A macro-microscopic analysis method and system for displacement development based on a sandpack model

Abstract

The application discloses a macro-microscopic analysis method and system for displacement development based on a sand filling model, and the analysis method comprises the following steps: assembling a simulated reservoir system based on a visual two-dimensional sand filling model; obtaining a displacement image; identifying macroscopic oil saturation; and establishing a microcosmic residual oil regularity evaluation method. The macro-microscopic oil-water distribution image in the displacement process under the reservoir condition can be determined more objectively and comprehensively to measure the development effect of the reservoir, the influence of different development modes under the oilfield condition on the distribution and type of residual oil is optimized, and the injection fluid parameters are guided.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development in petroleum engineering, and in particular to a macro- and micro-analysis method and system for displacement development based on a sand-filling model. Background Technology

[0002] In oil reservoir development, the internal seepage patterns and fluid distribution play a crucial role in improving reservoir recovery. Observing and statistically analyzing changes in fluid parameters within the reservoir has become an important research direction. Currently, experimental and numerical simulation methods are mainly used to study the oil-water distribution patterns within the reservoir.

[0003] Common reservoir simulation methods in the laboratory can be categorized by research dimension into core displacement simulation experiments, two-dimensional displacement simulation experiments, and three-dimensional displacement simulation experiments. Core displacement experiments rely on the core as the model basis. Determining the oil-water distribution within the core requires advanced equipment. Online nuclear magnetic resonance (NMR) technology can be used to clarify the distribution of oil and water phases within the pores, and the intensity of hydrogen signals can characterize oil saturation. However, this analysis relies on indirect hydrogen signal analysis, which introduces significant errors. After the core displacement experiment, CT scanning technology can be used to study the distribution of oil, water, and solids. However, its low resolution is unfavorable for accurately determining oil saturation and refining the distribution of remaining oil. The mainstream model for two-dimensional displacement simulation experiments is the glass etching model. This model can visually reflect the oil-water distribution, but the pore-throat structure is pre-calibrated by the glass, resulting in less influence from pore structure anisotropy and failing to accurately reflect the anisotropic structure of the reservoir's throat-pores. Three-dimensional displacement simulation experiments, based on large three-dimensional models, more realistically reflect the reservoir structure during the displacement experiment, but they cannot intuitively present the internal oil and water distribution. Therefore, there is an urgent need for an experimental device and processing method to demonstrate the macro- and micro-distribution of fluids under conditions close to those of an oil reservoir.

[0004] Previous studies on the relationship between calibration solution concentration and transmitted light intensity have introduced the optical analysis method Beer-Lambert's law, which describes the relationship between transmitted light intensity, concentration, and model thickness. However, while this law applies to the saturation of glass etching, its applicability to the saturation identification of other visualization models still needs improvement. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a macro- and micro-analysis method and system for displacement development based on a sand-filled model to overcome or at least partially solve the above problems.

[0006] According to one aspect of the present invention, a macro- and micro-analysis method for displacement development based on a sand-filling model is provided, the analysis method comprising:

[0007] Construct a simulated oil reservoir system based on a visualized two-dimensional sand-filling model;

[0008] Obtain displacement images;

[0009] Identify macroscopic oil saturation;

[0010] Establish a regular evaluation method for micro-level residual oil.

[0011] Optionally, the construction of the simulated reservoir system based on the visualized two-dimensional sand-filling model specifically includes:

[0012] A visual two-dimensional sand-filled model was constructed to simulate the anisotropic characteristics of the pore-throat channels in the reservoir.

[0013] The reservoir system includes a displacement dynamics and fluid replenishment system, a visual two-dimensional sand-filling model and image acquisition system, and a pressure maintenance and production statistics system.

[0014] Optionally, the displacement power and fluid replenishment system includes: a power supply device, a liquid storage device, and a reagent pre-mixing device, each including a plunger pump, an intermediate container containing multiple liquids, and the reagent pre-mixing device connected downstream, to facilitate the implementation of the displacement scheme.

