A method and system for determining the optimal hydraulic path in sandstone

Abstract

This invention discloses a method and system for determining the optimal hydraulic path in sandstone, belonging to the field of rock seepage technology. The method includes: acquiring a two-dimensional image of the grain size distribution on the surface of sandstone; constructing a microscale two-dimensional digital pipe network based on the two-dimensional image of the grain size distribution on the surface of sandstone; adding boundary conditions and node and pipe constraints to the microscale two-dimensional digital pipe network to obtain a two-dimensional pore network digital rock model; calculating the water pressure difference between the two ends of each pipe based on the two-dimensional pore network digital rock model; using the water pressure difference between the two ends of the pipe as the weight of the pipe, and selecting the seepage path with the largest path weight as the optimal hydraulic path for sandstone. This method achieves accurate identification of the optimal hydraulic path for sandstone and solves the current technical problem of not being able to accurately determine the optimal hydraulic path for sandstone.

Description

Technical Field

[0001] This invention relates to the field of digital rock and porous media seepage technology, and in particular to a method and system for determining the optimal hydraulic path in sandstone. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] In fields such as oil and gas exploration and development, groundwater flow simulation, geothermal resource utilization, and geotechnical engineering, the internal pore structure of rocks has a decisive influence on the seepage behavior of fluids (such as water, oil, and gas). Traditional research usually relies on core experiments, CT scanning imaging, and microstructural observation to obtain information on the pore structure of rocks. However, these methods are often costly, time-consuming, and difficult to fully reflect the fluid flow paths and hydraulic characteristics in complex pore networks.

[0004] With the development of Digital Rock Technology, constructing digital rock models based on two-dimensional or three-dimensional image data has become an important means of studying the microscopic seepage characteristics of rocks. Among them, the two-dimensional pore network model simplifies the pores and throats in the rock into network nodes and connecting edges by processing images of rock thin sections, microscopic imaging, or CT slices, providing an effective computational platform for seepage path analysis, pore connectivity evaluation, and fluid flow simulation.

[0005] However, existing analyses of two-dimensional pore network models mainly focus on calculating macroscopic parameters such as porosity and permeability, or on homogenization based on simple fluid dynamics formulas. They cannot determine the hydraulically optimal path in the pore network, and therefore cannot provide refined path optimization guidance for engineering applications such as oil and gas well network deployment, groundwater pollution control, and reservoir stimulation. Summary of the Invention

[0006] To address the aforementioned problems, this invention proposes a method and system for determining the optimal hydraulic path in sandstone, which can determine the optimal hydraulic path in sandstone by constructing a two-dimensional pore network digital rock model.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] Firstly, a method for determining the optimal hydraulic path in sandstone is proposed, including:

[0009] Obtain a two-dimensional image of the grain size distribution on the surface of sandstone;

[0010] A microscale two-dimensional digital pipeline network was constructed based on a two-dimensional image of the grain size distribution on the surface of sandstone.

[0011] Boundary conditions and node and pipe constraints are added to a microscale two-dimensional digital pipeline network to obtain a two-dimensional pore network digital rock model.

[0012] Based on the two-dimensional pore network digital rock model, the water pressure difference at both ends of each pipe was calculated.

[0013] The pressure difference between the two ends of the pipe is used as the weight of the pipe. The seepage path with the largest path weight is selected as the hydraulically optimal path for sandstone. The path weight of the seepage path is the sum of the weights of all the pipes that the seepage path passes through.

[0014] Furthermore, the actual length of the optimal hydraulic path for sandstone and the straight-line distance between the starting and ending nodes of the optimal hydraulic path for sandstone are also obtained.

[0015] The tortuosity of the optimal hydraulic path for sandstone is calculated based on the actual length of the path and the straight-line distance between the starting and ending nodes.

[0016] Furthermore, based on the two-dimensional image of the sandstone surface grain size distribution, the distribution law of sandstone pore parameters was determined;

[0017] Based on the distribution law of sandstone pore parameters, a microscale two-dimensional digital pipeline network is constructed.

[0018] Furthermore, the boundary conditions added to the microscale two-dimensional digital pipeline network include: setting the upstream surface water pressure of the microscale two-dimensional digital pipeline network to 1, the downstream surface water pressure to 0, and setting no flux on the left and right sides of the microscale two-dimensional digital pipeline network.

