Clastic rock reservoir physical property modeling method and system based on mainstream line constraint

Abstract

The invention provides a main flow line constrained clastic rock reservoir physical property modeling method and system, and the method comprises the steps: 1, carrying out the particle size analysis after carrying out the microfacies division of a continuous coring well core, and determining the strongest water flow position in a sedimentary microfacies; step 2; performing mercury injection test on the core samples of different sedimentary microfacies types, calculating the mercury removal efficiency of each core sample, and determining the core sample point with the minimum mercury removal efficiency value; 3, determining a main flow line of a sedimentary water body in the microfacies on the sedimentary microfacies plane distribution diagram according to the strongest water flow position in the sedimentary microfacies and the rock core sample point with the minimum mercury removal efficiency value; 4, with the main flow line of the sedimentary water body as a constraint condition, within the sedimentary microfacies range, interpolation of porosity and permeability parameters is conducted according to the trend that the main flow line gradually decreases towards the boundary direction, and a stratum porosity and permeability attribute model is constructed. The problem that a conventional attribute model cannot reflect the difference of fluid seepage paths is solved.

Description

Technical Field

[0001] The present invention relates to the field of three-dimensional geological modeling in oil development geology, and particularly to a method for modeling physical properties of clastic rock reservoirs based on mainstream line constraints. Background Art

[0002] Reservoir geological modeling is an important method for understanding the variation law of reservoirs in three-dimensional directions. The porosity and permeability parameters of reservoirs are the data basis for establishing property models. For clastic sedimentary reservoirs, after clastic particles are transported away from the source area by water flow, they are gradually deposited as the hydrodynamic force weakens. The pore-throat system composed of pores and throats between sedimentary particles is the place for oil and gas storage and seepage. The complexity of the pore-throat system directly determines the efficiency of oil and gas development. Porosity reflects the volume percentage of the pore-throat system in the reservoir, and permeability reflects the seepage ability of the pore-throat system in the reservoir. This parameter cannot reflect the relationship between rock pores and throats and cannot characterize the internal oil-water seepage path of the rock.

[0003] Waterflood development is a common method in the secondary development of oil and gas fields. This method can not only supplement formation energy and maintain formation pressure, but also displace oil and gas in the pore throats. During the advancement of the waterflood front, due to the influence of reservoir plane and vertical heterogeneity, fingering and bypassing phenomena often occur, resulting in the formation of remaining oil in the bypassing area of the injected water, thereby reducing the degree of reserve utilization. Therefore, it is necessary to finely characterize the seepage path of the injected water, that is, it is necessary to determine the situation where the injected water does not effectively seep in the pores and throats in different parts of the sand body.

[0004] The pore-throat system is formed along with the sedimentation process, that is, there is a genetic relationship between the pore-throat characteristics and the particle sedimentation mode and sedimentary hydrodynamic force. The corresponding pore-throat system can be determined according to the hydrodynamic force and particle sedimentation mode. During the advancement of the injected external fluid, there are significant differences in the proportion of throats where no effective seepage occurs between different pore-throat systems, that is, the degree of bypassing of the fluid in the sand bodies formed in different sedimentary environments is different. Therefore, analyzing from the perspective of the sedimentation process can achieve the purpose of fine characterization of the reservoir.

[0005] At present, the characterization of clastic rock reservoirs exists at two scales, large and small. Among them, the reservoir characterization at the large scale focuses on the description of the internal structure of the reservoir. The spatial distribution characteristics of the interbeds are mainly determined based on seismic data and logging curves, that is, the boundaries of each seepage unit. Then, porosity and permeability parameters are used to compare the seepage capacities of different seepage units between each seepage unit, and high-quality reservoirs and poor reservoirs are identified. The reservoir characterization at the small scale focuses on the description of the pore-throat structure of the reservoir. Mainly based on the observation of ordinary rock thin sections and cast thin sections, the sand bodies are divided into different types with different degrees of pore-throat development according to the size of the pore-throats and their combination patterns. The description of the internal structure of the reservoir improves the understanding of the reservoir to a certain extent, which is conducive to carrying out production measure adjustments and improving the matching degree between the sand bodies and the well pattern. However, this description method can only achieve the accuracy at the level of single-genetic sand bodies and cannot reflect the influence of water body changes during the deposition process of single-genetic sand bodies on the physical property characteristics of the internal pore-throat system. The description of the reservoir pore-throat structure can understand the pore and throat types inside the rock at the microscopic scale. However, this method requires a large number of samples in practical applications and does not involve different seepage situations of pores and throats, and there are problems such as a single parameter used for reservoir type division and rough division accuracy. Summary of the Invention

