Fracturing parameter determination method and device, electronic equipment and machine readable storage medium

Abstract

The invention discloses a fracturing parameter determination method and device, electronic equipment and a machine readable storage medium. The fracturing parameter determination method comprises the steps that an initial rock core scale numerical simulation model is established according to geological parameters; fitting an initial component model in the initial rock core scale numerical simulation model to obtain a rock core scale numerical simulation model; a rock core scale numerical simulation model is used for analyzing the synergistic effect after carbon dioxide enters the reservoir in the target area and the influence of the first initial fracturing parameter on the synergistic effect, and a first analysis result is obtained; constructing an oil field scale numerical simulation model according to the geological parameters, the component model and an original oil reservoir numerical simulator; and according to the first analysis result and the target index, performing fracturing parameter optimization by using an oil field scale numerical simulation model to obtain fracturing parameters. Therefore, the determination efficiency and accuracy of the fracturing parameters are improved, and the fracturing parameters can better meet the efficiency requirement of tight oil reservoir exploitation.

Description

Technical Field

[0001] This application relates to the field of oil and gas field development technology, and specifically to a method, apparatus, electronic device and machine-readable storage medium for determining fracturing parameters. Background Technology

[0002] Tight oil reservoirs are characterized by very small reservoir voids and low porosity and permeability of the reservoir rocks, which makes them difficult and inefficient to develop. Carbon dioxide pre-storage fracturing is a commonly used method to improve the development efficiency of tight oil reservoirs.

[0003] Carbon dioxide pre-storage fracturing primarily uses carbon dioxide as a fracturing fluid injected into the oil reservoir. By applying high pressure, it induces fractures in the rock, thereby improving the permeability of the tight oil reservoir, promoting its flow, and increasing its extraction efficiency. However, in existing technologies using carbon dioxide pre-storage fracturing for tight oil reservoir extraction, it is difficult to design optimal fracturing parameters for implementation in areas with complex geological environments, leading to poor operational results and thus affecting the extraction efficiency of tight oil reservoirs.

[0004] It is evident that existing tight oil reservoir development suffers from technical problems, such as fracturing parameters that are insufficient to meet the demands of tight oil reservoir development efficiency. Summary of the Invention

[0005] The purpose of this application is to provide a method, apparatus, electronic device, and machine-readable storage medium for determining fracturing parameters, in order to solve the technical problem in the prior art that fracturing parameters are difficult to meet the extraction efficiency of tight oil reservoirs.

[0006] To achieve the above objectives, the first aspect of this application provides a method for determining fracturing parameters, comprising:

[0007] Geological parameters, initial fracturing parameters, and target indicators are determined based on the geological conditions of the target area. Among them, the target indicators include at least one of environmental indicators, financial indicators, and production indicators.

[0008] An initial core-scale numerical simulation model is established based on geological parameters. The initial core-scale numerical simulation model includes an initial component model and a primary reservoir numerical simulator.

[0009] The initial component model in the initial core-scale numerical simulation model is fitted to obtain a well-fitted component model, which is then used to update the initial core-scale numerical simulation model to obtain the core-scale numerical simulation model.

[0010] The synergistic effect of carbon dioxide entering the reservoir in the target area and the influence of the first initial fracturing parameters on the synergistic effect were analyzed using a core-scale numerical simulation model, and the first analysis results were obtained.

[0011] An oilfield-scale numerical simulation model was constructed based on geological parameters, component models, and a primitive reservoir numerical simulator.

[0012] Based on the first analysis results and target indicators, the fracturing parameters were optimized using an oilfield-scale numerical simulation model to obtain the fracturing parameters.

[0013] In this embodiment of the application, the initial component model in the initial core-scale numerical simulation model is fitted to obtain a well-fitted component model, which is then used to update the initial core-scale numerical simulation model, resulting in a core-scale numerical simulation model, including:

[0014] The experimental value of the diffusion coefficient was obtained based on the results of the carbon dioxide diffusion experiment.

[0015] According to FICK's diffusion law, the experimental value of the diffusion coefficient is fitted to the initial composition model in the initial core-scale numerical simulation model to obtain a well-fitted composition model, which is then used to update the initial core-scale numerical simulation model, thus obtaining the core-scale numerical simulation model.

