Meshless connected unit method based on the integration of profile control and flooding simulation and channeling prevention method, system and readable medium

Abstract

This invention belongs to the field of oil and gas development technology, and relates to a method, system, and readable medium for integrated simulation and crossflow prevention based on the meshless connected element method. The method includes: arranging nodes in the computational domain using an adaptive point placement algorithm based on reservoir geological parameters; constructing a meshless connected element model based on generalized finite difference theory; fitting the meshless connected element model to historical production data from chemical flooding to obtain the pressure potential energy distribution of each node, and constructing a directed pressure potential energy graph for the entire field; starting from the injection well, traversing all potential flow paths connecting injection and production wells in the directed pressure potential energy graph to establish an integrated simulation and crossflow model; classifying the crossflow situation of the flow paths according to the integrated simulation and crossflow model, and generating the optimal prevention scheme based on the classification results. This invention overcomes the problems of mesh orientation effect and low computational efficiency of traditional mesh methods, and achieves visualized prevention of hidden crossflow channels in deep reservoirs.

Description

Technical Field

[0001] This invention relates to a method, system, and readable medium for integrated simulation of regulation and drive and prevention of crossflow based on the meshless connected unit method, belonging to the field of oil and gas development technology. Background Technology

[0002] Most of my country's major oilfields have entered the late stage of development with high or ultra-high water cut. Long-term water injection has led to extremely complex flow fields within the reservoirs, with prominent ineffective circulation (i.e., crossflow) of injected water along high-permeability strips or large channels, severely restricting the improvement of oil recovery. Implementing integrated regulation and flooding, combining deep fluid flow diversion with chemical flooding, is a key means to solve this problem. However, existing numerical simulation technologies face the following challenges in guiding the design of integrated regulation and flooding schemes: Traditional grid-based methods have limitations: to accurately characterize the front of the chemical agent and complex crossflow channels, extremely high-density grids are required, resulting in huge computational time, and there is a difficult-to-eliminate grid orientation effect, making it difficult to accurately simulate oblique or tortuous flow paths. Although existing connectivity models are computationally efficient, they often simplify the relationship between wells to a "point-to-point" straight-line connection, lacking a detailed description of the non-Newtonian fluid rheology, adsorption retention, and permeability reduction mechanisms of the chemical agent; at the same time, existing models cannot automatically identify complex and circuitous topological paths containing virtual nodes between injection and production wells, resulting in the invisibility of crossflow channels. Therefore, there is an urgent need for a numerical simulation method that can both efficiently identify complex flow field topologies and accurately simulate the physical processes of chemical flooding. Summary of the Invention

[0003] To address the aforementioned problems, the purpose of this invention is to provide an integrated simulation and crossflow prevention method, system, and readable medium based on the meshless connected element method. This method combines generalized finite difference and depth-first search (DFS) algorithms to achieve integrated diagnosis and treatment of deep reservoir flow fields.

[0004] To achieve the above objectives, this invention proposes the following technical solution: a method for integrated simulation and crossflow prevention based on the meshless connected element method, comprising the following steps: arranging nodes in the computational domain using an adaptive point placement algorithm according to reservoir geological parameters; constructing a meshless connected element model based on generalized finite difference theory according to node positions; fitting the meshless connected element model with historical production data from chemical flooding to obtain the pressure potential energy distribution of each node, and constructing a directed graph of pressure potential energy across the entire field; starting from the injection well, traversing all potential flow paths connecting injection and production wells in the directed graph of pressure potential energy across the entire field, and establishing an integrated simulation and flow prevention model; classifying the crossflow situation of the flow paths according to the integrated simulation and flow prevention model, and generating the optimal prevention scheme based on the classification results.

[0005] Furthermore, the method for constructing the meshless connected unit model is as follows: based on the generalized finite difference theory, using Taylor expansion and weighted least squares method, the physical information in the node control domain is transformed into the geometric properties of the connected unit, and the connection conductivity and connection volume between nodes are calculated.

[0006] Furthermore, the conductivity of the connection The formula for calculating the flow-conducting capacity of the connecting unit is as follows:

[0007] in, The penetration rate of the connecting unit; This refers to the flow rate or proportionality coefficient. For nodes Controlling volume, and All are generalized difference geometric coefficients, where m is the number of rows in the generalized difference coefficient matrix; The connecting volume is based on the principle of material balance, distributing the total reservoir volume to each connecting unit as a spatial carrier for the storage of fluids and chemical agents. Its calculation formula is as follows:

[0008] in, It is the volume of connection. It is the conductivity of the connection; It is the node spacing; N is the total reservoir volume, and N is the number of discrete nodes in the reservoir.