[0006] The present invention proposes a method and system for physical property modeling of clastic rock reservoirs based on main streamline constraints, so as to solve the problem of rough reservoir division types caused by the low applicability of the method for classifying and characterizing pore-throats from a microscopic perspective at a larger scale, and also solve the problem of production contradictions between oil wells and water wells caused by the low level of fineness in characterizing the internal structure of the reservoir from a macroscopic perspective. At the same time, it solves the problem that conventional attribute models cannot reflect the differences in fluid seepage paths.

[0007] The present invention proposes a method for physical property modeling of clastic rock reservoirs based on main streamline constraints, including:

[0008] Step 1: After microfacies division of the cores of continuous coring wells, carry out grain size analysis to determine the position of the strongest water flow within the same microfacies;

[0009] Step 2: Conduct mercury injection tests on core samples of different sedimentary microfacies types, calculate the mercury withdrawal efficiency of each core sample, and determine the core sample point with the minimum mercury withdrawal efficiency value within the same microfacies;

[0010] Step 3: Determine the main streamline of the sedimentary water body within the microfacies on the plane distribution map of the sedimentary microfacies according to the position of the strongest water flow intensity and the core sample point with the minimum mercury withdrawal efficiency value within the sedimentary microfacies;

[0011] Step 4: Using the main streamline of the sedimentary water body as a constraint condition, within the range of the sedimentary microfacies, interpolate the pore and permeability parameters according to the trend of gradually decreasing from the main streamline to the boundary direction, and construct a formation porosity and permeability attribute model.

[0012] Optionally, step 1 specifically includes:

[0013] Step 101: After performing microfacies division on the cores of consecutive coring wells, draw a grain size probability diagram;

[0014] Step 102: Based on the grain size probability diagram, determine the proportions of suspended transport components, saltation transport components, and rolling transport components within each type of sedimentary microfacies and the straight-line segment slopes of each component;

[0015] Step 103: Based on the proportions of the suspended transport components, saltation transport components, and rolling transport components and the straight-line segment slopes of each component, determine the position of the strongest water flow within the sedimentary microfacies.

[0016] Optionally, step 2 specifically includes:

[0017] Step 201: Based on mercury injection testing, calculate the saturation of mercury flowing out of each core sample according to the difference between the maximum mercury saturation and the minimum mercury saturation;

[0018] Step 202: Calculate the ratio of each mercury outflow saturation to the maximum mercury saturation to obtain the mercury withdrawal efficiency;

[0019] Step 203: Based on the mercury withdrawal efficiency, determine the core sample point with the minimum mercury withdrawal efficiency value.

[0020] Optionally, determining the main streamline of the sedimentary water body within the microfacies on the sedimentary microfacies plane distribution map based on the position of the strongest water flow intensity within the sedimentary microfacies and the core sample point with the minimum mercury withdrawal efficiency value includes:

[0021] Constrained by the position of the strongest water flow intensity within the sedimentary microfacies and the core sample point with the minimum mercury withdrawal efficiency value in the provenance direction, and combining the sand body thickness data drilled at each well point, select the maximum value of the sand body thickness for connection as the main streamline of the sedimentary water body within the microfacies.

[0022] Optionally, step 4 specifically includes:

[0023] According to the position of the main streamline, determine the regions where different sediment particles are located after sorting;

[0024] According to the regions where different sediment particles are located, interpolate the pore permeability parameters respectively according to the trend that the pore permeability value gradually deteriorates from the position of the main streamline to the microfacies boundary, and construct a formation porosity and permeability property model.