[0016] In this embodiment of the application, based on the first analysis results and target indicators, fracturing parameters are optimized using an oilfield-scale numerical simulation model to obtain fracturing parameters, including:

[0017] Geological parameters were analyzed using the original reservoir simulator to obtain the second analysis results;

[0018] Use geological parameters and the first initial fracturing parameters as input parameters;

[0019] The input parameters were analyzed using the original reservoir simulator to obtain the third analysis result;

[0020] The second initial fracturing parameters are determined based on the results of the first, second, and third analyses.

[0021] Based on the target indicators and the second initial fracturing parameters, the fracturing parameters are optimized using an oilfield-scale numerical simulation model to obtain the fracturing parameters.

[0022] In this embodiment of the application, geological parameters are analyzed using a primary reservoir simulator to obtain a second analysis result, including:

[0023] Geological parameters are input into the original reservoir numerical simulator for analysis, and images corresponding to the carbon dioxide fluid phase distribution field, pressure distribution field and crude oil viscosity distribution field in the target area are obtained.

[0024] The second analysis result is determined based on the images corresponding to the carbon dioxide fluid phase distribution field, pressure distribution field, and crude oil viscosity distribution field within the target area.

[0025] In this embodiment of the application, the input parameters are analyzed using a primitive reservoir simulator to obtain a third analysis result, including:

[0026] The input parameters were input into the original reservoir numerical simulator for analysis to obtain the carbon dioxide energy storage fracturing production enhancement law in the target area.

[0027] The interaction between carbon dioxide and tight oil in the target area is analyzed based on the relationship between the input parameters and the carbon dioxide energy storage fracturing production enhancement law in the target area, resulting in the third analysis result.

[0028] In this embodiment of the application, based on the target index and the second initial fracturing parameters, the fracturing parameters are optimized using an oilfield-scale numerical simulation model to obtain the fracturing parameters, including:

[0029] The second initial fracturing parameters and the target index are input into the oilfield-scale numerical simulation model to determine the relationship function between the second initial fracturing parameters and the target index.

[0030] The fracturing parameters are determined based on the relationship function between the second initial fracturing parameters and the target index.

[0031] In this application embodiment, the synergistic effect of carbon dioxide entering the reservoir within the target area includes:

[0032] The diffusion pattern of carbon dioxide from fractures to matrix at the core scale within the target area; the energy-enhancing effect of carbon dioxide entering the matrix from fractures at the core scale within the target area; the viscosity-reducing effect of carbon dioxide entering the matrix from fractures at the core scale within the target area; and the miscibility of carbon dioxide entering the matrix from fractures at the core scale within the target area with crude oil in the reservoir.

[0033] A second aspect of this application provides a fracturing parameter determination device, characterized in that it comprises:

[0034] The memory is configured to store instructions; and

[0035] The processor is configured to retrieve instructions from memory and, when executing the instructions, to implement the fracturing parameter determination method according to any one of the first aspects.

[0036] A third aspect of this application provides an electronic device, characterized in that it comprises:

[0037] The fracturing parameter determination device according to the second aspect.

[0038] A fourth aspect of this application provides a machine-readable storage medium, characterized in that the machine-readable storage medium stores instructions for causing a machine to perform the fracturing parameter determination method according to any one of the first aspects.

[0039] By employing the above technical solutions, an oilfield-scale numerical simulation model is established using a component model fitted in a core-scale numerical simulation model. This avoids directly fitting the component model in a large-scale oilfield-scale numerical simulation model, thus improving the fitting efficiency of the component model. Furthermore, based on the analysis results of the core-scale numerical simulation model, the oilfield-scale numerical simulation model is used to optimize fracturing parameters, which improves the efficiency and accuracy of fracturing parameter determination, enabling the fracturing parameters to better meet the efficiency requirements of tight oil reservoir development.

[0040] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0041] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings:

[0042] Figure 1 The illustration shows a flowchart of a fracturing parameter determination method according to an embodiment of this application;

[0043] Figure 2 The schematic diagram illustrates the structure of a fracturing parameter determination device according to an embodiment of this application. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0045] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0046] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0047] Figure 1 The illustration schematically shows a flowchart of a fracturing parameter determination method according to an embodiment of this application. Figure 1 As shown in the figure, this application provides a method for determining fracturing parameters, which may include the following steps.

