Micro-nano-scale shale CO2 oil displacement simulation method and system based on CFD

Abstract

The invention discloses a microscale shale pore CO2 oil displacement simulation method based on computational fluid dynamics (CFD). The microscale shale pore CO2 oil displacement simulation method is suitable for low-permeability and low-porosity oil reservoir development. According to the method, a porous medium numerical model is constructed, CO2-crude oil two-phase flow characteristics under different pore structures and stratum conditions are systematically researched, and a pore scale fluid distribution rule and displacement efficiency are mainly analyzed. The CFD numerical simulation technology is adopted, key parameters such as the CO2 diffusion and migration rule in the pores and residual oil saturation distribution are obtained, and the CO2 oil displacement mechanism in the micro-nano-scale pores is revealed. By comparing displacement effects under different environmental parameters (pressure, temperature and the like) and pore configurations (pore size distribution, connectivity and the like), a quantitative relation model of pore structure-oil displacement efficiency is established. The method provides theoretical basis and technical support for optimization of a low-permeability reservoir CO2 oil displacement scheme, and has important guiding significance for improving the unconventional oil and gas recovery ratio and CO2 geological sequestration.

Description

Technical Field

[0001] The present invention belongs to the technical field of carbon capture, utilization and storage, and specifically relates to an analytical method for exploring CO2-displaced micro- and nano-pore oil reservoirs. Background Art

[0002] CO2-EOR (CO2-EOR), an important method for enhancing oil recovery, has been applied in numerous oil fields both domestically and internationally. This technology injects CO2 into the reservoir, leveraging its miscible / immiscible interaction with crude oil to reduce oil viscosity, improve mobility, and induce crude oil expansion, thereby increasing oil recovery efficiency. However, in low-permeability, low-porosity shale reservoirs, CO2-EOR involves complex multiphase flow mechanisms due to the complex pore structure and high resistance to fluid migration. The displacement effect is significantly affected by pore-scale fluid distribution, interfacial effects, and reservoir heterogeneity.

[0003] Currently, research on CO2 flooding relies primarily on macroscopic core experiments and numerical simulation methods. Macroscopic experiments (such as long core flooding) can assess overall recovery rates, but they struggle to reveal the dynamics of fluid distribution and displacement fronts within microscopic pores. Conventional numerical simulation methods are often based on the continuum medium assumption, making it difficult to accurately characterize key physical processes such as capillary forces, adsorption effects, and phase changes in micro- and nanopores. Although molecular dynamics simulations can be used to study fluid behavior at the nanoscale, their limited computational scale makes it difficult to connect with actual reservoir engineering applications. Furthermore, shale reservoirs have diverse pore structures, and different pore size distributions, connectivity, and surface wettability all affect CO2 flooding efficiency. However, there is currently a lack of systematic analytical methods to quantify the impact of these factors.

[0004] Therefore, there is an urgent need to develop a numerical simulation method that can combine microscopic pore characteristics with macroscopic displacement patterns to further understand the oil displacement mechanism of CO2 in low-permeability shale pores, optimize injection parameters (such as pressure and rate), and predict oil displacement efficiency under different reservoir conditions. The microscale simulation method based on computational fluid dynamics (CFD) proposed in this paper aims to fill this technical gap and provide a theoretical basis for optimizing CO2 oil recovery technology in shale reservoirs. Summary of the Invention

[0005] The purpose of this invention is to provide a method for constructing a micro- and nano-scale pore model for low-permeability, low-porosity shale and analyzing its oil and gas flow characteristics. This method accurately characterizes the multiphase flow patterns during CO2 flooding, providing a theoretical basis for CO2-EOR technology in shale reservoirs. By establishing a digital model consistent with real-world pore characteristics and combining it with computational fluid dynamics simulations, this method systematically investigates the mechanism by which pore structure influences CO2 flooding efficiency.

[0006] The method for constructing a micro-nanoscale low-permeability and low-porosity shale pore model of the present invention comprises the following steps:

[0007] (1) Random growth model generation: Based on the quasi-random sequence generation (QSGS) algorithm, a statistically representative two-dimensional pore structure model is constructed by controlling four parameters: length, width, distribution probability, and growth probability;

[0008] (2) Contour vectorization processing: Use R2V software for image recognition and boundary extraction, and obtain accurate .dxf format vector graphics through binarization processing and edge detection algorithm;

[0009] (3) Geometry optimization: Implement Boolean operations and surface smoothing in the CAD environment to control the porosity and permeability characteristics of the model and output a 3D model in .sat format that complies with the ACIS standard.

[0010] A method for analyzing oil and gas flow characteristics based on the above model of the present invention comprises the following steps:

[0011] (1) Meshing: ANSYS Fluent was used for multi-scale meshing. Five layers of boundary layer mesh were set in the pore channel. Adaptive polyhedral mesh was used in the main area, and the mesh was locally refined to 1 / 5-1 / 10 of the characteristic pore diameter.

[0012] (2) Multiphase flow simulation: A VOF model was established to simulate the CO2-crude oil two-phase system. Displacement simulation was performed at 333K and 20MPa, using the PISO algorithm and the second-order upwind scheme.

[0013] (3) Analysis of displacement mechanism: The CO2 displacement efficiency is quantitatively evaluated through parameters such as the oil phase saturation change curve and the two-phase distribution cloud map, revealing the influence of pore structure on the evolution of the displacement front.

