Density flow deposition numerical simulation method for pulveryte

Abstract

The invention belongs to the technical field of shale oil and gas development, and discloses a density flow sedimentary numerical simulation method for pulveryte, which comprises the following steps: setting a time step length and an initial grid position of a sedimentary substance point; updating the grid position of the deposition substance point according to the time step length, and determining the current flow velocity of the sediment; s2, judging whether the current flow velocity of the sediment meets a preset flow velocity condition or not, if yes, taking the new grid position as the current grid position, and returning to the step S2, and if not, simulating the density flow channel deposition process according to the path grid in the flowing process; and constructing a density flow far-end fan body, and simulating the diffusion deposition process of the density flow far-end fan body based on the tail end grid of the carrying path. The density flow channel deposition and density flow far-end fan body diffusion deposition are simulated through flow velocity attenuation in the carrying process and substance diffusion in the deposition process, simulation results better conform to the real density flow deposition rule, and a basis is provided for representing the type of reservoir structures.

Description

Technical Field

[0001] The invention belongs to the technical field of shale oil and gas development, and in particular relates to a numerical simulation method for hyperpycnal flow deposition of fine-grained sedimentary rocks. Background Art

[0002] The earliest attention paid to the hyperpycnal flow was the change in the nature of lake water caused by the injection of hyperpycnal flow into lakes, but more research focused on the siltation of reservoirs caused by river injection into reservoirs. Domestic scholars have done a lot of research in this regard, especially the investigation of reservoir hyperpycnal flow in the 1970s and 1980s, which has made important insights into the siltation mechanism and the prevention of siltation through flood control. At the same time, some research has been conducted on its development mechanism through flume simulation experiments. In recent years, the research on hyperpycnal flow has mainly focused on coarse-grained sediments. With the discovery and development of shale oil and gas, hyperpycnal flow has attracted much attention as the main sedimentary phase belt with advantages in the sweet spot area of ​​shale oil and gas development, which has important guiding significance for the exploration and development of shale oil and gas.

[0003] However, due to the small thickness of the single phase of the hyperpycnal flow and the large changes and migrations in each phase, it is still difficult to identify and track it in seismic observations despite its large cumulative thickness. There is no good way to study its development characteristics, distribution, and internal structure of different phases. At the same time, due to physical conditions, it is also difficult to simulate it in a water tank in the laboratory. At present, the understanding of hyperpycnal flow is mostly based on drilling data, and the research on the plane and three-dimensional development and distribution of hyperpycnal flow is mostly based on theoretical models, and there is no good practical support.

[0004] Sedimentation numerical simulation technology provides a method to reproduce the sedimentation process with the help of the powerful computing power of today's computers. By setting different sedimentation conditions and simulating the effects of different conditions on sedimentation, the characteristics and mechanisms of sedimentation development can be explored, providing a new means for understanding hyperpycnal flow sediments. At present, there are two main ideas for numerical simulation: (1) Based on traditional mathematical methods and Newtonian mechanics, the control equations and boundary conditions of the model are constructed and solved, and the momentum and energy of each physical quantity in the model system at each moment are accurately solved by computer numerical methods, thereby simulating the transport, deposition and erosion of materials during the sedimentation process, and finally obtaining the complete sediment development and evolution process; however, this method is usually difficult to obtain the control equations of complex systems, and its numerical method for solving partial differential equations requires high CPU computing power. At the geological scale, large-scale and long-term simulation is almost impossible, so this method is mainly used in engineering fields with high precision requirements. (2) Based on the geological response model, the physical process is simplified and abstracted, and the core concepts of the geological system are represented by simplified mathematical models. The response relationship of different deposition processes is simulated under simplified "rules" to reproduce the deposition process. The disadvantage of this method is that it is difficult to prove its authenticity and predictability. The advantages are simple control equations, fast calculation speed, and the ability to handle complex interaction processes. Therefore, how to simulate the deposition process simply and accurately is an urgent problem to be solved.