[0048] Step 110: Determine the geological parameters, initial fracturing parameters and target indicators based on the geological conditions of the target area. The target indicators include at least one of the following: environmental indicators, financial indicators and production indicators.

[0049] It is understood that the fracturing parameters to be determined in this application embodiment are for use in the carbon dioxide pre-storage fracturing method to exploit tight oil reservoirs in the target area. Tight oil reservoirs refer to reservoirs with extremely low permeability and porosity, typically located in tight rocks such as shale, sandstone, or carbonate rocks. Due to the low permeability of these rocks, oil in tight oil reservoirs cannot flow naturally into the wellbore, thus requiring special extraction techniques to improve oil and gas recovery. Carbon dioxide pre-storage fracturing is a commonly used method to improve the extraction efficiency of tight oil reservoirs. By injecting carbon dioxide as a fracturing fluid into the reservoir and applying high pressure, fractures are created in the rock, thereby improving the permeability of the tight oil reservoir and promoting its flow. The target area refers to the area where tight oil reservoir extraction will take place, and can be set according to actual conditions; this application embodiment does not limit this.

[0050] Specifically, geological parameters, initial fracturing parameters, and target indicators can be determined based on the geological conditions of the target area. Target indicators are crucial for evaluating fracturing effectiveness and the profitability of tight oil reservoir development, and include at least one of environmental, financial, and production indicators. Environmental indicators aim to reduce environmental impact, such as reducing water consumption, lowering the risk of surface and groundwater pollution, and reducing greenhouse gas emissions, including CO2 backflow rate and CO2 recovery rate. Financial indicators aim to improve economic efficiency and reduce development costs, including net present value. Production indicators aim to maximize oil and gas production, including cumulative oil production, cumulative water production, cumulative gas production, daily oil production, daily gas production, and daily water production. Geological parameters include reservoir geological parameters and reservoir fluid parameters. Reservoir geological parameters include reservoir thickness and reservoir permeability, while reservoir fluid parameters include crude oil viscosity and flow-water interfacial tension. The initial fracturing parameters are ranges of values ​​determined based on the geological conditions of the target area. These initial fracturing parameters can include multiple categories, each with a range of values, such as well shut-in time, differential pressure, CO2 injection method, CO2 usage, CO2 injection rate, number of fracturing stages, number of fracturing clusters, stage spacing, cluster spacing, reservoir permeability, and porosity. Determining the geological parameters, initial fracturing parameters, and target indicators lays the data foundation for subsequent optimization of fracturing parameters.

[0051] Step 120: Establish an initial core-scale numerical simulation model based on geological parameters. The initial core-scale numerical simulation model includes an initial component model and a primary reservoir numerical simulator.

[0052] Understandably, the initial core-scale numerical simulation model is a model used to study and predict fluid flow, mass transfer, and rock-fluid interactions in reservoirs. It typically combines numerical calculation methods to perform detailed simulations and analyses of actual formations, reflecting the influence of rock pore structure and fluid properties on oil and gas flow, providing crucial foundational data for oilfield development and fracturing design. In this embodiment, the initial oilfield-scale numerical simulation model can be a radial one-dimensional model, including an initial component model and a primary reservoir numerical simulator. The initial component model is a small model within the core-scale numerical simulation model, designed to describe in detail the diffusion and interaction behavior of multi-component fluids such as carbon dioxide and crude oil in the core. The primary reservoir numerical simulator is also an embedded model within the initial core-scale numerical simulation model, used to simulate and predict fluid flow and fracturing processes throughout the reservoir. Constructing an initial core-scale numerical simulation model improves the efficiency of subsequent fracturing parameter optimization using the oilfield-scale numerical simulation model.

[0053] Step 130: Fit the initial component model in the initial core-scale numerical simulation model to obtain a well-fitted component model, and update the initial core-scale numerical simulation model to obtain the core-scale numerical simulation model.