[0009] Furthermore, the integrated profile control model establishes a seepage-mass transfer coupling equation on the connection network of the directed graph of the full-field pressure potential energy. The seepage-mass transfer coupling equation includes non-Newtonian fluid characteristics, adsorption mechanism, and permeability reduction mechanism. The non-Newtonian fluid characteristics consider the shear dilution effect of the polymer solution and use a power-law mode to correct the effective viscosity. The adsorption mechanism uses the Langmuir isotherm adsorption equation to describe the adsorption behavior of the chemical agent on the rock surface and calculates the concentration loss. The permeability reduction mechanism introduces a residual resistance coefficient to describe the obstruction effect of the chemical agent on the flow of the aqueous phase after adsorption, thereby simulating the water shut-off effect during profile control.

[0010] Furthermore, the flow path is a complex, circuitous path containing virtual nodes, and the path splitting coefficient of each flow path is calculated based on the directed graph of the overall pressure potential energy. The calculation formula is as follows:

[0011] in, Representative node arrive Traffic; For nodes The total outflow, where n is the nth time step. This refers to the number of connection units with J as the downstream point.

[0012] Furthermore, based on the aforementioned integrated control and drive model, a crossflow factor is calculated. This crossflow factor is used to classify the crossflow situation along the flow path. The calculation formula is:

[0013] in, The average conductivity of the path connection; The average connectivity volume of the path; The characteristic ratio of the flow velocity; This is the average characteristic value for the entire field.

[0014] Furthermore, the crossflow situation of the flow path is divided into four levels by the crossflow factor: crossflow factor This is a super-grade flow, corresponding to large-scale fissures or karst cave passages; This indicates strong crossflow, corresponding to high-permeability strips; If the flow is intermittent, it corresponds to the general dominant seepage channel. This represents matrix seepage, corresponding to the normal displacement zone.

[0015] Furthermore, based on the grading results, the optimal prevention and control scheme is generated as follows: The super-grade crossflow channel is based on a meshless connecting unit model, identifying and locating the set of connecting units contained in the crossflow path, and predicting the injection effect of high-strength gel or cross-linked polymer through numerical simulation; at the level of integrated model parameter correction, a very small cutoff factor is introduced to affect the connectivity conductivity of the connecting units. Significant reduction is made, bringing it close to zero, thereby forcibly blocking this invalid water circulation loop in the connected topology network; the strong crossflow channel is dynamically adjusted by modifying the connection volume. Parameters are used to characterize the adsorption and retention effects of chemical agents within the connecting unit; local seepage resistance is increased, and streamlines are redistributed from high-permeability channels to medium- and low-permeability regions.

[0016] This invention also discloses an integrated simulation and crossflow prevention system based on the meshless connected element method, comprising: a node step module, used to arrange nodes in the computational domain according to reservoir geological parameters using an adaptive point placement algorithm; a meshless model construction module, used to construct a meshless connected element model based on generalized finite difference theory according to node positions; a full-field pressure potential energy directed graph construction module, used to fit the meshless connected element model with historical production data of chemical flooding to obtain the pressure potential energy distribution of each node and construct a full-field pressure potential energy directed graph; a depth-first search module, used to traverse all potential injection-production well connected flow paths in the full-field pressure potential energy directed graph, starting from the injection well, to establish an integrated simulation and crossflow prevention model; and a prevention scheme generation module, used to classify the crossflow situation of the flow path according to the integrated simulation and crossflow prevention model and generate the optimal prevention scheme according to the classification results.

[0017] The present invention also discloses a computer-readable storage medium storing a computer program, which is executed by a processor to implement the integrated simulation and cross-current prevention method based on the meshless connection element method as described in any of the preceding claims.