[0005] Patent document CN115544868A discloses a method for simulating a sediment transport path under the action of gravity, including obtaining a sediment material point; determining the moving direction according to the current grid position of the sediment material point and the terrain slope of the adjacent grid, and updating the current grid position of the sediment material point according to the moving direction; judging whether the current kinetic energy of the sediment material point meets the preset kinetic energy condition; if it meets, returning to the step of the terrain slope of multiple adjacent grids of the current grid position of the sediment material point, if not, generating a transport path according to the grids passed by the sediment material point. The technical solution of this patent takes into account the micro-topographic slope to simulate the sediment transport process under the action of gravity, effectively determine the moving direction of the sediment, and combine the preset kinetic energy conditions to judge whether the energy of the sediment supports continued movement from the perspective of kinetic energy, efficiently control the transport distance of the sediment, and combine gravity traction and kinetic energy limitation to control the moving direction and transport distance, so as to achieve efficient simulation of the sediment transport path. However, the method of this patent only involves the calculation of the sediment transport path under the action of gravity, and the simulation result obtained is only the result of a transport path. It does not involve the simulation of the deposition of the hyperpycnal flow channel and the diffusion deposition simulation process of the distal fan of the hyperpycnal flow. It cannot simulate the hyperpycnal flow sediment body and cannot accurately simulate the hyperpycnal flow deposition law under natural conditions. Summary of the invention

[0006] The present invention aims to solve the technical problems existing in the background technology and provide a numerical simulation method for the hyperpycnal flow deposition of fine-grained sedimentary rocks. Based on different main controlling factors in the hyperpycnal flow deposition process, it is divided into two processes: material transport and diffusion deposition. The hyperpycnal flow channel deposition and the hyperpycnal flow distal fan diffusion deposition process are simulated through the attenuation of flow velocity in the transportation process and the diffusion of material in the deposition process. The sedimentary structure characteristics are studied and an effective simulation model is constructed, which provides a reference basis for characterizing the reservoir structure of this type.

[0007] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0008] A numerical simulation method for hyperpycnal flow deposition of fine-grained sedimentary rocks, the method comprising the following steps:

[0009] Step S1: setting the time step and the initial grid position of the sedimentary material points; the sedimentary material points are used to represent sediments;

[0010] Step S2: updating the grid position of the sediment material point according to the time step, and determining the current flow rate of the sediment;

[0011] Step S3: determining whether the current flow rate of the sediment meets a preset flow rate condition;

[0012] If satisfied, the new grid position is used as the current grid position and the process returns to step S2;

[0013] If it is not satisfied, the deposition process of the hyperpycnal flow channel is simulated according to the path grid during the flow process;

[0014] Step S4: construct the distal fan of the hyperpycnal flow, simulate the diffusion and deposition process of the distal fan of the hyperpycnal flow based on the terminal grid of the transport path, and complete the numerical simulation of the deposition of the hyperpycnal flow in one phase.

[0015] Furthermore, the step S2 specifically includes:

[0016] Step S201: Divide the time step into multiple time steps according to the time step length;

[0017] Step S202: updating the grid position of the sediment represented by the sediment material point according to each time step;

[0018] Step S203: Determine the current flow rate of the sediment of the package according to the initial flow rate, gravity change and energy dissipation of the sediment material point.

[0019] Furthermore, in step S203, the calculation formula of the current flow rate of the sediment is:

[0020] When the sediment fluid density is less than or equal to the fluid density setting threshold:

[0021]

[0022] When the sediment fluid density is greater than the fluid density setting threshold:

[0023]

[0024] In the above formula, U is the current flow velocity of the sediment; g represents the gravitational acceleration of the sediment; C v represents sediment concentration; f represents Darcy-Weisbach coefficient; α represents empirical coefficient; H represents equivalent thickness of sediment; S represents fluid slope; d 50 Represents the median particle size of sediment.