[0054] It is understandable that the parameter values ​​in the initial component model are based on experimentally measured values. However, in actual numerical simulations using a core-scale numerical simulation model, the parameters in the component model are values ​​under ideal conditions, which are difficult to achieve with experimental values ​​measured in the laboratory. Therefore, the parameter values ​​in the initial component model cannot meet the requirements of numerical simulation. It is necessary to fit the initial component model in the initial core-scale numerical simulation model to make the parameters of the component model reach ideal values, thereby improving the accuracy of numerical simulations using the core-scale numerical model. This will facilitate the selection of fracturing parameters in subsequent embodiments based on the analysis results of the core-scale numerical simulation model.

[0055] In this embodiment of the application, step 130 includes:

[0056] The experimental value of the diffusion coefficient was obtained based on the results of the carbon dioxide diffusion experiment.

[0057] According to FICK's diffusion law, the experimental value of the diffusion coefficient is fitted to the initial composition model in the initial core-scale numerical simulation model to obtain a well-fitted composition model, which is then used to update the initial core-scale numerical simulation model, thus obtaining the core-scale numerical simulation model.

[0058] It is understandable that FICK's diffusion law describes the relationship between mass transfer flux and concentration gradient during molecular diffusion when mass transfer occurs without relying on macroscopic mixing. Core scale refers to the spatial scale of studying core samples extracted from underground. Cores are typically cylindrical rock samples drilled from wellbores, usually a few meters in length and a few centimeters in diameter. Oilfield scale refers to the spatial scale of the entire oilfield or reservoir, typically covering an area of ​​several to hundreds of square kilometers. Since the oilfield scale is much larger than the core scale, directly fitting the initial component model at the oilfield scale is inefficient and inaccurate. Therefore, it is advisable to first fit the initial component model in the initial core-scale numerical simulation model, and then directly apply the fitted component model to the oilfield-scale numerical simulation model. This improves the efficiency and accuracy of using the oilfield-scale numerical simulation model for fracturing parameter optimization.

[0059] Specifically, a carbon dioxide diffusion experiment is first conducted to obtain the experimental diffusion coefficient. Based on the results, the experimental diffusion coefficient is then fitted to the initial component model using FICK's law to obtain a molecular diffusion coefficient that better satisfies the ideal conditions. This molecular diffusion coefficient is then used to replace the initial parameters in the initial component model, resulting in a well-fitted component model. This updated core-scale numerical simulation model better simulates carbon dioxide diffusion under ideal conditions, which is beneficial for optimizing fracturing parameters in subsequent embodiments based on the analysis results of the core-scale numerical simulation model.

[0060] Step 140: Analyze the synergistic effect of carbon dioxide entering the reservoir in the target area and the influence of the first initial fracturing parameters on the synergistic effect using a core-scale numerical simulation model to obtain the first analysis results;

[0061] Specifically, after fitting the component model in the initial core-scale numerical simulation model, core-scale numerical simulation can be performed. This involves using the core-scale numerical simulation model to analyze the synergistic effect of carbon dioxide entering the reservoir within the target area and the distances of the carbon dioxide diffusion front, crude oil viscosity reduction front, carbon dioxide diffusion limit, and crude oil viscosity reduction limit under different fracturing parameters. Furthermore, the influence of the initial fracturing parameters on the synergistic effect is analyzed to obtain the first analytical results. It is important to note that in actual engineering projects, the exploitation of tight oil reservoirs often involves large-scale operations. Due to the small scale of the core, directly using the analysis results of the core-scale numerical simulation model to optimize fracturing parameters may not meet the actual needs, leading to poor operational results and affecting the exploitation efficiency of tight oil reservoirs. Therefore, it is necessary to first conduct a preliminary analysis in the core-scale numerical simulation model, and then use the oilfield-scale numerical simulation model to optimize the fracturing parameters based on the results of the preliminary analysis.

[0062] In this application embodiment, the synergistic effect of carbon dioxide entering the reservoir within the target area includes:

[0063] The diffusion pattern of carbon dioxide from fractures to matrix at the core scale within the target area; the energy-enhancing effect of carbon dioxide entering the matrix from fractures at the core scale within the target area; the viscosity-reducing effect of carbon dioxide entering the matrix from fractures at the core scale within the target area; and the miscibility of carbon dioxide entering the matrix from fractures at the core scale within the target area with crude oil in the reservoir.