[0025] The present invention also provides a clastic rock reservoir physical property modeling system based on main streamline constraint, including:

[0026] A grain size analysis module, which is used to perform microfacies division on the cores of consecutive coring wells, conduct grain size analysis, and determine the position of the strongest water flow within the same microfacies;

[0027] The mercury withdrawal efficiency calculation module is used to perform mercury injection tests on core samples of different sedimentary microfacies types, calculate the mercury withdrawal efficiency of each core sample, and determine the core sample point with the minimum mercury withdrawal efficiency value within the same microfacies;

[0028] The main flow line determination module is used to determine the main flow line of the sedimentary water body within the microfacies on the sedimentary microfacies plane distribution map according to the position of the strongest water flow intensity within the sedimentary microfacies and the core sample point with the minimum mercury withdrawal efficiency value;

[0029] The formation porosity and permeability property model construction module is used to construct the formation porosity and permeability property model by interpolating the pore and permeability parameters in the sedimentary microfacies range with the main flow line of the sedimentary water body as the constraint condition and gradually decreasing trend from the main flow line to the boundary direction.

[0030] The present 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, the steps of the clastic rock reservoir physical property modeling method based on the main flow line constraint as described in any one of the above embodiments are implemented.

[0031] The present invention also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the clastic rock reservoir physical property modeling method based on the main flow line constraint as described in any one of the above embodiments are implemented.

[0032] Advantages of the present invention:

[0033] The clastic rock reservoir physical property modeling method based on the main flow line constraint proposed by the present invention comprehensively characterizes the hydrodynamic force, particle deposition mode, rock pore throat characteristics, and seepage characteristics during the rock deposition process from the perspective of the rock deposition process, introduces a new constraint condition of the main flow line, and constructs the formation porosity and permeability property model. On the one hand, for the first time, it is proposed to use the main flow line in the sedimentation process research as a constraint condition for interpolating pore and permeability parameters between well points in reservoir modeling to intervene in the change trend of grid pore and permeability parameters between well points, avoid the errors caused by traditional mechanical interpolation methods, and improve the accuracy of the property model; on the other hand, for the first time, it is proposed to combine the results of mercury injection tests with the sedimentation process to determine the difference in mercury withdrawal efficiency in the pore throat system formed under different water body conditions, so as to determine the degree of influence of the external fluid on the pore throat system during the propulsion process, and thus intervene in the oil-water seepage capacity in the reservoir. Description of the drawings

[0034] Figure 1 It is a step diagram of a clastic rock reservoir physical property modeling method based on the main flow line constraint provided by the present invention;

[0035] Figure 2 It is a step diagram of a particle size analysis method provided by the present invention;

[0036] Figure 3 It is a step diagram of a mercury withdrawal efficiency calculation method provided by the present invention;

[0037] Figure 4 It is a schematic diagram of a physical property modeling system for clastic rock reservoirs based on mainstream line constraint provided by the present invention. Detailed implementation manners

[0038] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0039] The present invention proposes a physical property modeling method for clastic rock reservoirs based on mainstream line constraint, as Figure 1 shown, including:

[0040] Step 1: After microfacies division of the cores of continuously cored wells, conduct grain size analysis to determine the position of the strongest water flow intensity within the sedimentary microfacies;

[0041] Step 1 is as Figure 2 shown, and specifically includes: Step 101: After microfacies division of the cores of continuously cored wells, draw a grain size probability diagram; Step 102: Determine the proportions of suspended transport components, saltation transport components, and rolling transport components within each type of sedimentary microfacies and the linear segment slopes of each component according to the grain size probability diagram; Step 103: Determine the position of the strongest water flow within the sedimentary microfacies according to the proportions of the suspended transport components, saltation transport components, and rolling transport components and the linear segment slopes of each component.

[0042] In one embodiment, the microfacies here can be areas such as river channels and lakes. After microfacies division of different regions, the core samples corresponding to the cores of continuously cored wells, such as low-permeability, medium-permeability, high-permeability, and extra-high-permeability samples, are used to conduct grain size analysis on each core sample to determine the average particle size φ value and the percentage of suspended components of the core sample, and draw a grain size probability diagram; read the proportions of suspended transport components, saltation transport components, and rolling transport components within each type of microfacies and the linear segment slope conditions of each component in the grain size probability diagram to determine the position of the strongest water flow within the sedimentary microfacies.

[0043] It should be noted that the higher the proportion of the rolling transportation component, the greater the strength of the sedimentary water body. Thus, the position of the highest point of the proportion of the rolling transportation component is determined as the position of the strongest water flow intensity within the sedimentary microfacies. The higher the proportion of the suspended transportation component, the weaker the energy of the sedimentary water body. The larger the slope of the straight line segment of each component reflects the better sorting of the sedimentary components, that is, different core samples can be accurately classified to the corresponding microfacies positions. Taking the river channel as an example, the middle position of the river channel is taken as the position of the strongest water flow intensity, and then the orientation of each core sample relative to the strongest water flow position can be determined.