[0025] Furthermore, the step S3 specifically includes:

[0026] Step S301: determining whether the current flow velocity of the sediment is greater than a set flow velocity threshold.

[0027] If satisfied, the new grid position is used as the current grid position and the process returns to step S2;

[0028] If it is not satisfied, the transport path of the sediment is determined by connecting the pathway grids during the flow process end to end in chronological order;

[0029] Step S302: taking the grid on the transport path as the center of the river channel, extending a preset number of grids on both sides of the transport path as the edge of the river channel, and determining the deposition thickness of the center and edge of the river channel according to the preset thickness value of the heterogeneous flow channel deposition, simulating the heterogeneous flow channel deposition process;

[0030] Step S303: When simulating the deposition process of the heterogeneous flow channel, a portion of the material is virtually deposited into the current grid according to the set ratio value and the accommodating space of the current grid until it reaches the terminal grid, and then the virtual deposition value is converted into a real deposition record value.

[0031] Furthermore, the step S4 specifically includes:

[0032] Step S401: constructing the density flow distal sector according to the generated random samples;

[0033] Step S402: simulating the fan diffusion and deposition process of the hyperpycnal flow according to the distal fan of the hyperpycnal flow and the terminal grid during the flow process.

[0034] Furthermore, the step S401 specifically includes:

[0035] Step S4011: randomly generate random sample points that obey a bivariate normal distribution;

[0036] Step S4012: Projecting random sample points to corresponding planar fan-shaped areas, and ensuring that the value of the binary normal distribution probability density function at the fan root is the largest, thereby constructing the heterogeneous flow distal fan body.

[0037] Furthermore, the step S402 specifically includes:

[0038] Step S4021: starting from the end grid in the flow process, counting the number of samples falling into the random sample points in each grid;

[0039] Step S4022: Determine the fan body deposition thickness according to the sample quantity and the deposition thickness conversion coefficient, and simulate the fan body diffusion deposition process of the hyperpycnal flow.

[0040] Furthermore, in step S4022, the calculation formula of the sector deposition thickness is as follows:

[0041] h i,j =n×α fanDepos

[0042] m input =∑h i,j ·Δs 2 ·ρ

[0043] In the above formula, h i,j represents the fan sedimentation thickness of the current grid; n represents the number of random sample points falling into the current grid; α fanDepos Indicates the conversion factor of the sediment thickness of the fan; m input represents the mass of sediment transported to the end of the path to be deposited; Δs represents the side length of the model grid; ρ represents the average density of the sediment.

[0044] Furthermore, the method comprises the following implementation steps:

[0045] Import geomorphic data and set model simulation parameters;

[0046] The initial simulation period n is set to 0;

[0047] According to steps S1-S4, the simulation path is searched, and the current period of heterogeneous flow channel deposition and fan diffusion deposition are performed to complete the current period of heterogeneous flow deposition simulation;

[0048] Update simulation period n = n + 1;

[0049] If the updated simulation period n is less than or equal to the set simulation period N, steps S1 to S4 are repeated to perform the next period of hyperpycnal flow deposition simulation;

[0050] If the updated simulation period n>the set simulation period N, the n times of hyperpycnal flow deposition simulation results are stacked to obtain the final hyperpycnal flow deposition data volume, and the deposition results are derived.

[0051] Furthermore, the method is implemented based on the Hyper-Sim simulation platform.