[0015] Optionally, the visualized two-dimensional sand filling model and image acquisition system includes: the visualized two-dimensional sand filling model is placed on a planar supplementary light, and a camera is set above the visualized two-dimensional sand filling model to acquire macro and micro images.

[0016] Optionally, the pressure maintenance and liquid production statistics system includes: a back pressure valve and its power supply device to maintain the pressure in the model at a reasonable level, and a liquid production metering device at the output end.

[0017] Optionally, obtaining the displacement image specifically includes:

[0018] The acquisition of macroscopic displacement images involves continuously capturing video footage during the displacement process and selecting images from key nodes as macroscopic displacement images.

[0019] The microscopic residual oil images were acquired by a microscope camera during the displacement process, and the images located within the affected area were selected as the microscopic residual oil images.

[0020] Optionally, the identification of macroscopic oil saturation specifically includes: oil saturation light intensity calibration and saturation field diagram conversion;

[0021] The oil saturation light intensity calibration includes: using a standard saturation test experiment, using a size of 2.5cm×2.5cm as the optical calculation basis model, the thickness of the internal cavity is consistent with the thickness of the visualized two-dimensional sand-filled model; its interior is not filled with quartz sand particles, and groove channels are etched at both the injection end and the output end of the upper plate of the model, and a single flat-bottomed light source is set at the bottom.

[0022] The saturation field map transformation includes: image gridding segmentation, grid merging, and saturation value transformation;

[0023] The image gridding segmentation acquires macroscopic images, crops sample regions, and segments ROI regions based on pixel points;

[0024] The mesh merging is based on 2m×2n. The RGB values ​​in each mesh are merged by taking the arithmetic mean. The smaller meshes are denoted as h and w respectively. Each micro-element mesh is assigned an index according to its row and column position.

[0025] The saturation value conversion utilizes a macroscopic oil saturation recognition method to convert the RGB values ​​of each grid into grayscale values, and then uses the grayscale values ​​and oil saturation to convert the transmitted light information into oil saturation values.

[0026] All grids complete the conversion of transmitted light information into oil saturation values, forming a macroscopic oil saturation field map.

[0027] Optionally, the method for establishing the micro-level residual oil regularity evaluation method specifically includes: residual oil extraction within the meta-grid, residual oil feature identification, and statistical analysis of the proportion of residual oil regularity levels.

[0028] Optionally, the extraction of residual oil within the meta-grid specifically includes:

[0029] Using the micro-mesh of the acquired macroscopic image, each micro-mesh is grayscaled. The pores in each mesh are separated from the rock, and the pore portion in each mesh is retained while the rock portion is defined as an invalid region.

[0030] The two fluids, oil and water, within the pores of each grid are further grayscaled. The two fluids are distinguished based on the color thresholds of the oil phase fluid and the water phase fluid. The oil phase fluid portion within each grid is retained, while the water phase portion is defined as an invalid region.

[0031] Optionally, the residual oil feature identification specifically includes:

[0032] The geometric features of the oil phase fluid within each grid are extracted, based on shape factor, concavity coefficient, and aspect ratio; the relationship between the shape factor and the remaining oil shape is expressed as follows:

[0033]

[0034] In the formula, S a is the shape factor; S is the area occupied by the remaining oil; C is the perimeter of the remaining oil;

[0035] The closer the shape factor is to half the average distance from the geometric center to the boundary within the remaining oil, the more regular the shape of the remaining oil.

[0036] The relationship between the concavity coefficient and the shape of the remaining oil is expressed as follows:

[0037]

[0038] Among them, S b r is the concavity coefficient. min r is the minimum distance between the geometric center and the boundary of the remaining oil. max This is the maximum distance between the geometric center and the boundary of the remaining oil.

[0039] The closer the concavity is to 1, the more regular it is, indicating that the difference in the boundary of the remaining oil edge is smaller, and the remaining oil;

[0040] The relationship between the aspect ratio and the shape of the remaining oil is expressed as follows:

[0041]

[0042] Among them, S c The aspect ratio; W o Remaining oil width; L o Remaining oil length;

[0043] The closer the aspect ratio is to 1, the closer the shape of the remaining oil is to oil droplets.