[0019] Furthermore, a two-dimensional pixel array of the two-dimensional image of the grain size distribution on the surface of the sandstone is extracted;

[0020] Extract a two-dimensional image of sandstone from a two-dimensional pixel array;

[0021] Two-dimensional images of sandstone are identified to determine the distribution pattern of sandstone pore parameters.

[0022] Furthermore, the node and pipeline constraints include: water flow mode, pipeline flow constraints, and node inflow and outflow equality constraints; among which, the pipeline flow constraints adopt the Poiseuille formula.

[0023] Secondly, a system for determining the optimal hydraulic path in sandstone is proposed, including:

[0024] The image acquisition unit is used to acquire two-dimensional images of the grain size distribution on the surface of sandstone.

[0025] A microscale two-dimensional digital pipeline network construction unit is used to construct a microscale two-dimensional digital pipeline network based on a two-dimensional image of the grain size distribution on the surface of sandstone.

[0026] A two-dimensional porous network digital rock model building unit is used to add boundary conditions and node and pipe constraints to a micro-scale two-dimensional digital pipeline network to obtain a two-dimensional porous network digital rock model.

[0027] The unit for determining the water pressure difference at both ends of the pipeline is used to calculate the water pressure difference at both ends of each pipeline based on a two-dimensional pore network digital rock model.

[0028] The sandstone hydraulic optimal path determination unit is used to take the water pressure difference between the two ends of the pipe as the weight of the pipe, and select the seepage path with the largest path weight as the sandstone hydraulic optimal path. The path weight of the seepage path is the sum of the weights of all pipes that the seepage path passes through.

[0029] Thirdly, a computer device is proposed, the device comprising:

[0030] A processor, adapted to execute computer programs;

[0031] A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the method for determining the optimal hydraulic path in sandstone as proposed in the first aspect.

[0032] Fourthly, a computer-readable storage medium is proposed, wherein the computer-readable storage medium stores a computer program adapted to be loaded and executed by a processor, the method for determining the optimal hydraulic path in sandstone as proposed in the first aspect.

[0033] Fifthly, a computer program product is proposed, which includes a computer program that, when executed by a processor, implements the method for determining the optimal hydraulic path in sandstone proposed in the first aspect.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0035] This invention proposes a method and system for determining the optimal hydraulic path in sandstone. The method constructs a microscale two-dimensional digital pipeline network, then adds boundary conditions and node and pipeline constraints to this network to obtain a two-dimensional pore network digital rock model. Based on this model, the water pressure difference between the two ends of each pipeline is calculated. Finally, the seepage path with the highest path weight is selected as the optimal hydraulic path for sandstone. This method achieves accurate identification of the optimal hydraulic path in sandstone and has significant theoretical and engineering application value.

[0036] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0037] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application.

[0038] Figure 1 This is a flowchart of a method for determining the optimal hydraulic path in sandstone according to an embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of a small-scale sandstone core thin section sample proposed in an embodiment of the present invention;

[0040] Figure 3 The microstructure of the small-scale sandstone core thin section sample proposed in the embodiments of the present invention;

[0041] Figure 4 This is a probability distribution diagram of the pore size of sandstone samples proposed in an embodiment of the present invention;

[0042] Figure 5 An example diagram of a two-dimensional pore network digital rock model is provided for embodiments of the present invention;

[0043] Figure 6 This is a probability distribution diagram of the pore size after sampling, as proposed in an embodiment of the present invention.

[0044] Figure 7 This is a digital distribution diagram of sandstone pipe pores proposed in an embodiment of the present invention;

[0045] Figure 8 This is a digital water pressure distribution diagram proposed in an embodiment of the present invention;

[0046] Figure 9 This is a seepage path diagram of a digital rock model proposed in an embodiment of the present invention;

[0047] Figure 10 This is a schematic diagram of the optimal hydraulic path and tortuosity for sandstone determined in an embodiment of the present invention. Detailed Implementation

[0048] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0049] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0050] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0051] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0052] To accurately determine the optimal hydraulic path for sandstone, this invention proposes a method for determining the optimal hydraulic path for sandstone. Through scientific modeling and algorithm design, it achieves accurate calculation and systematic analysis of the optimal hydraulic path for sandstone, providing theoretical support and technical tools for applications such as oil and gas development, groundwater management, and reservoir evaluation.