[0052] Compared with the prior art, the beneficial effects of the present invention are:

[0053] (1) The numerical simulation method for the hyperpycnal flow deposition of fine-grained sedimentary rocks provided by the present invention first obtains the effective time step and the deposition material points, then updates the grid, determines the current flow velocity of the sediment in each grid, and then judges the current state based on the current flow velocity of the sediment. If the current state does not meet the conditions for material transportation, the grids updated each time are connected in series to form a transportation path, thereby effectively simulating the hyperpycnal flow channel deposition process; finally, based on the randomly constructed hyperpycnal flow distal fan and the terminal grid during the flow process, the hyperpycnal flow distal fan diffusion deposition process is effectively simulated; therefore, based on the different main controlling factors in the hyperpycnal flow deposition process, the present invention divides it into two processes: material transportation and diffusion deposition, and simulates the hyperpycnal flow channel deposition and the hyperpycnal flow distal fan diffusion deposition respectively through the flow velocity attenuation during the transportation process and the material diffusion during the deposition process, studies its sedimentary structure characteristics, constructs an effective simulation model, and provides a reference basis for characterizing this type of reservoir structure;

[0054] (2) The simulation method of the present invention improves the judgment mechanism of the cessation of sediment transport state (such as the preset kinetic energy condition judgment mechanism adopted in patent document CN115544868A) for the simulated object, and introduces the empirical formula in fluid mechanics. By calculating the flow rate and comparing it with the set threshold value, it is judged whether the sediment transport state is to continue or stop. With sufficient theoretical research foundation and practical verification as support, the sediment transport path simulated based on flow rate calculation in the present invention is more accurate, and the simulation result is closer to the real heteropycnal flow deposition law in nature. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a flow chart of a numerical simulation method for hyperpycnal flow deposition of fine-grained sedimentary rocks according to Example 1 of the present invention;

[0056] Figure 2 for Figure 1 A flow chart of an embodiment of step S2;

[0057] Figure 3 for Figure 1 A flow chart of an embodiment of step S3;

[0058] Figure 4 for Figure 1 A flow chart of an embodiment of step S4;

[0059] Figure 5 This is a numerical simulation process diagram of the hyperpycnal flow deposition of fine-grained sedimentary rock in Example 2 of the present invention;

[0060] Figure 6 This is a schematic diagram of the simulation results of a phase of hyperpycnal flow deposition in Example 2 of the present invention;

[0061] Figure 7 This is a schematic diagram of the simulation results of the hyperpycnal flow deposition data volume finally stacked in Example 2 of the present invention. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. 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.

[0063] An embodiment of the present invention provides a numerical simulation method for hyperpycnal flow deposition of fine-grained sedimentary rocks. First, the time step and sedimentary material points are effectively acquired; then, the grid is updated to determine the current flow velocity of the sediment in each grid; then, the current state is judged based on the current flow velocity of the sediment. If the current state does not meet the conditions for material transportation, the grids updated each time are connected in series to form a transportation path, thereby effectively simulating the hyperpycnal flow channel deposition process; finally, based on the randomly constructed distal fan and the terminal grid in the flow process, the diffusion deposition process of the distal fan of the hyperpycnal flow is effectively simulated.

[0064] Example 1

[0065] The embodiment of the present invention provides a numerical simulation method for hyperpycnal flow deposition of fine-grained sedimentary rocks, and is performed based on the Hyper-Sim simulation platform.

[0066] It should be noted that, according to the different driving forces, the embodiment of the present invention divides the simulated hyperpycnal flow deposition process into two stages: 1. Sediment transportation and channel deposition process with gravity as the main driving force; 2. The process of diffusion-deposition of sediments in the static water body to generate the distal fan after reaching the water storage basin. Each gravity flow event is considered to be completed "instantaneously" in geology. According to the set parameters, one or more gravity flow events can occur in one time step of the model.

[0067] At the same time, it should be noted that the embodiment of the present invention divides the geological process to be simulated into several short time steps, and the division of the time steps depends on the time required for simulation. For example, the simulation time is 0.1Myr (1Myr = 1 million years), and 1000y (i.e. 1Ky, 1y = 1 year) is selected to represent a time step, then a total of 100000 / 1000 = 100 steps are required to be iterated. Each time step has one or more sediment transport events, and each event will produce a specific sediment body and update the bottom bed topography for the next time step iteration; each event is treated as a geological instantaneous process, and a certain amount of background mud deposits will be deposited at a set rate in the time interval between two events. Therefore, 10,000 flows with an interval of 100 years will represent a total simulation time of 1Myr.