[0044] A macro- and micro-analysis system for displacement development based on a sand-filling model, applying the aforementioned macro- and micro-analysis method for displacement development based on a sand-filling model, the analysis system comprising:

[0045] The simulated reservoir system construction module is used to construct a simulated reservoir system based on a visualized two-dimensional sand-filled model;

[0046] Displacement image acquisition module, used to acquire displacement images;

[0047] Oil saturation identification module, used to identify macroscopic oil saturation;

[0048] The evaluation method establishment module is used to establish a regular evaluation method for micro-level residual oil.

[0049] This invention provides a macro- and micro-analysis method and system for displacement development based on a sand-filled model. The analysis method includes: constructing a simulated reservoir system based on a visualized two-dimensional sand-filled model; acquiring displacement images; identifying macro-level oil saturation; and establishing a micro-level regularity evaluation method for remaining oil. This method can more objectively and comprehensively determine the impact of macro- and micro-level oil-water distribution images during the displacement process on reservoir development effects, optimize the influence of different development methods on the distribution and type of remaining oil under oilfield conditions, and guide the production injection fluid parameters.

[0050] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0051] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A flowchart of a macro- and micro-analysis method for displacement development based on a sand-filling model is provided for an embodiment of the present invention;

[0053] Figure 2 A schematic diagram of the saturation field based on the oil-water distribution in a microscopic image, provided for an embodiment of the present invention;

[0054] Figure 3 This invention provides a residual oil distribution map based on a single grid in a microscopic image, as provided in an embodiment of the invention. Detailed Implementation

[0055] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0056] The terms "comprising" and "having," and any variations thereof, in the specification, embodiments, claims, and drawings of this invention are intended to cover non-exclusive inclusion, such as including a series of steps or units.

[0057] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0058] This invention aims to meet the requirements of simulating reservoir conditions while also intuitively reflecting the changes in oil and water distribution within the reservoir, and providing a reference for further quantitative description. It utilizes a two-dimensional porous media-filled model to obtain macro- and microscopic images of the displacement process, and further obtains the distribution of water saturation and the distribution of various microscopic residual oils.

[0059] This invention aims to establish a method for fluid saturation identification and microscopic analysis based on a visualized two-dimensional sand-filled model. This method involves secondary processing of displacement experimental images obtained from a two-dimensional filled displacement model. At the macroscopic scale, it acquires images of oil saturation, and at the microscopic scale, it statistically analyzes and calculates the proportion of various types of residual oil. Based on image processing and optical computation methods, it transforms qualitative displacement images into quantitative studies of the regular proportions of residual oil. This allows for a more objective and comprehensive determination of the impact of macroscopic and microscopic oil-water distribution images during the displacement process on reservoir development, optimizing the influence of different development methods on the distribution and types of residual oil under oilfield conditions, and guiding the production injection fluid parameters.

[0060] The invention comprises four processes: assembling a simulated reservoir system based on a visualized two-dimensional sand-filled model, acquiring displacement images, identifying macroscopic oil saturation, and evaluating the regularity of microscopic remaining oil.

[0061] 1. The simulated reservoir system based on the visualized two-dimensional sand-filling model is constructed as follows:

[0062] The visualized two-dimensional sand-filled model is just one application scenario for reservoir simulation. It establishes a transparent, rigid, hollow shell to simulate the overlying strata and basement of the reservoir, preventing reservoir fluids from overflowing outwards.

[0063] The transparent hollow shell is filled with quartz sand particles that simulate the porous medium of the reservoir, and is fixed to the upper and lower tempered glass surfaces using an inorganic adhesive layer to simulate the anisotropic characteristics of the pore-throat of the reservoir.

[0064] The model-making details are hidden, only retaining the model's typical characteristics of being transparent and composed of porous media;

[0065] The reservoir system includes displacement and observation devices, including displacement power and fluid replenishment systems, visualization two-dimensional sand-filling models and image acquisition systems, and pressure maintenance and production statistics systems.

[0066] The displacement power and fluid replenishment system includes a power supply device, a liquid storage device, and a reagent pre-mixing device, which respectively include a plunger pump, an intermediate container containing different liquids (crude oil, formation water, and displacement agent), and a reagent pre-mixing device connected to the latter to facilitate the implementation of the displacement scheme.