[0053] This invention proposes a method for determining the optimal hydraulic path in sandstone, as shown in the embodiments of the present invention. Figures 1-9 As shown, it includes:

[0054] Obtain a two-dimensional image of the grain size distribution on the surface of sandstone;

[0055] A microscale two-dimensional digital pipeline network was constructed based on a two-dimensional image of the grain size distribution on the surface of sandstone.

[0056] Boundary conditions and node and pipe constraints are added to a microscale two-dimensional digital pipeline network to obtain a two-dimensional pore network digital rock model.

[0057] Based on the two-dimensional pore network digital rock model, the water pressure difference at both ends of each pipe was calculated.

[0058] The pressure difference between the two ends of the pipe is used as the weight of the pipe. The seepage path with the largest path weight is selected as the hydraulically optimal path for sandstone. The path weight of the seepage path is the sum of the weights of all the pipes that the seepage path passes through.

[0059] This invention proposes a method for determining the optimal hydraulic path in sandstone. After constructing a microscale two-dimensional digital pipeline network, boundary conditions and node and pipeline constraints are added to the network to obtain a two-dimensional pore network digital rock model. Based on this model, the water pressure difference between the two ends of each pipeline is calculated. Then, the seepage path with the highest path weight is selected as the optimal hydraulic path for sandstone. This method achieves accurate identification of the optimal hydraulic path in sandstone and has significant theoretical and engineering application value.

[0060] In some embodiments, the distribution law of sandstone pore parameters is determined based on a two-dimensional image of the grain size distribution on the surface of the sandstone.

[0061] Based on the distribution law of sandstone pore parameters, a microscale two-dimensional digital pipeline network is constructed.

[0062] In this embodiment of the invention, sandstone is prepared into small-scale sandstone core thin section samples, and the porosity and permeability of the small-scale sandstone core thin section samples are obtained based on conventional core testing experiments. The surface grain size of the small-scale sandstone core thin section samples is imaged using a Ti2-E fluorescence inverted microscope to obtain a two-dimensional image of the sandstone surface grain size distribution.

[0063] The process involves using appropriate cutting tools to cut sandstone into thin slices with a thickness of 50 micrometers or less to ensure that light can penetrate the slices for easy observation. A polishing machine is then used to smooth the surface of the cut sandstone slices, ensuring that the sample surface is smooth and free of protrusions, resulting in clear imaging and obtaining small-scale sandstone core thin slice samples.

[0064] Place the small-scale sandstone core thin section sample on the stage of the Ti2-E fluorescence inverted microscope, adjust the Ti2-E fluorescence inverted microscope, select an appropriate grain size observation range, start observation with a low-power objective lens until a suitable magnification is reached; adjust the height of the microscope condenser lens and the size of the aperture to make the light shine evenly on the small-scale sandstone core thin section sample, thereby improving the contrast and clarity of the image.

[0065] In the software accompanying the Ti2-E fluorescence inverted microscope, the image resolution was set to obtain high-quality images. The image acquisition function in the software was used to capture two-dimensional images of the surface layer of small-scale sandstone core thin section samples, which were then used as two-dimensional images of the grain size distribution of the sandstone surface. The images were then saved.

[0066] like Figure 2 The image shown is a small-scale sandstone core thin section obtained in an embodiment of the present invention. From a microscopic perspective, the two-dimensional image of the sandstone surface grain size distribution includes sandstone particles (including various detrital particles, interstitial materials, and authigenic minerals), pores (including water and air), and nodes at pore connections, as shown below. Figure 3 As shown.

[0067] The process of determining the distribution law of sandstone pore parameters based on the two-dimensional image of sandstone surface grain size distribution includes:

[0068] Extract a two-dimensional pixel array from a two-dimensional image of the grain size distribution on the surface of sandstone;

[0069] Extract a two-dimensional image of sandstone from a two-dimensional pixel array;

[0070] Two-dimensional images of sandstone are identified to determine the distribution pattern of sandstone pore parameters.

[0071] The distribution patterns of sandstone pore parameters include pore connectivity and pore diameter.

[0072] This invention embodiment is based on the Fiji image processing platform. It performs particle analysis on the obtained two-dimensional image of the sandstone surface and performs batch processing through a morphological operation plugin to extract the two-dimensional pixel array of the two-dimensional image of the sandstone surface particle size distribution.