[0044] Step 2: Conduct mercury injection tests on core samples of different sedimentary microfacies types, calculate the mercury withdrawal efficiency of each core sample, and select the core sample point with the smallest mercury withdrawal efficiency value according to the screening; optionally, as Figure 3 shown, Step 2 specifically includes:

[0045] Step 201: Based on the mercury injection test, calculate the saturation of the mercury flowing out of each core sample according to the difference between the maximum mercury saturation and the minimum mercury saturation;

[0046] Step 202: Calculate the ratio of the saturation of the mercury flowing out of each core sample to the maximum mercury saturation to obtain the mercury withdrawal efficiency;

[0047] Step 203: Determine the core sample point with the smallest mercury withdrawal efficiency value according to the mercury withdrawal efficiency.

[0048] In one embodiment, in combination with Figure 3 , conduct mercury injection tests on the core samples within each microfacies. Based on the mercury injection test data of the core samples within each microfacies, obtain the saturation of the mercury flowing out of each core sample according to Step 201; then calculate the mercury withdrawal efficiency of each core sample according to Step 202. It should be noted that the minimum mercury saturation reflects the percentage of the pore throat volume occupied by the mercury that cannot flow out under the action of capillary force to the total pore throat volume, that is, the percentage of the throat volume in the reservoir that cannot have effective seepage. The greater the mercury withdrawal efficiency, that is, the higher the percentage of the pore throat volume that can have effective seepage to the total pore throat volume, the higher the degree of influence of the external fluid on the pore throat system during the displacement process of the oil layer range. The mercury withdrawal efficiency is smaller closer to the position of the strongest water flow intensity. Determine the core sample point with the smallest mercury withdrawal efficiency value according to the mercury withdrawal efficiency of each sample within the microfacies.

[0049] Step 3: Determine the main streamline of the sedimentary water body within the microfacies on the sedimentary microfacies plane distribution map according to the position of the strongest water flow within the sedimentary microfacies and the core sample point with the minimum mercury withdrawal efficiency value;

[0050] In one embodiment, in the direction of the sediment source, the greater the water body strength of the core sample points closer to the position of the strongest water flow within the sedimentary microfacies and with the smallest mercury withdrawal efficiency value during the deposition period, the more sediment it carries, and the greater the sedimentary thickness of the sand body. According to the planar distribution of the sand body thickness drilled by the well points within each microfacies, continuous tracking is carried out according to the maximum value of the sand body thickness, and combined with the particle size analysis results of the samples from each coring well, the distribution of the main flow line is determined.

[0051] It should be noted that both Step 1 and Step 2 are for depicting the boundary of the main flow line. Through the calculations of different characteristics of each microfacies in Step 1 and Step 2, the position of the finally determined main flow line is more accurate.

[0052] Step 4: Taking the main flow line of the sedimentary water body as a constraint condition, within the sedimentary microfacies range, interpolation of pore permeability parameters is carried out according to the trend of gradually decreasing from the main flow line towards the boundary direction, and a formation porosity and permeability attribute model is constructed.

[0053] In one embodiment, according to the position of the main flow line, the regions where different sediment particles are located are determined through sorting; according to the regions where different sediment particles are located, interpolation of pore permeability parameters is respectively carried out according to the trend of gradually deteriorating pore permeability values from the position of the main flow line towards the microfacies boundary, and a formation porosity and permeability attribute model is constructed. Specifically, when establishing the formation porosity and permeability attribute model, the main flow line determined in Step 3 is used as a new constraint condition to limit the planar change trend of the grid porosity and permeability parameters between well points. The sediment particles at the main flow line position are well sorted, and the porosity and permeability parameters are higher than those in the non-main flow line sedimentation area. Then, when interpolating the pore permeability parameters between well points within the microfacies, the microfacies is divided into two parts by the main flow line, and interpolation between well points is respectively carried out according to the trend of gradually deteriorating pore permeability values from the position of the main flow line towards the microfacies boundary, avoiding the phenomenon that the mechanical interpolation results are inconsistent with the water body energy change, and even avoiding inaccurate model caused by incorrect difference data.