[0014] The advantages of the present invention are:

[0015] (1) The QSGS algorithm was first combined with CAD technology to achieve the transformation from a statistical model to an engineering-usable model; (2) The proposed multi-scale grid division strategy takes into account both computational accuracy and efficiency, and can accurately capture the flow characteristics in micron-scale pores; (3) The established VOF-PISO coupling algorithm can effectively simulate the displacement dynamics of supercritical CO2 in complex pores; (4) The analytical method can quantitatively evaluate the oil recovery efficiency under different pore structures, providing theoretical support for the design of CO2-EOR schemes for low-permeability reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described below with reference to the accompanying drawings and examples, in which:

[0017] Figure 1It is the bulk phase cloud diagram of the CO2 displacement process;

[0018] Figure 2 is the change of residual oil during the CO2 displacement process. DETAILED DESCRIPTION

[0019] The present invention will be further described below with reference to embodiments. The examples described below are only a part of the present invention, and the present invention is not limited to these examples.

[0020] Example 1: Analysis of CO2 storage capacity during oil recovery in shale fractures with varying permeabilities

[0021] By constructing a shale fracture gradient pore model with permeabilities of 20mD, 25mD, and 30mD, the CO2 flooding process was simulated at a constant temperature of 333K and a constant pressure of 20MPa. The VOF multiphase flow model was combined with the PR state equation. Through the volume phase cloud analysis, it was found that as the permeability increased from 20mD to 30mD, the oil recovery efficiency increased significantly, such as Figure 2 , where the 20mD model shows obvious fingering phenomenon, and the 25mD model shows the best sweep efficiency, as shown in Figure 1 ; This result provides an important basis for optimizing CO2 flooding parameters in fractured shale reservoirs.

[0022] Example 2: Analysis of CO2 flooding capacity in different reservoir environments

[0023] The method of the present invention can be used to analyze the oil displacement capacity of carbon dioxide in various reservoir environments such as different temperatures and pressures. The steps of Example 1 can be followed for different temperatures and pressures. At the same time, the statistical oil displacement rate can intuitively evaluate the impact of different formation conditions on oil displacement capacity, such as Figure 2 To visually observe the distribution of CO2 stored in the pore, a volume phase cloud diagram can be drawn, such as Figure 1 .

[0024] The embodiments described above are merely examples of the present invention and do not constitute any form of limitation. Anyone skilled in the art can successfully implement the present invention according to the above procedures. However, any modifications and variations made by a skilled person using the above technical content without departing from the scope of the technical solution of the present invention are equivalent embodiments of the present invention. Furthermore, all equivalent changes and variations made to the above embodiments based on the implementation techniques of the present invention fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for constructing a low-permeability and low-porosity shale pore model at micro-nano scale, characterized in that The quasi-random sequence generation (QSGS) algorithm is combined with computer-aided design (CAD) technology to establish a shale pore structure model for oil and gas flow characteristics analysis. The method is characterized by the following steps: (1) Random growth model generation: Based on the random growth process of the model controlled by four parameters (length, width, distribution probability, and growth probability), a two-dimensional distribution model with specific morphological characteristics is generated through probability constraints and output in bitmap format. (2) Contour vectorization processing: R2V software is used to identify the boundaries of the generated model image, and the precise contour is extracted through binarization processing and edge detection algorithm, and finally converted into an editable .dxf vector graphics file to provide structured data for subsequent geometric analysis or numerical simulation. (3) Geometry Optimization: Geometry optimization is performed in the CAD environment, including topological operations such as Boolean operations (merge / intersect) and surface smoothing to reduce model porosity and control permeability characteristics. .sat format files are generated that comply with the ACIS geometry kernel standard.

2. A method for analyzing oil and gas distribution based on a constructed model according to claim 1, characterized in that The following steps are included: (1) Meshing: This study used ANSYS Fluent to mesh the optimized model. First, the geometric model in .sat format was imported, and the geometry repair function was used to address any minor defects. A hybrid meshing strategy was adopted, with five layers of boundary layer meshes set in key areas such as pore channels. The height of the first layer was determined based on the flow characteristics. A polyhedral mesh was used in the main area, with local encryption performed in areas with complex pore structures. The mesh size was controlled to be 1 / 5-1 / 10 of the characteristic pore diameter. (2) Computational fluid dynamics simulation: After modeling and meshing, the VOF model was used to describe the CO2-crude oil two-phase system. The CO2 and oil phases were set so that the pores were filled with oil. The simulation was performed at 333K and 20 MPa with a displacement pressure of 20 MPa. The model was locally initialized and CO2 was injected into the pores to simulate the CO2 displacement process. The PISO algorithm was combined with a second-order upwind scheme for numerical solution, and an adaptive time step (initial 1×10-6 s) and a convergence criterion of 1×10-4 were set. (3) Analysis of displacement capacity: By statistically analyzing the volume fraction change curve of the oil phase during storage; drawing the oil and gas two-phase phase cloud map, studying the influence of pore structure on the two-phase aggregation process; monitoring the change of pore CO2 volume fraction in real time during the simulation process, tracking the dynamic evolution process of the displacement front, and quantitatively analyzing the change of displacement efficiency over time, the seepage mechanism and oil displacement characteristics of supercritical CO2 in porous media are systematically revealed, providing theoretical support and optimization basis for CO2 enhanced oil recovery technology.

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