) model applicable to multiple species, environmental physical parameters, population parameters, and the population size of each grid point at the previous deposition simulation time;

[0064] S103, determining the carbonate rock biological yield at the current deposition simulation time based on the carbonate rock vertical yield model and the current population size, and determining the carbonate rock deposition thickness at the current deposition simulation time based on the carbonate rock biological yield;

[0065] S104, determining the sedimentary topography at the last sedimentary simulation time, superimposing the carbonate rock deposition thickness onto the sedimentary topography at the last sedimentary simulation time, and obtaining the current sedimentary landform at the current sedimentary simulation time;

[0066] S105. Use the current sedimentary landform as the sedimentary landform at the next sedimentary simulation moment, use the next sedimentary simulation moment as the current sedimentary simulation moment, use the current population size as the population size at the next sedimentary simulation moment, and repeat steps S102 to S104 until the end of the sedimentary simulation, thereby obtaining the carbonate rock deposition process in the actual study area.

[0067] Compared with the prior art, the numerical simulation method for carbonate rock deposition provided by the embodiments of the present invention uses the Generalized Lotka-Volterra model to determine the population size of each grid point at the current deposition simulation time. Since the Generalized Lotka-Volterra model can be used to simulate direct competition and nutritional relationships between any number of species, the internal competition relationships within the same biological population and the effects of interactions between multiple species can be considered during the carbonate rock deposition process, thereby improving the rationality and accuracy of the resulting carbonate rock deposition process.

[0068] It should be noted that the interval between the last deposition simulation moment and the current deposition simulation moment is a preset time step, wherein the preset time step can be adjusted according to the experience value or the actual scenario, and is not specifically limited here.

[0069] In some embodiments of the present invention, the plane grid model is a square orthogonal grid model, specifically, Figure 2 As shown, the plane mesh model includes 10×10 grid points.

[0070] In some embodiments of the present invention, population parameters include the inherent birth rate of each species, the inherent mortality rate, the carrying capacity of the environment for each species, the population migration rate of each species, and a community matrix describing the interaction between species, where each element in the population matrix is ​​the competition coefficient between two species; Figure 3 As shown, step S102 includes:

[0071] S301, determining a grid evolution rule based on the inherent birth rate and inherent mortality rate of each species, the carrying capacity of the environment for each species, the population migration rate of each species, and a community matrix describing the interactions between species, where each element in the community matrix is ​​a competition coefficient between two species;

[0072] S302 : Determine the population size of each grid point among multiple grid points at the current sedimentation simulation time based on the Generalized Lotka-Volterra model and the grid evolution rule.

[0073] In some embodiments of the present invention, the Generalized Lotka-Volterra model is:

[0074]

[0075] Where N i is the population size of species i at each grid point at the last deposition simulation moment; t is time; R i is the intrinsic birth rate of species i; K i is the carrying capacity of the environment for the i-th species; N is the number of species; A ij is the competition coefficient of the jth species to the ith species; M i is the intrinsic mortality rate of species i; I i is the population migration rate of species i.

[0076] For ease of understanding, in some embodiments of the present invention, Figure 2 Only two species, prey and predator, are included as examples for this introduction. Among them, the prey ( Figure 2 The population size of the last sedimentation simulation moment is 13, and the predator ( Figure 2 The population size at the last deposition simulation moment (the stronger icon in the figure) is 5.

[0077] The grid evolution rule is:

[0078]

[0079]

[0080]

[0081] Where X is the grid point occupied by prey; Y is the grid point occupied by prey; S is the grid point not occupied by any species; p1 is the predation rate of predators on prey; p2 is the inherent mortality rate of predators; and p3 is the inherent birth rate of prey.

[0082] It should be noted that the probabilities p1, p2, and p3 satisfy the Generalized Lotka-Volterra (GLV) model in real time.

[0083] It should be understood that the first formula in the grid evolution rule states that for a grid point in state X, if a randomly selected adjacent grid point is in state Y, then that grid point will transition to state Y with probability p1, representing prey X being preyed upon by predator Y. The second formula states that species Y dies with probability p2, clearing the grid point. The third formula states that species X reproduces with probability p3, occupying the surrounding grid points.