[0054] In this embodiment, first, the results of mercury injection tests are combined with the deposition process to determine the difference in mercury withdrawal efficiency in the pore-throat systems formed under different water body conditions, so as to determine the extent of the influence of external fluids on the pore-throat system during the propulsion process, and thus intervene in the oil-water seepage capacity in the reservoir; second, the main flow line in the deposition process research is used as a constraint condition for interpolation of pore permeability parameters between well points and applied to reservoir modeling to intervene in the change trend of grid pore permeability parameters between well points, avoiding the errors caused by traditional mechanical interpolation methods and improving the accuracy of the attribute model.

[0055] The present invention also provides experimental data of a clastic rock reservoir physical property modeling method based on the main flow line constraint proposed by the present invention, as follows:

[0056] In Table 1, the ratios of the maximum mercury withdrawal efficiency to the minimum mercury withdrawal efficiency of the low-permeability 1-x, medium-permeability 2-x, high-permeability 3-x, and extra-high-permeability 4-x samples are 2.42, 3.68, 2.23, and 1.96 respectively, where x = 1, 2…, which reflects that there are significantly different seepage characteristics among samples of the same pore-permeability level under different deposition conditions. Therefore, the pore-permeability parameters between well points obtained by mechanical interpolation ignore the actual situation of different seepage characteristics within the same pore-permeability value. Based on the determination of the sediment provenance direction, the trend of pore-permeability variation within the microfacies needs to be constrained by the main streamline, that is, the characterization of the physical property model of the clastic rock reservoir is more refined according to the method provided by the present invention.

[0057] Table 1 Physical property data table of different pore-permeability samples

[0058]

[0059] The present invention also provides a physical property modeling system for clastic rock reservoirs based on main streamline constraint, as Figure 4 shown, including:

[0060] A grain size analysis module, which is used to carry out grain size analysis after microfacies division of the cores of continuous coring wells to determine the position of the strongest water flow within the sedimentary microfacies;

[0061] A mercury withdrawal efficiency calculation module, which is used to carry out mercury injection tests on the core samples of different sedimentary microfacies types, calculate the mercury withdrawal efficiency of each core sample, and determine the core sample point with the minimum mercury withdrawal efficiency value within the same microfacies;

[0062] A main streamline determination module, which is used to determine the main streamline of the sedimentary water body within the microfacies on the plane distribution map of the sedimentary microfacies according to the position of the strongest water flow within the sedimentary microfacies and the core sample point with the minimum mercury withdrawal efficiency value;

[0063] A formation porosity and permeability attribute model construction module, which is used to interpolate the pore-permeability parameters according to the trend of gradually decreasing from the main streamline to the boundary within the sedimentary microfacies range with the main streamline of the sedimentary water body as the constraint condition, and construct a formation porosity and permeability attribute model.

[0064] It should be noted that the physical property modeling system for clastic rock reservoirs based on main streamline constraint can implement the same physical property modeling method for clastic rock reservoirs based on main streamline constraint as in the above method embodiments, which will not be elaborated here.

[0065] The present 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 steps of the physical property modeling method for clastic rock reservoirs based on main streamline constraint as in any one of the above embodiments.

[0066] In another embodiment of the present invention, a terminal device is provided. The terminal device includes a processor and a memory. The memory is used to store a computer program, and the computer program includes program instructions. The processor is used to execute the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function. The processor described in the embodiment of the present invention can be used for the operation of the physical property modeling method of clastic rock reservoirs based on mainstream line constraints.

[0067] The present invention also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the physical property modeling method of clastic rock reservoirs based on mainstream line constraints in any one of the above embodiments.

[0068] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in the terminal device and is used to store programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and, of course, the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, and this storage space stores the operating system of the terminal. And, in this storage space, one or more instructions suitable for being loaded and executed by the processor are also stored. These instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. One or more instructions stored in the computer-readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the physical property modeling method of clastic rock reservoirs based on mainstream line constraints in the above embodiments.