[0064] It is understandable that the synergistic effects of carbon dioxide entering the reservoir within the target area include the diffusion pattern of carbon dioxide from fractures to the matrix at the core scale, the energy-enhancing effect of carbon dioxide entering the matrix from fractures at the core scale, the viscosity-reducing effect of carbon dioxide entering the matrix from fractures at the core scale, and the miscibility effect of carbon dioxide entering the matrix from fractures at the core scale with crude oil in the reservoir. Analyzing these synergistic effects can provide a scientific basis for the subsequent optimization of fracturing parameters using oilfield-scale numerical simulation models.

[0065] Step 150: Construct an oilfield-scale numerical simulation model based on geological parameters, composition models, and the original reservoir numerical simulator;

[0066] Specifically, an oilfield-scale numerical simulation model is constructed based on the component model fitted in the core-scale numerical simulation model, the acquired geological parameters, and the original reservoir numerical simulator. The oilfield numerical simulation model is a computational tool used to simulate and predict fluid flow behavior, oil and gas recovery rates, and production performance in oilfields. It can be a horizontal well single-stage fracturing model, using fine meshes to represent fractures and employing logarithmic refinement around the fracture mesh to better adapt to the complexity and inhomogeneity of tight oil reservoirs. Alternatively, the oilfield-scale numerical simulation model can be an optimized model of supercritical carbon dioxide fracturing flowback regime, established by combining the interaction mechanism between carbon dioxide and tight reservoirs / oil, considering the porosity and permeability variations of tight reservoirs and the interaction between carbon dioxide and tight oil. It should be noted that the oilfield-scale numerical simulation model can be set according to actual conditions, and this application does not limit this.

[0067] By using the component model fitted in the core-scale numerical simulation model to establish the oilfield-scale numerical simulation model, the fitting of the component model in the large-scale oilfield-scale numerical simulation model is avoided. This improves the fitting efficiency of the component model, thereby improving the efficiency and accuracy of fracturing parameter selection, and enabling the selected fracturing parameters to better meet the efficiency requirements of tight oil reservoir development.

[0068] Step 160: Based on the first analysis results and target indicators, the fracturing parameters are optimized using an oilfield-scale numerical simulation model to obtain the fracturing parameters.

[0069] Specifically, based on the first analysis results obtained using the core-scale numerical simulation model and the target indicators obtained in step 110, the fracturing parameters are optimized using the oilfield-scale numerical simulation model and the included original reservoir numerical simulator, selecting the optimal values ​​as the fracturing parameters. It should be noted that multiple fracturing parameters can be optimized simultaneously, with an optimal value selected for each parameter; however, only one target value can be selected at a time. By optimizing fracturing parameters using the oilfield-scale numerical simulation model based on the first analysis results and target indicators, the obtained fracturing parameters better reflect the actual production conditions of tight oil reservoirs, thereby better meeting the efficiency requirements of tight oil reservoir production.

[0070] In this embodiment of the application, step 160 includes:

[0071] Geological parameters were analyzed using the original reservoir simulator to obtain the second analysis results;

[0072] Use geological parameters and the first initial fracturing parameters as input parameters;

[0073] The input parameters were analyzed using the original reservoir simulator to obtain the third analysis result;

[0074] The second initial fracturing parameters are determined based on the results of the first, second, and third analyses.

[0075] Based on the target indicators and the second initial fracturing parameters, the fracturing parameters are optimized using an oilfield-scale numerical simulation model to obtain the fracturing parameters.

[0076] Specifically, geological parameters are input into the original reservoir numerical simulator for analysis, yielding a second analysis result. These geological parameters, along with the first initial fracturing parameters, are then used as input parameters to the original reservoir simulator. The simulator is used to analyze these input parameters, resulting in a third analysis result. Based on these three analysis results, a superior second initial fracturing parameter is selected from the first initial fracturing parameters. It's important to note that both the second and first initial fracturing parameters include multiple categories, each encompassing multiple values ​​within a specific range. Since the second initial fracturing parameters are selected from the first initial fracturing parameters, their range is smaller than that of the first initial fracturing parameters. After narrowing down the range of fracturing parameters, the optimal fracturing parameters are then obtained using an oilfield-scale numerical simulation model, based on the target indicators and the second initial fracturing parameters. By optimizing the first initial fracturing parameters based on the second and third analysis results obtained from the original reservoir numerical simulator, the range of the first initial fracturing parameters is narrowed to obtain the second initial fracturing parameters. Then, the second initial fracturing parameters are optimized using the oilfield-scale numerical simulation model to obtain the optimal fracturing parameters. This can improve the efficiency and accuracy of fracturing parameter optimization, so that the optimized fracturing parameters can meet the efficiency requirements of tight oil reservoir development.