[0084] In some embodiments of the present invention, the vertical carbonate rock yield model includes a benthic carbonate rock yield model, and the carbonate rock deposition thickness includes the benthic carbonate rock deposition thickness; wherein the benthic carbonate rock yield model is:

[0085] E(x,y)=e x,y *t s *R x,y

[0086]

[0087] Where E(x,y) is the thickness of benthic carbonate sediments; e x,y is the carbonate accumulation rate of benthic organisms; t s is the current deposition compensation; R x,y is the yield coefficient; e m is the maximum accumulation rate of the lithofacies at the (x, y) grid point; I0 ​​is the surface light intensity; I k is the saturation light intensity; k e is the biological extinction coefficient; wd (x,y) is the water depth at the (x,y) grid point.

[0088] In some embodiments of the present invention, the carbonate rock vertical yield model further includes a deep-sea pelagic zone carbonate rock yield model, and the carbonate rock deposition thickness further includes a deep-sea pelagic zone carbonate rock deposition thickness; wherein the deep-sea pelagic zone carbonate rock yield model is:

[0089]

[0090] Where P(x,y) is the thickness of carbonate sediments in the deep-sea pelagic zone; P maxThe maximum carbonate production in the deep-sea pelagic zone; P f is the exponential decay coefficient.

[0091] The embodiment of the present invention proposes two different vertical carbonate rock yield models, namely a benthic organism carbonate rock yield model and a deep-sea pelagic zone carbonate rock yield model, which can be used to simulate carbonate rock deposition processes in different environments, thereby improving the applicability of the numerical simulation method of carbonate rock deposition processes.

[0092] Since the deposition topography at the last deposition simulation moment is not a two-dimensional plane in actual application, in order to improve the rationality of the deposition topography at the last deposition simulation moment, in some embodiments of the present invention, Figure 4 The step S104 of determining the deposition topography at the last deposition simulation time includes:

[0093] S401, obtaining a simulated terrain grid model corresponding to the actual study area at the last deposition simulation time, the simulated terrain grid model including a plurality of terrain grids and settlement values ​​and uplift values ​​of each terrain grid;

[0094] S402: Determine the sedimentary topography at the last sedimentation simulation time according to the subsidence value and the uplift value.

[0095] The embodiment of the present invention determines the sedimentary topography at the last sedimentation simulation moment by using the settlement values ​​and uplift values ​​of each terrain grid, which can improve the closeness between the sedimentary topography at the last sedimentation simulation moment and the actual topography, thereby improving the rationality of the sedimentary topography at the last sedimentation simulation moment, and further improving the rationality of the numerical simulation method of the carbonate rock deposition process.

[0096] In a specific embodiment of the present invention, Figure 5 As shown in the figure, the simulated terrain grid model includes 6×4 grids, time01 is the last sedimentation simulation time, time02 is the current sedimentation simulation time, grids greater than 0 represent uplift grids, grids less than 0 represent subsidence grids, and grids with a value greater than 0 represent subsidence grids. Figure 5 The uplift and subsidence values ​​of each grid in the model can be used to determine the sedimentary topography at the last sedimentation simulation moment.

[0097] It should be noted that since the uplift and subsidence values ​​for each grid must be manually entered by the user, in order to simplify user input, in some embodiments of the present invention, a simulated terrain function can be constructed to automatically generate the uplift and subsidence values ​​for each grid. For example, each grid can be set to have a uniform uplift to simplify user input and increase the speed of numerical simulation of the carbonate rock deposition process.

[0098] Since both the benthic carbonate rock yield model and the deep-sea pelagic zone carbonate rock yield model require the knowledge of the water depth at each grid point, and the water depth is related to the sea level and the sedimentary topography at the last deposition simulation time, therefore, in some embodiments of the present invention, Figure 6 As shown, before step S105, the following steps are further included:

[0099] S601, determining the sea level at the last deposition simulation moment;

[0100] S602: Determine the water depth at each grid point based on the sea level at the last deposition simulation time and the depositional topography at the last deposition simulation time.

[0101] It should be understood that the height difference between the sea level at each grid point and the sedimentary topography at the last sedimentation simulation time is the water depth at each grid point.

[0102] In a specific embodiment, the sea level at a certain grid point is 220 meters, and the sedimentary topography at the last sedimentation simulation time at this grid point is 20 meters, then the water depth at this grid point is 200 meters.

[0103] In some embodiments of the present invention, Figure 7 As shown, step S601 includes:

[0104] S701, obtaining a simulated sea level model;

[0105] S702: Determine the sea level at the last deposition simulation time based on the sea level model.

[0106] Among them, the simulated sea level model is a functional relationship model between sea level height and deposition time. Therefore, the sea level height at the last deposition simulation time can be determined through the last deposition simulation time.