[0067] A visualized two-dimensional sand-filling model and its image acquisition system are described. The visualized two-dimensional sand-filling model is placed on a planar supplementary light, and a camera is set above the visualized two-dimensional sand-filling model to acquire macro and micro images.

[0068] The pressure maintenance and liquid production statistics system, back pressure valve and its power supply device maintain the pressure in the model at a reasonable level, and the liquid production metering device is provided at the output end.

[0069] After the visualized two-dimensional sand-filling model is connected to the displacement and product fluid collection system, saturated water, saturated oil and aging processes are carried out.

[0070] The saturated water process is characterized by using a power supply device, an intermediate container containing formation water, a visual two-dimensional sand-filled model, a back pressure valve, and a product metering device to inject formation water at a constant flow rate of 0.1 ml / min. When the volume of injected formation water is stable and equal to the volume of produced water in the product metering device, the saturated water process is considered to be over.

[0071] After the water saturation process is completed, the oil saturation process is started. Using a power supply device, an intermediate container containing crude oil, a visual two-dimensional sand-filling model, a back pressure valve, and a liquid production metering device, the oil saturation process is considered to be over when the amount of crude oil injected and the amount of oil produced in the liquid production metering device are stable and equal.

[0072] After the water saturation process is completed, the oil saturation process is started. The pressure in the visualized two-dimensional sand-filled model is stabilized and maintained at the preset pressure condition of the reservoir for more than 72 hours using the back pressure valve and its power supply device, so that its internal wettability and other properties are close to the reservoir characteristics. During this process, the initial water saturation and oil saturation in the model are calculated.

[0073] After the simulated reservoir system is assembled, displacement experiments are carried out, and macroscopic and microscopic displacement images are acquired during the process.

[0074] The displacement experiment is characterized by a power supply device, an intermediate container containing a displacement agent, a reagent pre-mixing device, a visual two-dimensional sand-filled model, a back pressure valve, a product liquid metering device, and a camera. The water content in the product liquid metering device is kept stable at over 98%, and macroscopic displacement images and microscopic residual oil images are acquired during the displacement process.

[0075] The key feature of acquiring macroscopic displacement images is that they are acquired by continuously shooting video by a camera during the displacement process, and images of key nodes are selected as macroscopic displacement images.

[0076] The microscopic residual oil images were acquired by a microscope camera during the displacement process, and the images located within the affected area were selected as the microscopic residual oil images.

[0077] The macroscopic oil saturation identification is obtained as follows:

[0078] The identification of macroscopic oil saturation is characterized by two processes: isointense calibration of oil saturation and conversion of saturation field diagrams.

[0079] The method for calibrating the intensity of light with oil saturation adopts the standard saturation test experiment. A small-sized (2.5cm×2.5cm) optical calculation model is used as the basic model. The thickness of its internal cavity is consistent with the thickness of the visualized two-dimensional sand-filled model, but it is not filled with quartz sand particles. The injection end and output end of the model plate are etched with groove channels to facilitate the uniform propagation of the injected fluid during the injection process. A single flat-bottomed light source is set at its bottom.

[0080] In the basic optical calculation model, the intensity of transmitted light in a medium of equal thickness is independent of the intensity of incident light from a single light source, and is only related to the equivalent thickness of the fluid within the model. The ratio of this equivalent thickness to the total thickness can characterize the fluid saturation at that point, which can be expressed as a unique relationship between the intensity of transmitted light and the fluid saturation in this model.

[0081] The quantitative characterization of transmitted light intensity is achieved by grayscale value scaling, which requires a basic optical computational model with standard saturation images at different saturation levels.

[0082] The standard saturation image acquisition method involves slowly injecting crude oil into the optical computational model at a flow rate of 0.1 ml / min until all air is expelled. The colors in the image obtained from the model's viewport remain consistent. The computational model image at the initial oil saturation is recorded, and the volume of injected oil is also recorded.