[0068] The simulation data of the embodiment of the present invention are shown in Table 1 below:

[0069] Table 1 Specific simulation parameters

[0070]

[0071] like Figure 1 As shown, the simulation method of the embodiment of the present invention specifically includes the following steps:

[0072] Step S1: Set the time step and the initial grid position of the sediment material point (i.e., sediment entrance); the sediment material point is used to represent sediment; as shown in Table 1 above, the total simulation time of the embodiment of the present invention is 100 Ky, and the time steps corresponding to the simulation scenes 1-5 are 1 Ky, 1 Ky, 1 Ky, 0.5 Ky, and 2 Ky, respectively; the sediment material point is used to represent sediment;

[0073] Step S2: updating the grid position of the sediment material point according to the time step, and determining the current flow rate of the sediment;

[0074] Step S3: determining whether the current flow rate of the sediment meets a preset flow rate condition;

[0075] If satisfied, the new grid position is used as the current grid position and the process returns to step S2;

[0076] If it is not satisfied, the deposition process of the hyperpycnal flow channel is simulated according to the path grid during the flow process;

[0077] Step S4: construct the distal fan of the density flow, and simulate the diffusion and deposition process of the distal fan of the density flow based on the terminal grid of the transport path.

[0078] like Figure 2 As shown, the step S2 specifically includes:

[0079] Step S201: Divide into multiple time steps according to the time step; as shown in Table 1 above, simulation scenarios 1-5 are divided into 100, 100, 100, 200, and 50 time steps respectively (corresponding to the number of heterogeneous flow events in Table 1).

[0080] Step S202: updating the grid position of the sediment represented by the sediment material point according to each time step.

[0081] Step S203: Determine the current flow rate of the sediment of the package according to the initial flow rate, gravity change and energy dissipation of the sediment material point.

[0082] Among them, in step S203, when determining the current flow rate of the sediment in the package, first set a threshold value according to the fluid density to determine whether the sediment is a low-density fluid or a high-density fluid; the fluid density setting threshold value can be determined based on conventional experience, or adjusted and determined according to the actual simulation scenario and simulation requirements.

[0083] When the sediment fluid density is less than or equal to the fluid density setting threshold:

[0084]

[0085] When the sediment fluid density is greater than the fluid density setting threshold:

[0086]

[0087] In the above formulas (1)-(2), U is the current flow velocity of the sediment; g represents the gravitational acceleration of the sediment; C v represents sediment concentration; f represents Darcy-Weisbach coefficient; α represents empirical coefficient; H represents equivalent thickness of sediment; S represents fluid slope; d 50 Represents the median particle size of sediment.

[0088] In the embodiment of the present invention, a rapid slope descent algorithm under the action of gravity is used to calculate the deposition path of the hyperpycnal flow.

[0089] It should be noted that for a single gravity flow deposition event, the material source enters the model from the model boundary or any specified grid, and the sediment mass can be a constant value or a function of time. The sediment entering the model is treated as a particle, that is, a complete sediment "package" during the transportation stage. In order to simplify the model, the embodiment of the present invention uses flow velocity as a comprehensive influencing factor to control sediment transport and deposition, and always maintains mass conservation and energy conservation during the simulation process.

[0090] The movement of the "package" will follow the principle of the fastest gradient descent, that is, the particle will move along the direction of the largest local surface elevation gradient to the lowest grid among the eight adjacent grids of "east, south, west, north, southeast, southwest, northeast, and northwest".

[0091] like Figure 3 As shown, the step S3 specifically includes:

[0092] Step S301: determining whether the current flow velocity of the sediment is greater than a set flow velocity threshold.

[0093] If satisfied, the new grid position is used as the current grid position and the process returns to step S2;

[0094] If it is not satisfied, the transport path of the sediment is determined by connecting the pathway grids during the flow process end to end in chronological order.