[0073] Subsequently, pixel processing techniques were used to denoise, extract contours, and segment the two-dimensional pixel array to obtain a two-dimensional image of sandstone.

[0074] This invention employs Gaussian filtering to perform noise reduction on a two-dimensional pixel array, aiming to eliminate imaging noise and preserve true edges. The formula for Gaussian filtering is as follows:

[0075] .

[0076] in, This is the filtered image; It is a two-dimensional pixel array; These are normalization coefficients; care should be taken to avoid over-smoothing, which can lead to blurred edges. x , y These are the pixel coordinates in the image, corresponding to the horizontal and vertical positions of a point on the image plane, used to locate specific pixel points; σ It is the standard deviation of the Gaussian function.

[0077] Canny edge detection is used to extract contours from the filtered image. After Gaussian filtering and smoothing the two-dimensional pixel array, the gradient magnitude (Sobel operator) needs to be calculated. The calculation formula is as follows:

[0078] .

[0079] in, To represent the calculated gradient magnitude, reflecting the total degree of grayscale change at a point in a two-dimensional pixel array in two directions; The result is obtained by applying the Sobel operator to the image and taking the derivative in the horizontal direction, reflecting the rate of gray-level change of the pixel array at that point along the horizontal direction; The result is obtained by applying the Sobel operator to the image and taking the derivative in the vertical direction, reflecting the rate of gray-level change of the pixel array at that point along the vertical direction. Represents the direction of the gradient, describing the direction of the greatest change in grayscale at that pixel.

[0080] After calculating the gradient magnitude of the 2D pixel array, non-maximum suppression is performed to refine the edges. Finally, a double-threshold hysteresis connection is applied, with a standard deviation of 1.0 used for the Gaussian kernel. It should be noted that Canny edge detection is sensitive to noise and requires noise reduction processing beforehand.

[0081] The Otsu algorithm in threshold segmentation is used to segment the identified contours to obtain a two-dimensional image of sandstone. The Otsu algorithm can automatically calculate the optimal threshold. T The formula for maximizing the between-class variance is as follows:

[0082] .

[0083] in, T Represents the segmentation threshold; Indicates the threshold is T Between-class variance over time; Indicates the segmentation threshold is T At that time, the proportion of foreground elements in the image; Indicates the threshold is T At that time, the proportion of the background class in the image; Indicates the threshold is T At that time, the average gray value of the foreground class; Indicates the threshold is T At that time, the average gray value of the background class.

[0084] Based on the Otsu algorithm described above, the difference between the image before and after segmentation is most obvious.

[0085] This invention identifies and statistically analyzes the pixel area of ​​each pore in a two-dimensional image of sandstone. A Parameters such as perimeter are used. The aperture of each aperture is further calculated using the pixel area of ​​each aperture. The formula for calculating the pore diameter of each pore is as follows:

[0086] .

[0087] In the formula, A The pixel area of ​​the aperture. The pore diameter is denoted by .

[0088] This invention embodiment performs probability distribution statistics on the pore size of pores determined from two-dimensional images of sandstone to determine the probability distribution curve of the pore size, such as... Figure 4 As shown, by Figure 4 It can be seen that the pore distribution of the sandstone sample roughly follows a log-normal distribution, with a mean of 72 micrometers and a standard deviation of 0.49479.

[0089] Multiple pore sizes are obtained by randomly sampling pore sizes based on the probability distribution curve of the pore size. The probability distribution function of the sampled pore size is as follows: Figure 6 As shown.

[0090] Figure 7 The digital distribution structure of sandstone pipe pores ranging from 0.1 micrometers to 1000 micrometers in a microscale two-dimensional digital pipe network is shown. The pipe radius exhibits a random distribution state based on a log-normal distribution.

[0091] Based on the sandstone pore parameter distribution patterns obtained from the above calculations, pores are characterized by pipes, nodes are defined by the connections between pores, and the pore diameter is used as the corresponding pipe diameter. A microscale two-dimensional digital pipe network is constructed using a square mesh in data simulation software. In this network, the pipe diameter is equal to the pore diameter corresponding to the pipe. In a microscale two-dimensional digital pipeline network, all pipelines have the same length.