[0083] Injected oil volume V oi And calculate the initial oil saturation S in the pores within the model. oi :

[0084]

[0085] In the formula: a is the side length of the model, and h is the height of the cavity inside the model;

[0086] When the air inside the optical computational fundamental model is completely evacuated, the corresponding oil saturation S is... oi =1;

[0087] Standard saturation images were generated by simultaneously injecting a fixed ratio of oil and water into the model at different saturation levels, with ratios of (1:9, 2:8, ..., 9:1). The oil saturation of the corresponding images was denoted as S. o1 S o2 S o9The total injection flow rate was 0.2 ml / min. The oil and water were produced at a stable output ratio at the output end. The calculation model images with different oil saturation were obtained, and the transmitted light intensity was stable and unique.

[0088] The grayscale value scalarization process is used to calculate the base model image, which has stable three primary color features, namely RGB features (R represents red, G represents green, and B represents blue). It is used to determine the intensity of transmitted light by single scalarization and to perform color dimensionality reduction on the image.

[0089] Color dimensionality reduction processing converts the RGB values ​​in an image into grayscale values. Grayscale values ​​range from 0 to 255, where 0 represents black and 255 represents white. The relationship between RGB and grayscale values ​​is expressed as follows:

[0090] I=R×0.299+G×0.587+B×0.114 (2)

[0091] In the formula: I is the grayscale value;

[0092] The computational basis model image with an oil saturation of 1 undergoes color dimensionality reduction processing, recording the grayscale values ​​I of the saturated crude oil image. oi ;

[0093] After color dimensionality reduction processing, each standard saturation image yields corresponding grayscale values ​​for different saturations. Based on Beer-Lambert's law for image color processing, the relationship between grayscale values ​​and oil saturation is established.

[0094]

[0095] In the formula: K is the gray conversion coefficient of crude oil, which is obtained by substituting the initial oil saturation and gray value into the above formula. The standard saturation test experiment is completed.

[0096] The transformation of saturation field maps is characterized by three processes: image gridding, grid merging, and saturation value transformation.

[0097] The characteristic of image gridding segmentation is that it acquires macroscopic images, crops sample regions (ROIs), and segments the ROI regions based on pixels;

[0098] After image meshing and segmentation, mesh merging is performed to improve computational speed and stability, with a 2 m ×2 n As the basis for mesh merging, the RGB values ​​within each mesh are merged by taking the arithmetic mean, and are denoted as h and w respectively. Each micro-element mesh is assigned an index according to its row and column position.

[0099] The saturation value conversion utilizes a macroscopic oil saturation recognition method to first convert the RGB values ​​of each grid into grayscale values, and then uses the grayscale values ​​and oil saturation to convert the transmitted light information into oil saturation values.

[0100] All grids complete the conversion of transmitted light information into oil saturation values, forming a macroscopic oil saturation field map.

[0101] 3. The evaluation of the regularity of the microscopic residual oil is as follows:

[0102] The evaluation of micro-level residual oil regularity is characterized by three processes: residual oil extraction within a micro-grid, residual oil feature identification, and statistical analysis of the proportion of residual oil regularity levels.

[0103] Residual oil extraction within micro-grids: Using the micro-grids of the acquired macroscopic images, each micro-grid is grayscaled. The pores and rocks within each grid are separated after processing. The pore portion within each grid is retained, and the rock portion is defined as an invalid region.

[0104] The two fluids, oil and water, are further grayscaled in the pores of each grid. The two fluids are distinguished according to the color threshold of the oil phase fluid and the water phase fluid. The oil phase fluid part in each grid is retained, and the water phase part is defined as an invalid region.

[0105] The feature of residual oil feature identification is that it extracts the geometric features of the oil phase fluid within each grid, according to the shape factor, concavity coefficient, and aspect ratio.

[0106] The relationship between the shape factor and the shape of the remaining oil is expressed as follows:

[0107]

[0108] In the formula, S a S is the shape factor; S is the area occupied by the remaining oil; C is the perimeter of the remaining oil. The closer the shape factor is to half the average distance from the geometric center to the boundary within the remaining oil, the more regular the shape of the remaining oil.