[0095] Wherein, the preset flow rate condition is: the current flow rate of the sediment is greater than a set threshold.

[0096] During the simulation process, each time the package moves, its flow rate will be recalculated. If the flow rate is greater than the set threshold, it means that the sediment has a tendency to continue moving, and the current new grid position will be used as a benchmark to find the grid with the lowest terrain in the surrounding area; this process will be repeated until the package flow rate decays to a level that is insufficient to support its continued movement. At this time, the corresponding grid position will be used as the end point of this sediment transportation. The grids that the package passes through are connected end to end in order to obtain the sediment transportation path.

[0097] Step S302: The grid on the transport path obtained in step S301 is used as the center of the river channel, and two grids are expanded on both sides of the transport path as the edge of the river channel. Then, the deposition thickness of the center and edge of the river channel is determined according to the preset thickness value of the heterogeneous flow channel deposition, so as to simulate the heterogeneous flow channel deposition process.

[0098] Step S303: When simulating the deposition process of the heterogeneous flow channel, a portion of the material is virtually deposited into the current grid according to the set ratio value and the accommodating space of the current grid until it reaches the terminal grid, and then the virtual deposition value is converted into a real deposition record value.

[0099] It should be noted that the actual deposition process of hyperpycnal flow is deposition while transportation, that is, deposition and transportation occur simultaneously. In order to reduce the complexity of the program and the amount of calculation, the embodiment of the present invention introduces a concept called "equivalent virtual filling". Simply put, "deposition" and "transportation" are processed separately in "time". When calculating the transportation path, a part of the material is "virtually" deposited to the current grid according to the set ratio and the accommodating space of the current grid. Until the sediment "package" reaches the end of transportation, the "virtual" deposition amount will be converted into the real deposition amount record and the terrain will be updated.

[0100] The reason why it is called "virtual" filling is that the filling result will not be immediately recorded in the corresponding array (processing in programming) during virtual filling. Only after the transportation path calculation is completed, it will be recorded in the array that stores the sedimentation and surface elevation in the subsequent sedimentation calculation. This not only takes into account the impact of sedimentation on the transportation path during the transportation process, but also greatly simplifies the calculation amount.

[0101] like Figure 4 As shown, the step S4 specifically includes:

[0102] Step S401: constructing the density flow remote sector according to the generated random sample, specifically comprising the following steps:

[0103] Step S4011: randomly generate N random sample points that obey a bivariate normal distribution;

[0104] Step S4012: Projecting random sample points into the corresponding plane fan-shaped area, and ensuring that the value of the binary normal distribution probability density function at the fan root is the largest, thereby constructing the far-end fan body of the heterogeneous flow;

[0105] Step S402: According to the far-end sector of the density flow and the terminal grid during the flow, the sector diffusion and deposition process of the density flow is simulated, which specifically includes the following steps:

[0106] Step S4021: starting from the end grid in the flow process, counting the number of samples falling into the random sample points in each grid;

[0107] Step S4022: According to the sample quantity and deposition thickness conversion coefficient α fanDepos , determine the fan-body sediment thickness and simulate the fan-body diffusion sedimentation process of hyperpycnal flow.

[0108] The calculation formula of the fan body deposition thickness is as follows:

[0109] h i,j =n×α fanDepos (3)

[0110] m input=∑h i,j ·Δs 2 ·ρ (4)

[0111] In the above formulas (3)-(4), h i,j represents the fan sedimentation thickness of the current grid; n represents the number of random sample points falling into the current grid; α fanDepos Indicates the conversion factor of the sediment thickness of the fan; m input represents the mass of sediment transported to the end of the path to be deposited; Δs represents the side length of the model grid; ρ represents the average density of the sediment.