[0018] The technical solution of the present invention has at least the following technical effects or advantages: The present invention overcomes the problems of grid orientation effect and low computational efficiency of traditional grid methods, and realizes the visualization and prevention of hidden channel flow in deep oil reservoirs. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of a meshless connected unit model in one embodiment of the present invention; Figure 2 This is a schematic diagram of the connectivity of the study area in one embodiment of the present invention; Figure 3 These are two dominant flow paths between injection and production wells selected in the study area in one embodiment of the present invention. Figure (a) shows the first dominant flow path and Figure (b) shows the second dominant flow path. Figure 4 This is a schematic diagram of a connected path in one embodiment of the present invention; Figure 5 This is a diagram showing the splitting coefficient distribution in one embodiment of the present invention; Figure 6 This is an inter-well path diagram in one embodiment of the present invention; Figure 7 This is a dynamic simulation diagram of the entire production cycle of the ST-65 oilfield in one embodiment of the present invention; Figure 8Figure (a) is a dynamic simulation diagram of the entire oilfield production cycle during the generation of the optimal prevention and control scheme in one embodiment of the present invention. Figure (b) is a diagram of the cumulative oil production change of the block, Figure (c) is a diagram of the water cut change of the block, and Figure (d) is a diagram of the daily oil production change of the A23 single well. Figure 9 This is a distribution diagram of the change in conductivity of the connection after the integrated simulation of regulation and drive and the method for preventing cross-current in one embodiment of the present invention. Detailed Implementation

[0020] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention is described in detail through specific embodiments. However, it should be understood that the specific embodiments are provided only for a better understanding of the present invention and should not be construed as limiting the present invention. In the description of the present invention, it should be understood that the terminology used is for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0021] To address the problems of grid orientation effect and low computational efficiency in existing technologies, this invention proposes a method, system, and readable medium for integrated simulation and crossflow prevention based on the meshless connected element method. The method includes the following steps: 1) Arranging nodes in the computational domain using an adaptive point placement algorithm based on reservoir geological parameters; 2) Constructing a meshless connected element model based on generalized finite difference theory according to the node locations; 3) Fitting the meshless connected element model to historical production data from chemical flooding to obtain the pressure potential energy distribution of each node, thus constructing a directed pressure potential energy graph for the entire field; 4) Starting from the injection well, traversing all potential flow paths connecting injection and production wells in the directed pressure potential energy graph to establish an integrated simulation and crossflow model; 5) Classifying the crossflow situation of the flow paths according to the integrated simulation and crossflow model, and generating the optimal prevention scheme based on the classification results. This invention overcomes the problems of grid orientation effect and low computational efficiency in traditional grid methods, achieving visualized prevention of hidden crossflow channels in deep reservoirs. The invention is described in detail below with reference to the accompanying drawings.

[0022] Example 1 This embodiment takes a major oil-bearing fault block in an oilfield as an example and discloses an integrated simulation and crossflow prevention method based on the meshless connected element method, including the following steps: S1 arranges nodes in the computational domain based on reservoir geological parameters using an adaptive node placement algorithm.

[0023] To address the complex fault boundaries and heterogeneous properties of the target block, nodes are generated and arranged within the computational domain, including well points and encrypted virtual nodes.

[0024] S2 constructs a meshless connected element model based on the node positions and the generalized finite difference theory.

[0025] like Figure 1 As shown, the method for constructing a meshless connected element model is as follows: Based on generalized finite difference theory, using Taylor expansion and weighted least squares method, the physical information within the node control domain is transformed into the geometric properties of the connected elements, and the connection conductivity and connection volume between nodes are calculated. The mesh system represents the physical information on the mesh. In a special case, the mesh center is taken as the node, and then a connected system is constructed. Two parameters, connection conductivity and connection volume, are assigned to the connected system. These parameters are calculated using the node location information and the aforementioned physical properties. Therefore, the physical properties of the nodes are transformed into parameters on the connected elements. Figure 1 The diagram clearly illustrates the topological connections between nodes, with the dark, thick solid lines visually representing the pre-defined high-permeability strips in the geological model. This demonstrates that the meshless interconnected unit model can accurately map hidden geological properties into a visualized fluid-dominant seepage network even without a mesh.

[0026] Connection conductivity The formula for calculating the flow-conducting capacity of the connecting unit is as follows:

[0027] in, The penetration rate of the connecting unit; This refers to the flow rate or proportionality coefficient. For nodes Controlling volume, and All are generalized difference geometric coefficients, where m is the number of rows in the generalized difference coefficient matrix; The connecting volume, based on the principle of mass balance, allocates the total reservoir volume to each connecting unit, serving as a spatial carrier for the storage of fluids and chemical agents. Its calculation formula is as follows:

[0028] in, It is the volume of connection. It is the conductivity of the connection; It is the node spacing; N is the total reservoir volume, and N is the number of discrete nodes in the reservoir.