[0107] It should be noted that the simulated sea level model can be obtained by the user inputting multiple discrete values ​​corresponding to each time point, or it can be obtained based on the constructed sea level height function, that is, the sea level height at each grid point corresponding to each time point is obtained based on the sea level height function.

[0108] In order to better implement the numerical simulation method for carbonate rock deposition process in the embodiment of the present invention, based on the numerical simulation method for carbonate rock deposition process, the embodiment of the present invention also provides a numerical simulation system for carbonate rock deposition process, such as Figure 8 As shown, the carbonate rock deposition process numerical simulation system 800 includes:

[0109] A grid model construction unit 801 is used to construct a plane grid model according to the actual research area, and the plane grid model includes multiple grid points;

[0110] The biological community determination unit 802 is used to obtain environmental physical parameters and population parameters at the current sedimentation simulation time, as well as the population size of each grid point at the previous sedimentation simulation time, and determine the current population size of each grid point at the current sedimentation simulation time based on the Generalized Lotka-Volterra model applicable to multiple species, the environmental physical parameters, the population parameters, and the population size at the previous sedimentation simulation time;

[0111] A carbonate rock deposition thickness determination unit 803 is configured to determine the carbonate rock biological yield at the current deposition simulation time based on the carbonate rock vertical yield model and the current population size, and to determine the carbonate rock deposition thickness at the current deposition simulation time based on the carbonate rock biological yield;

[0112] The current sedimentary landform determination unit 804 is used to determine the sedimentary landform at the last sedimentary simulation moment, superimpose the carbonate rock deposition thickness on the sedimentary landform, and obtain the current sedimentary landform at the current sedimentary simulation moment;

[0113] The deposition process determination unit 805 is used to use the current depositional landform as the depositional landform at the next deposition simulation moment, the next deposition simulation moment as the current deposition simulation moment, and the current population size as the population size at the next deposition simulation moment, and repeat steps 2 to 4 until the deposition simulation ends, thereby obtaining the carbonate rock deposition process in the actual study area.

[0114] The carbonate rock deposition process numerical simulation system 800 provided in the above embodiment can implement the technical solution described in the above embodiment of the carbonate rock deposition process numerical simulation method. The specific implementation principles of the above modules or units can be found in the corresponding contents in the above embodiment of the carbonate rock deposition process numerical simulation method, which will not be repeated here.

[0115] Those skilled in the art will appreciate that all or part of the process steps of the above-described embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a magnetic disk, an optical disk, a read-only memory, or a random access memory.

[0116] The above is a detailed introduction to the method and system for numerical simulation of carbonate rock deposition process provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method and core ideas of the present invention. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A numerical simulation method for carbonate rock deposition process, characterized in that: include: Step 1: construct a plane grid model according to the actual research area, wherein the plane grid model includes a plurality of grid points; Step 2: Obtain environmental physical parameters and population parameters at the current deposition simulation time, as well as the population size of each grid point at the previous deposition simulation time, and determine the current population size of each grid point at the current deposition simulation time based on a Generalized Lotka-Volterra model applicable to multiple species, the environmental physical parameters, the population parameters, and the population size at the previous deposition simulation time; Step 3: determining the carbonate rock biological productivity at the current deposition simulation time based on the carbonate rock vertical productivity model and the current population size, and determining the carbonate rock deposition thickness at the current deposition simulation time based on the carbonate rock biological productivity; Step 4: Determine the sedimentary topography at the last sedimentary simulation time, superimpose the carbonate rock deposition thickness on the sedimentary topography, and obtain the current sedimentary landform at the current sedimentary simulation time; Step 5: Using the current sedimentary landform as the sedimentary landform at the next sedimentary simulation moment, using the next sedimentary simulation moment as the current sedimentary simulation moment, using the current population size as the population size at the next sedimentary simulation moment, and repeating steps 2 to 4 until the sedimentary simulation ends, thereby obtaining the carbonate rock deposition process in the actual study area; The vertical carbonate rock yield model includes a benthic carbonate rock yield model, and the carbonate rock deposition thickness includes the benthic carbonate rock deposition thickness; the benthic carbonate rock yield model is: Where, is the thickness of benthic carbonate sediments; is the benthic carbonate accumulation rate; Compensation for current deposition; is the yield coefficient; is the maximum accumulation rate of the lithofacies at the (x,y) grid point; is the surface light intensity; is the saturation light intensity; is the biological extinction coefficient; is the water depth at the (x,y) grid point; The carbonate rock vertical yield model also includes a deep-sea pelagic zone carbonate rock yield model, and the carbonate rock deposition thickness also includes a deep-sea pelagic zone carbonate rock deposition thickness; the deep-sea pelagic zone carbonate rock yield model is: Where, is the thickness of carbonate sediments in the deep-sea pelagic zone; It is the maximum carbonate production in the deep-sea pelagic zone; is the exponential decay coefficient.