[0112] The embodiment of the present invention adopts a binary normal distribution point casting algorithm to simulate the remote fan of the hyperpycnal flow deposition, ensuring the accuracy of the simulation results. Taking two grids with grid coordinates (5, 5) and (10, 3) in the fan-shaped area as an example, assuming that the user-defined fan deposition thickness conversion coefficient α fanDepos is 0.25 (the deposition thickness conversion factor α fanDepos Generally, it can be determined through physical flume experiments or measurement data such as cores and outcrops). N random points that obey a binary normal distribution are projected into this plane fan-shaped area, where 10 points fall into the grid (5, 5) and 3 points fall into the grid (10, 3). Then the sedimentary thickness on the grid (5, 5) is 10*0.25, i.e. 2.5m. Similarly, the thickness at the grid (10, 3) is 3*0.25, i.e. 0.75m. Based on this, all grids in the fan-shaped area are calculated to obtain the distribution of the sedimentary thickness of the fan, and it is necessary to ensure that the total thickness to be deposited is equal to the sum of the thicknesses of all these grids.

[0113] Example 2

[0114] The embodiment of the present invention adopts the numerical simulation method of hyperpycnal flow deposition of fine-grained sedimentary rock in Example 1, and performs actual simulation operations on the five model scenarios in Table 1 in Example 1 based on the Hyper-Sim simulation platform.

[0115] Combination Figure 5 The specific implementation steps are as follows:

[0116] (1) Importing geomorphic data and setting model simulation parameters. For specific parameters, see Table 1 of Example 1;

[0117] (2) The initial simulation period n is set to 0 and the simulation begins;

[0118] (3) According to steps S1-S4 in Example 1, the simulation path is searched, and the current phase of heterogeneous flow channel deposition and fan diffusion deposition are performed to complete the current phase of heterogeneous flow deposition simulation. The results of the single phase of heterogeneous flow deposition simulation are shown in Figure 6 As shown;

[0119] (4) Update the simulation period n=n+1, and make the following conditional judgment:

[0120] If the updated simulation period n is less than or equal to the set simulation period N, the process proceeds to step (3), and steps S1 to S4 in Example 1 are repeated to perform the next period of hyperpycnal flow deposition simulation;

[0121] If the updated simulation period n> the set simulation period N, the results of n times of hyperpycnal flow deposition simulation are stacked to obtain the final hyperpycnal flow deposition data volume, and the deposition results are derived.

[0122] The simulated deposition results of the five model scenarios at different time steps in Table 1 are as follows Figure 7 As shown, the upper horizontal axis in the figure represents five model scenarios: Run1, Run2, Run3, Run4 and Run5; the left vertical axis in the figure represents 20, 40, 60, 80 and 100 time steps respectively.

[0123] The above description is only an embodiment of the present invention and is not intended to limit the present invention. Any modification, equivalent replacement and improvement made within the application scope of the present invention shall be included in the protection scope of the present invention.

Claims

1. A numerical simulation method for the hyperpycnal flow deposition of fine-grained sedimentary rocks, characterized in that: The method comprises the following steps: Step S1: setting the time step and the initial grid position of the sedimentary material points; the sedimentary material points are used to represent sediments; Step S2: updating the grid position of the sediment material point according to the time step, and determining the current flow rate of the sediment; Step S3: determining whether the current flow rate of the sediment meets a preset flow rate condition; If satisfied, the new grid position is used as the current grid position and the process returns to step S2; If it is not satisfied, the deposition process of the hyperpycnal flow channel is simulated according to the path grid during the flow process; Step S4: construct the distal fan of the hyperpycnal flow, simulate the diffusion and deposition process of the distal fan of the hyperpycnal flow based on the terminal grid of the transport path, and complete the numerical simulation of the deposition of the hyperpycnal flow in one phase.

2. The method according to claim 1, characterized in that The step S2 specifically includes: Step S201: Divide the time step into multiple time steps according to the time step length; Step S202: updating the grid position of the sediment represented by the sediment material point according to each time step; Step S203: Determine the current flow rate of the sediment of the package according to the initial flow rate, gravity change and energy dissipation of the sediment material point.