[0029] S3 fits the meshless connected unit model to historical chemical flooding production data to obtain the pressure potential energy distribution of each node, constructs a directed graph of pressure potential energy across the entire field, and transforms the undirected connected network into a directed graph of pressure potential energy across the entire field based on the pressure gradient direction between nodes.

[0030] Based on the simulated nodal pressure distribution, the fluid flow direction is determined. Using a depth-first search (DFS) algorithm, starting from the injection well node, all possible flow branches are traversed until the production well, searching for all potential "injection well-virtual node-production well" connected sequences throughout the entire field. For example... Figure 2 As shown, Figure 2 The circular symbols represent different types of well points: white (injection wells), red (production wells), and black (virtual wells). The well points are connected by line segments, each corresponding to a connected unit. Each connected unit is marked with an arrow that clearly indicates the direction of fluid flow, providing an intuitive reference for analyzing the injection-production relationship. Figure 3 These are the selected dominant flow paths between two injection and production wells. Each line in the diagram represents a specific underground flow path, rather than a simple straight line connection.

[0031] The Depth-First Search (DFS) algorithm is used to automatically trace complex, circuitous flow paths containing virtual nodes between injection and production wells in the directed graph of the overall pressure and potential energy, and to calculate the path splitting coefficients. The path splitting coefficients for each flow path are then calculated based on the directed graph of the overall pressure and potential energy. The calculation formula is as follows:

[0032] in, Representative node arrive Traffic; For nodes The total outflow, where n is the nth time step. The number of connection units with J as the downstream point.

[0033] The connectivity path of the ST-65 block, a major oil-bearing fault block in a certain oilfield, is as follows: Figure 4 As shown, it achieves the skeletal extraction of the intricate underground fluid network structure, intuitively demonstrating the macroscopic flow distribution of injected water between wells. The splitting coefficient distribution of the ST-65 block is as follows: Figure 5 As shown. Figure 4 and Figure 5 The study not only demonstrates the complex "well-to-well" and "well-to-virtual node" topology between injection and production wells, but also intuitively characterizes the splitting coefficient of each path through the features of the connecting lines. This reflects the flow distribution weight of the fluid among the network nodes in the initial state, thus establishing the benchmark matrix for flow field diagnosis. Figure 5 The color intensity of the path represents the magnitude of the geometric splitting coefficient. The larger the splitting coefficient, the higher the traffic weight that path carries in the topology.

[0034] The path splitting factor is generalized to any path (including multiple simple paths), and the formula is:

[0035] in, It is the splitting coefficient of any path (composed of multiple connecting units connected end to end). It is the splitting coefficient of one of the simple paths.

[0036] This indicator directly reflects the hydraulic contribution of the path. If a certain path's... If the pressure distribution is significantly higher than other paths, then that path is determined to be the dominant flow channel. Based on the node pressure distribution and its gradient direction calculated from the meshless connected element model, the original undirected network is transformed into a directed graph of full-field pressure potential energy.

[0037] Starting with the injection well, S4 traverses all potential injection and production well connections and flow paths in the entire field pressure potential energy directional graph to establish an integrated regulation and drive model.

[0038] The integrated profile control model establishes a flow-mass transfer coupling equation on the connected network of the directed graph of pressure and potential energy across the entire field. This equation includes non-Newtonian fluid characteristics, adsorption mechanisms, and permeability reduction mechanisms. The non-Newtonian fluid characteristics consider the shear dilution effect of the polymer solution, using a power-law model to correct for the effective viscosity. The adsorption mechanism employs the Langmuir isotherm adsorption equation to describe the adsorption behavior of the chemical agent on the rock surface and calculates the concentration loss. The permeability reduction mechanism introduces a residual drag coefficient to describe the hindering effect of the adsorbed chemical agent on the flow of the aqueous phase, thus simulating the water shut-off effect during profile control. It simulates the movement of the plugging agent along high-conductivity channels and dynamically updates the permeability reduction coefficient based on the adsorption amount. .