[0109] The relationship between the concavity coefficient and the shape of the remaining oil can be expressed as:

[0110]

[0111] Among them, S b r is the concavity coefficient. min r is the minimum distance between the geometric center and the boundary of the remaining oil. max This represents the maximum distance between the geometric center and the boundary of the remaining oil. The closer the concavity is to 1, the more regular it is, indicating that the boundary difference of the remaining oil edge is smaller, and the remaining oil...

[0112] The relationship between the aspect ratio and the shape of the remaining oil is expressed as follows:

[0113]

[0114] Among them, S c The aspect ratio; W o Remaining oil width; L o Remaining oil length. The closer the aspect ratio is to 1, the closer the shape of the remaining oil is to an oil droplet.

[0115] Three residual oil characteristics are used as comprehensive evaluation criteria, designed as three residual oil characteristic values, namely shape factor characteristic value, concavity coefficient characteristic value, and aspect ratio characteristic value.

[0116] The three categories will be standardized and divided into unified categories, including the following steps:

[0117] Step 1: First, statistically analyze the levels of the shape factor characteristic value, concavity coefficient characteristic value, and aspect ratio characteristic value for each remaining oil.

[0118] Step 2: Establish a special hierarchical evaluation of shape factor eigenvalues, concavity coefficient eigenvalues, and aspect ratio eigenvalues:

[0119] In the regularity evaluation of residual oil, if any field of shape factor characteristic value, concavity coefficient characteristic value and aspect ratio characteristic value reaches the first level of regularity, then the regularity classification of the residual oil is the first level of regular residual oil.

[0120] Step 3: Establish the hierarchical scores for shape factor eigenvalues, concavity coefficient eigenvalues, and aspect ratio eigenvalues:

[0121] To assign scores to different regularity levels, scores are first set according to the level types classified by the three residual oil regularity characteristic values. If a K-level regularity is set (3≤K≤7), then the scores for the shape factor characteristic value, concavity coefficient characteristic value, and aspect ratio characteristic value of the first-level regularity level are all 1. The first-level regularity level indicates the highest degree of regularity.

[0122] The characteristic values ​​of shape factor, concavity coefficient, and aspect ratio are all set to 2 for the second-level regularity level. The regularity level of the second-level regularity level is second only to the first-level regularity level, and its remaining oil regularity potential is slightly higher than that of the first-level regularity level.

[0123] The characteristic values ​​of shape factor, concavity coefficient, and aspect ratio are all set to 3 for the third-level regularity level. The regularity level of the third-level regularity level is lower than that of the first-level and second-level regularity levels, and has a slightly higher regularity potential than the first-level and second-level regularity levels.

[0124] Following this logic, the final score for the shape factor characteristic value, concavity coefficient characteristic value, and aspect ratio characteristic value of the K-level regularity level is set to 5. The K-level regularity level has the lowest degree of regularity and the greatest potential for regularity.

[0125] Calculate the total regularity score = regularity score of shape factor eigenvalue (cannot be 1) + regularity score of shape factor eigenvalue (cannot be 1) + regularity score of aspect ratio eigenvalue (cannot be 1);

[0126] When a Level 1 ruleability is achieved in any game, the total ruleability score is 1.

[0127] Step 4: Classify the grading criteria for the regularity characteristics of remaining oil based on the regularity level:

[0128]

[0129] Step 5: Based on the shape factor characteristic value, concavity coefficient characteristic value and aspect ratio characteristic value of different residual oils, the final residual oil classification is obtained. The regularity of the residual oil after displacement is evaluated. The more regular the shape of the residual oil surface, the stronger the hydrodynamic scouring ability of that area, that is, the better the hydrodynamic wave effect.

[0130] The characteristic of the remaining oil percentage statistics lies in the statistical analysis of the area and quantity of remaining oil at different regularity levels.