[0092] Preferably, a 50x50 grid network is used to construct a microscale two-dimensional digital pipeline network, with horizontal pipelines represented by 0 and vertical pipelines represented by 1. The diameter of each pipeline varies but the length is the same, and the diameter of each pipeline is the diameter of the corresponding pore.

[0093] The data simulation software used here can be MATLAB, etc.

[0094] To simulate seepage within pores, this embodiment of the invention adds boundary conditions and node and pipe constraints to a microscale two-dimensional digital pipeline network.

[0095] The boundary conditions added to the microscale two-dimensional digital pipeline network include: setting the upstream surface water pressure of the microscale two-dimensional digital pipeline network to 1, the downstream surface water pressure to 0, and setting no flux on the left and right sides of the microscale two-dimensional digital pipeline network.

[0096] Figure 5 The boundary conditions and pipeline node coordinate distribution of the sandstone two-dimensional digital pipeline network constructed according to embodiments of the present invention are described.

[0097] The node and pipe constraints added to the microscale two-dimensional digital pipeline network include: water flow mode, pipeline flow constraint, and node inflow and outflow equality constraint; among which, the pipeline flow constraint adopts the Poiseuille formula.

[0098] In this embodiment of the invention, the water flow in the microscale two-dimensional digital pipeline network is set as laminar flow, with each layer not affecting the others, and the water flow velocity distribution is parabolic.

[0099] The pipeline flow constraint uses Poiseuille's formula, which is:

[0100] .

[0101] in, For pipeline flow rate, The viscosity of the fluid in the pipe. The water pressure difference between the two ends of the pipe. This refers to the water pressure value at the inlet node of the pipeline. This refers to the water pressure value at the outlet node of the pipeline. This represents the length of the pipe.

[0102] The node inflow-outflow equality constraint means that for each node in a microscale two-dimensional digital pipeline network, the sum of the inflows to the nodes (total inflow to the nodes) equals the sum of the outflows to the nodes (total outflow to the nodes). Therefore, the following formula is used to characterize the node inflow-outflow equality constraint:

[0103] .

[0104] In the formula, This is the difference between the total flow into the node and the total flow out of the node.

[0105] Boundary conditions and node and pipe constraints are added to a microscale two-dimensional digital pipeline network to obtain a two-dimensional pore network digital rock model.

[0106] By adding node and pipe constraints to a microscale two-dimensional digital pipe network by defining the water flow mode, Poiseuille's formula, and the constraint of equal inflow and outflow at nodes, a two-dimensional porous network digital rock model is obtained to describe the flow rate law when water undergoes laminar flow in the two-dimensional pipe network. The flow rate of each pipe, the water pressure at both ends of the pipe, and the water pressure difference between the two ends of the pipe are calculated using the two-dimensional porous network digital rock model. Figure 8 As shown, this is a digital distribution diagram of water pressure in a two-dimensional pore network digital rock model. The digital distribution diagram shows that the water pressure gradually decreases from top to bottom until it changes from 1 to 0.

[0107] This invention generates a seepage path diagram of a digital rock model based on a two-dimensional pore network digital rock model. This path diagram contains all seepage paths in sandstone.

[0108] Calculate the path weight of each seepage path in sandstone;

[0109] The seepage path with the largest path weight is selected as the hydraulically optimal path for sandstone.

[0110] The path weight of the seepage path is the sum of the weights of all pipes that the seepage path passes through, and the weight of a pipe is equal to the absolute value of the water pressure difference between its two ends.

[0111] This embodiment of the invention also obtains the actual length of the optimal hydraulic path for sandstone, and the straight-line distance between the starting node and the ending node of the optimal hydraulic path for sandstone.

[0112] The tortuosity of the optimal hydraulic path for sandstone is calculated based on the actual length of the path and the straight-line distance between the starting and ending nodes.

[0113] This invention's embodiments analyze the aforementioned two-dimensional pore network digital rock model based on a path algorithm, generating, as follows: Figure 9 The digital rock model seepage path diagram is shown, from which the hydraulically optimal path is obtained and the tortuosity is calculated. The specific process is as follows:

[0114] The path algorithm uses Dijkstra's algorithm to perform optimal path analysis on a two-dimensional pore network digital rock model to obtain the hydraulically optimal path.