[0039] Starting with the injection well node, a depth-first search algorithm is used to traverse all possible connectivity paths between injection and production wells, constructing an inter-well connectivity topology network for the study block. The resulting inter-well connectivity diagram comprehensively reflects the actual hydraulic connectivity relationships between injection wells, production wells, and virtual nodes. Lines represent effective connectivity paths, and arrows indicate the actual flow direction of fluid under pressure, providing a topological foundation for subsequent path splitting coefficient calculation, dominant flow path identification, and crossflow channel classification. Figure 6 As shown.

[0040] Based on the meshless interconnected element model, the construction of the Lorentz curve depends on two core physical parameters: inter-well conductivity, which reflects the seepage rate. Interwell connectivity volume characterizing the material basis Cumulative flow capacity ( ): Indicates the order after sorting. The sum of the conductivity of each connecting unit represents the cumulative proportion of the total conductivity of the entire field, characterizing the dynamic contribution of the fluid flow. Its calculation formula is:

[0041] In the formula, Cumulative liquidity; : Connectivity conductivity.

[0042] Cumulative storage capacity ( ): Indicates the order after sorting. The cumulative share of the total connection volume of each connection unit to the total connection volume of the entire field represents the static contribution of the reservoir space. Its calculation formula is:

[0043] In the formula, This represents the total number of connection units. The x-axis is... The curve plotted with the vertical axis is the Lorenz curve of the dynamic connectivity of this reservoir model.

[0044] To transform curve characteristics into quantitative evaluation indicators, the Lorentz coefficient is defined. The area enclosed by the Lorenz curve and the perfectly homogeneous line (i.e., the diagonal) is twice the area between them. Its mathematical expression is:

[0045] In the formula, The area enclosed by the Lorenz curve and the horizontal axis.

[0046] S5 classifies the crossflow situation along the flow path based on the integrated regulation and drive model, and generates the best prevention and control plan based on the classification results.

[0047] The crossflow factor is calculated based on the integrated control and drive model. The crossflow situation along the flow path is classified using this factor. A zero-boundary crossflow factor is constructed by combining the Lorentz coefficient. The calculation formula is:

[0048] in, The average conductivity of the path connection; The average connectivity volume of the path; The characteristic ratio of the flow velocity; The average characteristic value for the entire game. and These are the weighting coefficients. .

[0049] The crossflow situation in the flow path is divided into four levels based on the crossflow factor: crossflow factor This is a super-grade flow, corresponding to large-scale fissures or karst cave passages; This indicates strong crossflow, corresponding to high-permeability strips; If the flow is intermittent, it corresponds to the general dominant seepage channel. The matrix seepage corresponds to the normal displacement zone, and the classification results are shown in Table 1. Figure 7 The diagram differentiates the paths based on the severity of crossflow: Extreme crossflow channel: The diagram clearly shows the main inrush channel from well I1 to well P5. This type of channel has extremely strong flow-carrying capacity and is the root cause of water flooding in production wells. Strong flow channel: The yellow paths in the diagram represent secondary dominant channels, which have a strong diversion effect on the injected water. Weak crossflow channels: These are the typical dominant seepage channels. Matrix seepage channels: This is a normal displacement area. It transforms the geometric flow path into a clearly defined hierarchical flow channel, precisely identifying the key targets that need to be addressed.

[0050] Table 1. Dominant Channel Classification Based on Crossflow Factor

[0051] Based on the classification results of the crossflow channels in Table 1, the optimal prevention and control scheme is generated. For the super-grade crossflow channels, a "forced cutoff" control strategy is adopted. Specifically, based on a meshless connecting unit model, the set of connecting units contained in the crossflow path is identified and located. The injection effect of high-strength gel or cross-linked polymer is predicted through numerical simulation. At the level of integrated model parameter correction, a very small cutoff factor is introduced to affect the connectivity conductivity of the connecting units. By significantly reducing the value to near zero, the invalid water circulation loop is forcibly blocked in the connected topology network, effectively suppressing short-circuit flow.

[0052] The method for obtaining the minimum cutoff factor is as follows: By analyzing the migration of the injected reagent near the well, the amount of reagent entering each connecting unit connected to the well point is calculated. A cutoff factor is determined by the ratio of the reagent dosage to the volume of the connecting unit. The specific value of the cutoff factor is obtained through interpolation. Alternatively, a one-dimensional displacement experiment with a specific reagent can be performed beforehand, and a graph showing the decrease in reagent inflow and seepage capacity can be plotted. The minimum cutoff factor can then be obtained from this graph.