[0077] In this embodiment of the application, geological parameters are analyzed using a primary reservoir simulator to obtain a second analysis result, including:

[0078] Geological parameters are input into the original reservoir numerical simulator for analysis, and images corresponding to the carbon dioxide fluid phase distribution field, pressure distribution field and crude oil viscosity distribution field in the target area are obtained.

[0079] The second analysis result is determined based on the images corresponding to the carbon dioxide fluid phase distribution field, pressure distribution field, and crude oil viscosity distribution field within the target area.

[0080] Specifically, geological parameters are input into the original reservoir numerical simulator for analysis, obtaining images corresponding to the carbon dioxide fluid phase distribution field, pressure distribution field, and crude oil viscosity distribution field within the target area. The second analysis result is determined based on these images. The carbon dioxide fluid phase distribution field refers to the form and concentration distribution of carbon dioxide at different locations within the reservoir, describing the physical state and spatial distribution of carbon dioxide within the reservoir. The pressure distribution field refers to the pressure distribution at different locations within the reservoir, describing the fluid pressure at each point. The crude oil viscosity distribution field refers to the distribution of crude oil viscosity at different locations within the reservoir, describing the changes in flow resistance of crude oil within the reservoir. By determining the second analysis result based on these images, the synergistic effect of carbon dioxide injection can be more comprehensively evaluated, thereby improving the exploitation efficiency of tight oil reservoirs.

[0081] In this embodiment of the application, the input parameters are analyzed using a primitive reservoir simulator to obtain a third analysis result, including:

[0082] The input parameters were input into the original reservoir numerical simulator for analysis to obtain the carbon dioxide energy storage fracturing production enhancement law in the target area.

[0083] The interaction between carbon dioxide and tight oil in the target area is analyzed based on the relationship between the input parameters and the carbon dioxide energy storage fracturing production enhancement law in the target area, resulting in the third analysis result.

[0084] Specifically, the input parameters are input into the original reservoir numerical simulator for analysis. The values ​​of the input parameters are then modified, and the modified values ​​are input into the original reservoir numerical simulator for multiple analyses. This yields the CO2 storage fracturing production enhancement law in the target area. The CO2 storage fracturing production enhancement law refers to the influence of CO2 injection and storage fracturing on reservoir production enhancement, as derived through numerical simulation and analysis. After obtaining the CO2 storage fracturing production enhancement law in the target area, the relationship between the input parameters and the output values ​​of the original reservoir numerical simulator is analyzed. This analysis examines the relationship between the input parameters and the CO2 storage fracturing production enhancement law in the target area. Based on this relationship, the interaction between CO2 and tight oil in the target area is analyzed, resulting in a third analytical result. Analyzing the relationship between the input parameters and output values ​​of the numerical simulator helps to understand the impact of different input parameters on the CO2 storage fracturing production enhancement effect, thereby improving the optimization efficiency of fracturing parameters.

[0085] In this embodiment of the application, based on the target index and the second initial fracturing parameters, the fracturing parameters are optimized using an oilfield-scale numerical simulation model to obtain the fracturing parameters, including:

[0086] The second initial fracturing parameters and the target index are input into the oilfield-scale numerical simulation model to determine the relationship function between the second initial fracturing parameters and the target index.

[0087] The fracturing parameters are determined based on the relationship function between the second initial fracturing parameters and the target index.