[0115] Let the set of nodes in the two-dimensional porous network digital rock model be . The pipeline assembly is Source The starting node (upstream face node) and ending node of the hydraulic path. This is the terminal node (downstream face node) of the hydraulic path. The weights of the pipes between adjacent nodes u and v in each hydraulic path are also considered. Defined as the absolute value of the water pressure difference between the two ends of the pipe connecting node u and node v, i.e.:

[0116] .

[0117] in, , These are the water pressure values ​​at node u at one end of the pipeline and the water pressure values ​​at node v at the other end of the pipeline, respectively. The larger the absolute value of the water pressure difference between the two ends of the pipeline, the greater the flow rate in the pipeline, and therefore the higher the weight.

[0118] In Dijkstra's algorithm, a distance array d[v] is introduced, representing the current known maximum cumulative path weight from the source node s to node v. The initialization condition is set to d[s] = 0.

[0119] During the algorithm iteration, for the current node u, traverse all its adjacent nodes v, if the following conditions are met... If the path weight from the source point through u to v is greater than the currently recorded d[v], then d[v] is updated, and the predecessor node is recorded for subsequent path backtracking.

[0120] like Figure 9The diagram shows the seepage path of a two-dimensional pore network digital rock model. The scale bar on the right shows the percentage of the maximum flow rate in the pipe. Each seepage path is tortuous and branching, reflecting the complex connectivity of the pore network. The diagram also shows that the main seepage channel carries most of the flow rate of the pipe network (close to 50% of the maximum flow rate), while water flow is difficult to pass through the secondary seepage paths, reflecting the distinction between effective and ineffective pores in the pore network.

[0121] The tortuosity of the optimal hydraulic path in sandstone is calculated using the following formula:

[0122] .

[0123] in, The actual length of the hydraulically optimal path for sandstone. This represents the straight-line distance between the starting and ending nodes of the optimal hydraulic path for sandstone.

[0124] like Figure 10 As shown, it is based on Figure 9 The obtained optimal hydraulic path diagram for sandstone has a tortuosity of 1.4286.

[0125] This invention constructs a digital rock model of a two-dimensional pipeline network and then accurately identifies the optimal hydraulic path in sandstone based on an improved Dijkstra algorithm. Compared with traditional methods that rely solely on macroscopic parameter calculations or geometric empirical rules, this invention comprehensively considers the physical coupling relationship between pore structure characteristics and hydraulic parameters, effectively solving the problem of difficulty in identifying the main seepage channel under conditions of strong heterogeneity and complex structure. At the same time, by calculating the tortuosity of the optimal hydraulic path in sandstone before and after reconstruction, a quantitative evaluation of the path optimization effect is achieved. It features high model accuracy and wide engineering applicability, and can provide important theoretical support and technical tools for oil and gas deployment, groundwater flow analysis, and porous media seepage research.

[0126] This invention also proposes a system for determining the optimal hydraulic path in sandstone, comprising:

[0127] The image acquisition unit is used to acquire two-dimensional images of the grain size distribution on the surface of sandstone.

[0128] A microscale two-dimensional digital pipeline network construction unit is used to construct a microscale two-dimensional digital pipeline network based on a two-dimensional image of the grain size distribution on the surface of sandstone.

[0129] A two-dimensional porous network digital rock model building unit is used to add boundary conditions and node and pipe constraints to a micro-scale two-dimensional digital pipeline network to obtain a two-dimensional porous network digital rock model.

[0130] The unit for determining the water pressure difference at both ends of the pipeline is used to calculate the water pressure difference at both ends of each pipeline based on a two-dimensional pore network digital rock model.

[0131] The sandstone hydraulic optimal path determination unit is used to take the water pressure difference between the two ends of the pipe as the weight of the pipe, and select the seepage path with the largest path weight as the sandstone hydraulic optimal path. The path weight of the seepage path is the sum of the weights of all pipes that the seepage path passes through.

[0132] It should be noted that the sandstone hydraulic optimal path determination system provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the equipment can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the sandstone hydraulic optimal path determination system and the sandstone hydraulic optimal path determination method embodiment provided in the above embodiments belong to the same concept, and their specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0133] The present invention also discloses a computer device, the device comprising:

[0134] A processor, adapted to execute computer programs;

[0135] A computer-readable storage medium storing a computer program, which, when executed by the processor, implements a method for determining the optimal hydraulic path in sandstone according to an embodiment of the present invention.