2. The method for numerical simulation of carbonate rock deposition process according to claim 1, characterized in that: The population parameters include the inherent birth rate and inherent mortality rate of each species, the carrying capacity of the environment for each species, the population migration rate of each species, and a community matrix describing the interactions between species, wherein each element in the community matrix is ​​the competition coefficient between two species; the second step includes: Determining a grid evolution rule based on the inherent birth rate, inherent death rate, environmental carrying capacity for each species, population migration rate of each species, the community matrix, and the population size of each grid point at the last sedimentation simulation time; The population size of each grid point in the plurality of grid points at the current deposition simulation moment is determined based on the Generalized Lotka-Volterra model and the grid evolution rule.

3. The method for numerical simulation of carbonate rock deposition process according to claim 2, characterized in that: The Generalized Lotka-Volterra model is: Where N i is the population size of species i at each grid point at the last deposition simulation moment; t is time; R i is the intrinsic birth rate of species i; K i is the carrying capacity of the environment for the i-th species; N is the number of species; A ij is the competition coefficient of the jth species to the ith species; M i is the intrinsic mortality rate of species i; I i is the population migration rate of species i.

4. The method for numerical simulation of carbonate rock deposition process according to claim 3, characterized in that: Species include predators and prey, and the grid evolution rule is: Where X is the grid point occupied by prey; Y is the grid point occupied by prey; S is the grid point not occupied by any species; p1 is the predation rate of predators on prey; p2 is the intrinsic mortality rate of predators; p3 is the intrinsic birth rate of prey; p1, p2, and p3 are real-time satisfied by the Generalized Lotka-Volterra model.

5. The method for numerical simulation of carbonate rock deposition process according to claim 1, characterized in that: Determining the sedimentary topography at the last sedimentation simulation moment includes: Obtaining a simulated terrain grid model corresponding to the actual study area at the last deposition simulation moment, the simulated terrain grid model including a plurality of terrain grids and settlement values ​​and uplift values ​​of each terrain grid; The sedimentary topography at the last sedimentation simulation moment is determined according to the settlement value and the uplift value.

6. The method for numerical simulation of carbonate rock deposition process according to claim 1, characterized in that: Before step 5, the method further includes: Determine the sea level at the last deposition simulation moment; The water depth at each grid point is determined based on the sea level at the last deposition simulation time and the deposition topography at the last deposition simulation time.

7. The method for numerical simulation of carbonate rock deposition process according to claim 6, characterized in that: Determining the sea level at the last deposition simulation time includes: Obtain simulated sea level models; The sea level height at the last deposition simulation time is determined based on the sea level model.

8. A numerical simulation system for carbonate rock deposition process, characterized in that: The method for numerical simulation of carbonate rock deposition process according to any one of claims 1 to 7, wherein the system comprises: A grid model construction unit, configured to construct a plane grid model according to an actual research area, wherein the plane grid model includes a plurality of grid points; a biological community determination unit, configured to obtain environmental physical parameters and population parameters at a current deposition simulation time, and the population size of each grid point at a previous deposition simulation time, and determine a current population size of each grid point at the current deposition simulation time based on a Generalized Lotka-Volterra model applicable to multiple species, the environmental physical parameters, the population parameters, and the population size at the previous deposition simulation time; a carbonate rock deposition thickness determination unit, configured to determine the carbonate rock biological yield at a current deposition simulation time based on a carbonate rock vertical yield model and the current population size, and to determine the carbonate rock deposition thickness at the current deposition simulation time based on the carbonate rock biological yield; a current sedimentary landform determination unit, configured to determine the sedimentary landform at the last sedimentary simulation moment, superimpose the carbonate rock deposition thickness onto the sedimentary landform, and obtain the current sedimentary landform at the current sedimentary simulation moment; The sedimentation process determination unit is used to use the current sedimentary landform as the sedimentary landform at the next sedimentation simulation moment, the next sedimentation simulation moment as the current sedimentation simulation moment, and the current population size as the population size at the next sedimentation simulation moment, and repeat steps 2 to 4 until the end of the sedimentation simulation, thereby obtaining the carbonate rock sedimentation process in the actual study area.

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