[0088] Specifically, the second initial fracturing parameters and target indicators are input into an oilfield-scale numerical simulation model. The relationship function between the second initial fracturing parameters and the target indicators is determined using a permeability factor curve. This relationship function can be determined using either a one-factor analysis method or a response surface methodology. The permeability factor curve describes the relationship between reservoir permeability changes and fracturing parameters, reflecting changes in reservoir permeability under different operating conditions. The one-factor analysis method involves changing only one factor at a time while keeping other factors constant, analyzing the impact of that factor's change on the results. The response surface methodology involves constructing a mathematical model to describe the influence of multiple factors on the response variable and finding the optimal value. After obtaining the relationship function between the second initial fracturing parameters and the target indicators, the function can be analyzed based on actual conditions, and the optimal value among the second fracturing parameters can be selected as the fracturing parameters. By using a large-scale oilfield-scale numerical simulation model to optimize fracturing parameters, the obtained fracturing parameters can be better adapted to actual large-scale reservoir development. Furthermore, based on the relationship function between the second initial fracturing parameters and the target index, the most suitable fracturing parameters for the target index can be determined to maximize the recovery rate and production of tight oil reservoirs.

[0089] The fracturing parameter determination method provided in this application establishes an oilfield-scale numerical simulation model by utilizing a component model fitted in a core-scale numerical simulation model. This avoids directly fitting the component model in a large-scale oilfield-scale numerical simulation model, thus improving the fitting efficiency of the component model. Furthermore, based on the analysis results of the core-scale numerical simulation model, the fracturing parameters are optimized using the oilfield-scale numerical simulation model, which improves the efficiency and accuracy of fracturing parameter determination, enabling the fracturing parameters to better meet the efficiency requirements of tight oil reservoir development.

[0090] Figure 2 A schematic block diagram of a controller according to an embodiment of this application is shown. Figure 2 As shown in the figure, this application provides a controller that may include:

[0091] Memory 210 is configured to store instructions; and

[0092] Processor 220 is configured to retrieve instructions from memory 210 and, when executing the instructions, to implement the fracturing parameter determination method provided in the method embodiment.

[0093] Specifically, in this embodiment of the application, the processor 220 can be configured to:

[0094] Geological parameters, initial fracturing parameters, and target indicators are determined based on the geological conditions of the target area. Among them, the target indicators include at least one of environmental indicators, financial indicators, and production indicators.

[0095] An initial core-scale numerical simulation model is established based on geological parameters. The initial core-scale numerical simulation model includes an initial component model and a primary reservoir numerical simulator.

[0096] The initial component model in the initial core-scale numerical simulation model is fitted to obtain a well-fitted component model, which is then used to update the initial core-scale numerical simulation model to obtain the core-scale numerical simulation model.

[0097] The synergistic effect of carbon dioxide entering the reservoir in the target area and the influence of the first initial fracturing parameters on the synergistic effect were analyzed using a core-scale numerical simulation model, and the first analysis results were obtained.

[0098] An oilfield-scale numerical simulation model was constructed based on geological parameters, component models, and a primitive reservoir numerical simulator.

[0099] Based on the first analysis results and target indicators, the fracturing parameters were optimized using an oilfield-scale numerical simulation model to obtain the fracturing parameters.

[0100] It is understood that the fracturing parameter determination device provided in this application embodiment can realize each process of the data fracturing parameter determination method in the method embodiment and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0101] This application also provides an electronic device, which may include:

[0102] The fracturing parameter determination device provided in the above embodiments.

[0103] It is understood that the electronic device provided in the embodiments of this application includes a fracturing parameter determination device and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0104] This application also provides a machine-readable storage medium storing instructions that cause a machine to execute the fracturing parameter determination method provided in the method embodiment, achieving the same technical effect. To avoid repetition, these instructions will not be elaborated here.

[0105] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application 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.

[0106] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. 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... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0107] 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.

[0108] 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.

[0109] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0110] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0111] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0112] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0113] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for determining fracturing parameters, characterized in that, The method includes: Geological parameters, initial fracturing parameters, and target indicators are determined based on the geological conditions of the target area. The target indicators include at least one of environmental indicators, financial indicators, and production indicators. An initial core-scale numerical simulation model is established based on the geological parameters, wherein the initial core-scale numerical simulation model includes an initial component model and an original reservoir numerical simulator; The initial component model in the initial core-scale numerical simulation model is fitted to obtain a well-fitted component model, which is then used to update the initial core-scale numerical simulation model to obtain the core-scale numerical simulation model. The core-scale numerical simulation model was used to analyze the synergistic effect of carbon dioxide entering the reservoir in the target area and the influence of the first initial fracturing parameters on the synergistic effect, and the first analysis results were obtained. Based on the geological parameters, the component model, and the original reservoir numerical simulator, an oilfield-scale numerical simulation model is constructed. Based on the first analysis results and the target indicators, the fracturing parameters are optimized using the oilfield-scale numerical simulation model to obtain the fracturing parameters.