3. The method according to claim 2, characterized in that In step S203, the calculation formula of the current flow rate of the sediment is: When the sediment fluid density is less than or equal to the fluid density setting threshold: When the sediment fluid density is greater than the fluid density setting threshold: In the above formula, U is the current flow velocity of the sediment; g represents the gravitational acceleration of the sediment; C v represents sediment concentration; f represents Darcy-Weisbach coefficient; α represents empirical coefficient; H represents equivalent thickness of sediment; S represents fluid slope; d 50 Represents the median particle size of sediment.

4. The method according to claim 3, characterized in that: The step S3 specifically includes: Step S301: determining whether the current flow velocity of the sediment is greater than a set flow velocity threshold. If satisfied, the new grid position is used as the current grid position and the process returns to step S2; If it is not satisfied, the transport path of the sediment is determined by connecting the pathway grids during the flow process end to end in chronological order; Step S302: taking the grid on the transport path as the center of the river channel, extending a preset number of grids on both sides of the transport path as the edge of the river channel, and determining the deposition thickness of the center and edge of the river channel according to the preset thickness value of the heterogeneous flow channel deposition, simulating the heterogeneous flow channel deposition process; Step S303: When simulating the deposition process of the heterogeneous flow channel, a portion of the material is virtually deposited into the current grid according to the set ratio value and the accommodating space of the current grid until it reaches the terminal grid, and then the virtual deposition value is converted into a real deposition record value.

5. The method according to claim 1, characterized in that The step S4 specifically includes: Step S401: constructing the density flow distal sector according to the generated random samples; Step S402: simulating the fan diffusion and deposition process of the hyperpycnal flow according to the distal fan of the hyperpycnal flow and the terminal grid during the flow process.

6. The method according to claim 5, characterized in that The step S401 specifically includes: Step S4011: randomly generate random sample points that obey a bivariate normal distribution; Step S4012: Projecting random sample points to corresponding planar fan-shaped areas, and ensuring that the value of the binary normal distribution probability density function at the fan root is the largest, thereby constructing the heterogeneous flow distal fan body.

7. The method according to claim 6, characterized in that The step S402 specifically includes: Step S4021: starting from the end grid in the flow process, counting the number of samples falling into the random sample points in each grid; Step S4022: Determine the fan body deposition thickness according to the sample quantity and the deposition thickness conversion coefficient, and simulate the fan body diffusion deposition process of the hyperpycnal flow.

8. The method according to claim 7, characterized in that In step S4022, the formula for calculating the fan body deposition thickness is as follows: h i,j =n×α fanDepos m input =∑h i,j ·Ds 2 ·r In the above formula, h i,j represents the fan sedimentation thickness of the current grid; n represents the number of random sample points falling into the current grid; α fanDepos Indicates the conversion factor of the sediment thickness of the fan; m input represents the mass of sediment transported to the end of the path to be deposited; Δs represents the side length of the model grid; ρ represents the average density of the sediment.

9. The method according to any one of claims 1 to 8, characterized in that: The method comprises the following implementation steps: Import geomorphic data and set model simulation parameters; The initial simulation period n is set to 0; According to steps S1-S4, the simulation path is searched, and the current period of heterogeneous flow channel deposition and fan diffusion deposition are performed to complete the current period of heterogeneous flow deposition simulation; Update simulation period n = n + 1; If the updated simulation period n is less than or equal to the set simulation period N, steps S1 to S4 are repeated to perform the next period of hyperpycnal flow deposition simulation; If the updated simulation period n>the set simulation period N, the n times of hyperpycnal flow deposition simulation results are stacked to obtain the final hyperpycnal flow deposition data volume, and the deposition results are derived.

10. The method according to claim 9, characterized in that The method is implemented based on the Hyper-Sim simulation platform.

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