[0136] The present invention also discloses a computer-readable storage medium storing a computer program adapted for loading and execution by a processor of a method for determining the optimal hydraulic path in sandstone according to embodiments of the present invention.

[0137] The present invention also discloses a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements a method for determining the optimal hydraulic path in sandstone as proposed in the embodiments of the present invention.

[0138] The method proposed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0139] Those skilled in the art will recognize that the units and algorithm steps described in conjunction with the embodiments herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0140] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for determining the optimal hydraulic path in sandstone, characterized in that, include: Obtain a two-dimensional image of the grain size distribution on the surface of sandstone; The distribution law of sandstone pore parameters was determined based on the two-dimensional image of the grain size distribution on the surface of the sandstone. Based on the distribution law of sandstone pore parameters, a microscale two-dimensional digital pipeline network is constructed; Boundary conditions and node and pipe constraints were added to a microscale two-dimensional digital pipeline network to obtain a two-dimensional pore network digital rock model. The boundary conditions included setting the upstream water pressure of the microscale two-dimensional digital pipeline network to 1 and the downstream water pressure to 0, and setting no flux on the left and right sides of the microscale two-dimensional digital pipeline network. The node and pipe constraints included: water flow mode, pipe flow constraint, and node inflow and outflow equality constraint; among which, the pipe flow constraint adopted the Poiseuille formula. Based on the two-dimensional pore network digital rock model, the water pressure difference at both ends of each pipe was calculated. The pressure difference between the two ends of the pipe is used as the weight of the pipe. The seepage path with the largest path weight is selected as the hydraulically optimal path for sandstone. The path weight of the seepage path is the sum of the weights of all the pipes that the seepage path passes through.

2. The method for determining the optimal hydraulic path in sandstone as described in claim 1, characterized in that, It also obtains the actual length of the optimal hydraulic path for sandstone, as well as the straight-line distance between the starting and ending nodes of the optimal hydraulic path for sandstone. The tortuosity of the optimal hydraulic path for sandstone is calculated based on the actual length of the path and the straight-line distance between the starting and ending nodes.

3. The method for determining the optimal hydraulic path in sandstone as described in claim 1, characterized in that, Extract a two-dimensional pixel array from a two-dimensional image of the grain size distribution on the surface of sandstone; Extract a two-dimensional image of sandstone from a two-dimensional pixel array; Two-dimensional images of sandstone are identified to determine the distribution pattern of sandstone pore parameters.

4. A system for determining the optimal hydraulic path in sandstone, characterized in that, include: The image acquisition unit is used to acquire two-dimensional images of the grain size distribution on the surface of sandstone. A microscale two-dimensional digital pipeline network construction unit is used to determine the distribution law of sandstone pore parameters based on a two-dimensional image of sandstone surface grain size distribution; and to construct a microscale two-dimensional digital pipeline network based on the distribution law of sandstone pore parameters. A two-dimensional porous network digital rock model construction unit is used to add boundary conditions and node and pipe constraints to a microscale two-dimensional digital pipeline network to obtain a two-dimensional porous network digital rock model. The boundary conditions include: setting the upstream water pressure of the microscale two-dimensional digital pipeline network to 1 and the downstream water pressure to 0, and setting no flux on the left and right sides of the microscale two-dimensional digital pipeline network. The node and pipe constraints include: water flow mode, pipe flow constraint, and node inflow and outflow equality constraint; among which, the pipe flow constraint adopts the Poiseuille formula. The unit for determining the water pressure difference at both ends of the pipeline is used to calculate the water pressure difference at both ends of each pipeline based on a two-dimensional pore network digital rock model. The sandstone hydraulic optimal path determination unit is used to take the water pressure difference between the two ends of the pipe as the weight of the pipe, and select the seepage path with the largest path weight as the sandstone hydraulic optimal path. The path weight of the seepage path is the sum of the weights of all pipes that the seepage path passes through.

5. An electronic device, characterized in that, The device includes: A processor, adapted to execute computer programs; A computer-readable storage medium storing a computer program, which, when executed by the processor, implements the method for determining the optimal hydraulic path in sandstone as described in any one of claims 1-4.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded by a processor and executed by a method for determining the optimal hydraulic path in sandstone as described in any one of claims 1-4.

7. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method for determining the optimal hydraulic path in sandstone as described in any one of claims 1-4.

Images