2. The method for determining fracturing parameters according to claim 1, characterized in that, The process of fitting the initial component model in the initial core-scale numerical simulation model to obtain a well-fitted component model, and then updating the initial core-scale numerical simulation model to obtain the core-scale numerical simulation model, includes: The experimental value of the diffusion coefficient was obtained based on the results of the carbon dioxide diffusion experiment. According to FICK's diffusion law, the experimental value of the diffusion coefficient is fitted to the initial composition model in the initial core-scale numerical simulation model to obtain a well-fitted composition model, which is then used to update the initial core-scale numerical simulation model, thus obtaining the core-scale numerical simulation model.

3. The method for determining fracturing parameters according to claim 1, characterized in that, The step of optimizing fracturing parameters using the oilfield-scale numerical simulation model based on the first analysis results and the target indicators to obtain fracturing parameters includes: The geological parameters were analyzed using the original reservoir simulator to obtain a second analysis result; The geological parameters and the first initial fracturing parameters are used as input parameters; The input parameters are analyzed using the original reservoir simulator to obtain a third analysis result; The second initial fracturing parameters are determined based on the first analysis result, the second analysis result, and the third analysis result. Based on the target index and the second initial fracturing parameters, the fracturing parameters are optimized using the oilfield-scale numerical simulation model to obtain the fracturing parameters.

4. The method for determining fracturing parameters according to claim 3, characterized in that, The analysis of the geological parameters using the original reservoir simulator to obtain the second analysis result includes: The geological parameters are input into the original reservoir numerical simulator for analysis to obtain images corresponding to the carbon dioxide fluid phase distribution field, pressure distribution field and crude oil viscosity distribution field in the target area; The second analysis result is determined based on the images corresponding to the carbon dioxide fluid phase distribution field, the pressure distribution field, and the crude oil viscosity distribution field within the target area.

5. The method for determining fracturing parameters according to claim 3, characterized in that, The analysis of the input parameters using the original reservoir simulator to obtain a third analysis result includes: The input parameters are input into the original reservoir numerical simulator for analysis to obtain the carbon dioxide energy storage fracturing production enhancement law in the target area; The interaction between carbon dioxide and tight oil in the target area is analyzed based on the relationship between the input parameters and the carbon dioxide energy storage fracturing production enhancement law in the target area, and the third analysis result is obtained.

6. The method for determining fracturing parameters according to claim 3, characterized in that, The step of optimizing fracturing parameters using the oilfield-scale numerical simulation model based on the target index and the second initial fracturing parameters to obtain the fracturing parameters includes: The second initial fracturing parameters and the target index are input into the oilfield-scale numerical simulation model to determine the relationship function between the second initial fracturing parameters and the target index. The fracturing parameters are determined based on the relationship function between the second initial fracturing parameters and the target index.

7. The method for determining fracturing parameters according to claim 1, characterized in that, The synergistic effects of carbon dioxide entering the reservoir within the target area include: The diffusion pattern of carbon dioxide from fractures to the matrix at the core scale within the target area; the energy-enhancing effect of carbon dioxide entering the matrix from fractures at the core scale within the target area; the viscosity-reducing effect of carbon dioxide entering the matrix from fractures at the core scale within the target area; and the miscibility of carbon dioxide entering the matrix from fractures at the core scale within the target area with crude oil in the reservoir.

8. A device for determining fracturing parameters, characterized in that, include: The memory is configured to store instructions; as well as The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the fracturing parameter determination method according to any one of claims 1 to 7.

9. An electronic device, characterized in that, include: The fracturing parameter determination device according to claim 8.

10. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to perform the fracturing parameter determination method according to any one of claims 1 to 7.

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