[0053] The strong crossflow channel employs a "seepage field reconstruction" control strategy, dynamically correcting the connection volume. Parameters are used to characterize the adsorption and retention effects of chemical agents in the connecting unit; the adjustment of the connecting volume corresponds in a physical sense to the change of the equivalent pore volume and characteristic flow velocity of the fluid in the unit, thereby increasing the local seepage resistance and inducing the redistribution of streamlines from high-permeability channels to medium- and low-permeability regions, thus achieving a balanced improvement in the injection profile.

[0054] For pathways identified as weak crossflow and matrix seepage channels, a low-concentration chemical displacement solution or surfactant is injected for subsequent displacement. The dynamic simulation diagram of the entire oilfield production cycle during the generation of the optimal prevention and control plan is shown below. Figure 8 As shown.

[0055] The distribution diagram of the change in connection conductivity after implementing the integrated simulation of regulation and drive and the cross-current prevention method in this embodiment is shown in the figure below. Figure 9 As shown, the connecting line at the original high-conductivity channel location becomes lighter in color and thinner in width, quantitatively characterizing the conductivity of this path connection. Significant decay. Figure 9 The results show that the flow field streamlines are reconstructed, and the subsequently injected fluid is forced to turn into the matrix region where the original connecting line is thinner, which verifies the accuracy of the physical mechanism simulation of the method in this embodiment of "blocking large pores and activating low permeability layer".

[0056] Example 2 Based on the same inventive concept, this embodiment discloses an integrated simulation and crossflow prevention system for regulation and drive based on the meshless connected element method, including: The node step module is used to arrange nodes in the computational domain based on reservoir geological parameters using an adaptive node placement algorithm. The meshless model building module is used to construct a meshless connected element model based on the generalized finite difference theory according to the node positions. The full-field pressure potential energy directed graph construction module is used to fit the meshless connected unit model with historical chemical flooding production data to obtain the pressure potential energy distribution of each node and construct the full-field pressure potential energy directed graph. The depth-first search module is used to traverse all potential injection and production well connection flow paths in the entire field pressure potential energy directed graph, starting from the injection well, and to establish an integrated regulation and drive model. The prevention and control plan generation module is used to classify the crossflow situation of the flow path according to the integrated regulation and drive model, and generate the best prevention and control plan based on the classification results.

[0057] Example 3 Based on the same inventive concept, this embodiment discloses a computer-readable storage medium storing a computer program, which is executed by a processor to implement the integrated simulation and cross-current prevention method based on the meshless connection unit method as described above.

[0058] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0059] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0060] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0061] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0062] 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 it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific embodiments of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention. The above content is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims

1. A method for integrated simulation and cross-current prevention based on meshless connected element method, characterized in that, Includes the following steps: Based on reservoir geological parameters, nodes are arranged in the computational domain using an adaptive node placement algorithm. Based on the node positions, a meshless connected element model is constructed using the generalized finite difference theory. By fitting the meshless connected unit model with historical chemical flooding production data, the pressure potential energy distribution of each node is obtained, and a directed graph of pressure potential energy across the entire field is constructed. Starting with the injection well, the flow paths of all potential injection and production well components in the entire field pressure potential energy directional graph are traversed to establish an integrated regulation and drive model. The crossflow situation along the flow path is classified according to the integrated regulation and drive model, and the optimal prevention and control scheme is generated based on the classification results.

2. The integrated simulation and cross-current prevention method based on the meshless connected element method as described in claim 1, characterized in that, The method for constructing the meshless connected unit model is as follows: based on the generalized finite difference theory, using Taylor expansion and weighted least squares method, the physical information in the node control domain is transformed into the geometric properties of the connected unit, and the connection conductivity and connection volume between nodes are calculated.

3. The integrated simulation and cross-current prevention method based on the meshless connected element method as described in claim 2, characterized in that, The connection conductivity The formula for calculating the flow-conducting capacity of the connecting unit is as follows: ； in, The penetration rate of the connecting unit; This refers to the flow rate or proportionality coefficient. For nodes Controlling volume, and All are generalized difference geometric coefficients, where m is the number of rows in the generalized difference coefficient matrix; The connecting volume is based on the principle of material balance, distributing the total reservoir volume to each connecting unit as a spatial carrier for the storage of fluids and chemical agents. Its calculation formula is as follows: ； in, It is the volume of connection. It is the conductivity of the connection; It is the node spacing; N is the total reservoir volume, and N is the number of discrete nodes in the reservoir.