[0069] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0070] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0071] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing devices to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0072] These computer program instructions can also be loaded onto a computer or other programmable data processing devices, such that a series of operation steps are executed on the computer or other programmable devices to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable devices provide steps for implementing the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific embodiments of the present invention, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A physical property modeling method for clastic rock reservoirs based on mainstream line constraints, characterized in that, Including: Step 1: After microfacies division of the cores from continuous coring wells, conduct grain size analysis to determine the water flow intensity characteristics of each well point, and determine the position of the strongest water flow within the same microfacies; Step 2: Conduct mercury injection tests on the core samples of different sedimentary microfacies types, calculate the mercury withdrawal efficiency of each core sample, and determine the core sample point with the minimum mercury withdrawal efficiency within the same microfacies; Step 3: Determine the main flow line of the sedimentary water body within the microfacies on the sedimentary microfacies plane distribution map based on the position of the strongest water flow intensity within the sedimentary microfacies and the core sample point with the minimum mercury withdrawal efficiency value; Step 4: Taking the main flow line of the sedimentary water body as a constraint condition, within the sedimentary microfacies range, interpolate the pore permeability parameters according to the trend of gradually decreasing from the main flow line towards the boundary direction, and construct the formation porosity and permeability attribute model.

2. The physical property modeling method for clastic rock reservoirs based on mainstream line constraints according to claim 1, characterized in that The specific content of Step 1 includes: Step 101: After microfacies division of the cores from continuous coring wells, draw a grain size probability diagram; Step 102: Determine the proportions of suspended transport components, saltation transport components, and rolling transport components within each type of sedimentary microfacies and the straight-line segment slopes of each component according to the grain size probability diagram; Step 103: Determine the position of the strongest water flow intensity within the sedimentary microfacies based on the proportions of the suspended transport components, saltation transport components, and rolling transport components and the straight-line segment slopes of each component.

3. A physical property modeling method for clastic rock reservoirs based on mainstream line constraints according to claim 1, characterized in that The specific content of Step 2 includes: Step 201: Based on the mercury injection test, calculate the saturation of the mercury flowing out of each core sample according to the difference between the maximum mercury saturation and the minimum mercury saturation; Step 202: Calculate the ratio of the saturation of the mercury flowing out to the maximum mercury saturation for each, and obtain the mercury withdrawal efficiency; Step 203: Determine the core sample point with the minimum mercury withdrawal efficiency value according to the mercury withdrawal efficiency.

4. A physical property modeling method for clastic rock reservoirs based on mainstream line constraint according to claim 1, characterized in that, Determining the main flow line of the sedimentary water body within the microfacies on the sedimentary microfacies plane distribution map based on the position of the strongest water flow intensity within the sedimentary microfacies and the core sample point with the minimum mercury withdrawal efficiency value includes: Taking the position of the strongest water flow intensity within the sedimentary microfacies and the core sample point with the minimum mercury withdrawal efficiency value as constraints in the provenance direction, and combining the sand body thickness data drilled at each well point, select the highest value of the sand body thickness for connection as the main flow line of the sedimentary water body within the microfacies.

5. A physical property modeling method for clastic rock reservoirs based on mainstream line constraint according to claim 1, characterized in that The specific content of Step 4 includes: Determine the regions where different sediment particles are located through sorting according to the position of the main flow line; According to the regions where different sediment particles are located, interpolate the pore permeability parameters respectively according to the trend of gradually deteriorating pore permeability values from the position of the main flow line towards the microfacies boundary, and construct the formation porosity and permeability attribute model.

6. A physical property modeling system for clastic rock reservoirs based on mainstream line constraints, characterized in that, Including: A grain size analysis module, which is used to conduct grain size analysis after microfacies division of the cores from continuous coring wells to determine the position of the strongest water flow intensity within the sedimentary microfacies; A mercury withdrawal efficiency calculation module, which is used to conduct mercury injection tests on the core samples of different sedimentary microfacies types, calculate the mercury withdrawal efficiency of each core sample, and screen the core sample point with the minimum mercury withdrawal efficiency value; A main flow line determination module, which is used to determine the main flow line of the sedimentary water body within the microfacies on the sedimentary microfacies plane distribution map based on the position of the strongest water flow intensity within the sedimentary microfacies and the core sample point with the minimum mercury withdrawal efficiency value; The formation porosity and permeability property model construction module is used to interpolate pore and permeability parameters within the sedimentary microfacies range with the main flow line of the sedimentary water body as the constraint condition, and construct the formation porosity and permeability property model according to the trend of gradually decreasing from the main flow line towards the boundary direction.

7. 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 steps of the clastic reservoir physical property modeling method based on main flow line constraint according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the clastic reservoir physical property modeling method based on main flow line constraint according to any one of claims 1 to 5.

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