4. The integrated simulation and cross-current prevention method based on the meshless connected element method as described in claim 1, characterized in that, The integrated regulation and drive model establishes a seepage-mass transfer coupling equation on the connection network of the directed graph of the full-field pressure potential energy. The seepage-mass transfer coupling equation includes non-Newtonian fluid characteristics, adsorption mechanism and permeability reduction mechanism. The non-Newtonian fluid characteristics take into account the shear dilution effect of polymer solution and use power-law mode to correct the effective viscosity. The adsorption mechanism uses the Langmuir isotherm adsorption equation to describe the adsorption behavior of chemical agent on rock surface and calculate concentration loss. The permeability reduction mechanism introduces a residual resistance coefficient to describe the hindering effect of chemical adsorption on the flow of the aqueous phase, thereby simulating the water-blocking effect during profile control.

5. The integrated simulation and cross-current prevention method based on the meshless connected element method as described in claim 4, characterized in that, The flow path is a complex, circuitous path containing virtual nodes. The path splitting coefficient of each flow path is calculated based on the directed graph of the overall pressure potential energy. The calculation formula is as follows: ； in, Representative node arrive Traffic; For nodes The total outflow, where n is the nth time step. This refers to the number of connection units with J as the downstream point.

6. The integrated simulation and cross-current prevention method based on the meshless connected element method as described in claim 5, characterized in that, Based on the aforementioned integrated control and drive model, a crossflow factor is calculated. This crossflow factor is then used to classify the crossflow situation along the flow path. The calculation formula is: in, The average conductivity of the path connection; The average connectivity volume of the path; The characteristic ratio of the flow velocity; The average characteristic value for the entire game. and These are the weighting coefficients. .

7. The integrated simulation and cross-current prevention method based on the meshless connected element method as described in claim 6, characterized in that, The crossflow situation in the flow path is divided into four levels based on the crossflow factor: crossflow factor This is a super-grade flow, corresponding to large-scale fissures or karst cave passages; This indicates strong crossflow, corresponding to high-permeability strips; If the flow is intermittent, it corresponds to the general dominant seepage channel. This represents matrix seepage, corresponding to the normal displacement zone.

8. The integrated simulation and cross-current prevention method based on the meshless connected element method as described in claim 7, characterized in that, Based on the grading results, the optimal prevention and control scheme is generated as follows: The super-grade crossflow channel is based on a meshless connecting unit model, identifying and locating the set of connecting units contained in the crossflow path, and predicting the injection effect of high-strength gel or cross-linked polymer through numerical simulation; at the level of integrated model parameter correction, a very small cutoff factor is introduced to affect the connectivity conductivity of the connecting units. Significant reduction is made, bringing it close to zero, thereby forcibly blocking this invalid water circulation loop in the connected topology network; the strong crossflow channel is dynamically adjusted by modifying the connection volume. Parameters are used to characterize the adsorption and retention effects of chemical agents within the connecting units; Increase local seepage resistance to induce a redistribution of streamlines from high-permeability channels to medium- and low-permeability areas.

9. A system for integrated simulation and cross-current prevention based on the meshless connected element method, characterized in that, include: The node step module is used to arrange nodes in the computational domain based on reservoir geological parameters using an adaptive node placement algorithm. The meshless model building module is used to construct a meshless connected element model based on the generalized finite difference theory according to the node positions. The full-field pressure potential energy directed graph construction module is used to fit the meshless connected unit model with historical chemical flooding production data to obtain the pressure potential energy distribution of each node and construct the full-field pressure potential energy directed graph. The depth-first search module is used to traverse all potential injection and production well connection flow paths in the entire field pressure potential energy directed graph, starting from the injection well, and to establish an integrated regulation and drive model. The prevention and control scheme generation module is used to classify the crossflow situation of the flow path according to the integrated regulation and drive model, and generate the best prevention and control scheme based on the classification results.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which is executed by a processor to implement the integrated simulation and cross-current prevention method based on the meshless connection unit method as described in any one of claims 1-8.

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