[0131] Beneficial Effects: The method of this invention is safe and reliable, and the experimental equipment can be reused, saving resources and protecting the environment. Based on a visualized filling model, a reservoir dynamic development simulation experiment is conducted. Macroscopic displacement images are collected, and these images are used to construct analytical micro-elements using a grid-based segmentation algorithm. Transmitted light intensity is matched with fluid saturation to establish a saturation field map based on grid segmentation. The regularity of the remaining oil distribution area and quantity is quantitatively described using three methods: shape factor, concavity coefficient, and aspect ratio. A positive correlation exists between the regularity of the remaining oil and the hydrodynamic intensity, providing a reliable and practical research method for studying the distribution of remaining fluids in porous media and subsequent development.

[0132] The above specific embodiments further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A macro- and micro-analysis method for displacement development based on a sand-filling model, characterized in that, The analytical method includes: Construct a simulated oil reservoir system based on a visualized two-dimensional sand-filling model; Obtain displacement images; Identify macroscopic oil saturation; Establish a regular evaluation method for micro-level residual oil.

2. The macro- and micro-analysis method for displacement development based on a sand-filling model according to claim 1, characterized in that, The construction of the simulated reservoir system based on the visualized two-dimensional sand-filling model specifically includes: A visual two-dimensional sand-filled model was constructed to simulate the anisotropic characteristics of the pore-throat channels in the reservoir. The reservoir system includes a displacement dynamics and fluid replenishment system, a visual two-dimensional sand-filling model and image acquisition system, and a pressure maintenance and production statistics system.

3. The macro- and micro-analysis method for displacement development based on a sand-filling model according to claim 2, characterized in that, The displacement power and fluid replenishment system includes a power supply device, a liquid storage device, and a reagent pre-mixing device, each comprising a plunger pump, an intermediate container containing multiple liquids, and a reagent pre-mixing device connected downstream, facilitating the implementation of the displacement scheme.

4. The macro- and micro-analysis method for displacement development based on a sand-filling model according to claim 2, characterized in that, The visualized two-dimensional sand-filling model and image acquisition system includes: A two-dimensional sand-filled model is placed on a flat fill light, and a camera is set above the model to acquire macro and micro images.

5. The macro- and micro-analysis method for displacement development based on a sand-filling model according to claim 2, characterized in that, The pressure maintenance and liquid production statistics system includes: a back pressure valve and its power supply device to maintain the pressure in the model at a reasonable level, and a liquid production metering device at the output end.

6. The macro- and micro-analysis method for displacement development based on a sand-filling model according to claim 1, characterized in that, The acquisition of the displacement image specifically includes: The acquisition of macroscopic displacement images involves continuously capturing video footage during the displacement process and selecting images from key nodes as macroscopic displacement images. The microscopic residual oil images were acquired by a microscope camera during the displacement process, and the images located within the affected area were selected as the microscopic residual oil images.

7. The macro- and micro-analysis method for displacement development based on a sand-filling model according to claim 1, characterized in that, The identification of macroscopic oil saturation specifically includes: oil saturation light intensity calibration and saturation field diagram conversion; The oil saturation light intensity calibration includes: using a standard saturation test experiment, using a size of 2.5cm×2.5cm as the optical calculation basis model, the thickness of the internal cavity is consistent with the thickness of the visualized two-dimensional sand-filled model; its interior is not filled with quartz sand particles, and groove channels are etched at both the injection end and the output end of the upper plate of the model, and a single flat-bottomed light source is set at the bottom. The saturation field map transformation includes: image gridding segmentation, grid merging, and saturation value transformation; The image gridding segmentation acquires macroscopic images, crops sample regions, and segments ROI regions based on pixel points; The mesh merging is based on 2m×2n. The RGB values ​​in each mesh are merged by taking the arithmetic mean. The smaller meshes are denoted as h and w respectively. Each micro-element mesh is assigned an index according to its row and column position. The saturation value conversion utilizes a macroscopic oil saturation recognition method to convert the RGB values ​​of each grid into grayscale values, and then uses the grayscale values ​​and oil saturation to convert the transmitted light information into oil saturation values. All grids complete the conversion of transmitted light information into oil saturation values, forming a macroscopic oil saturation field map.

8. The macro- and micro-analysis method for displacement development based on a sand-filling model according to claim 1, characterized in that, The method for establishing micro-level residual oil regularity evaluation specifically includes: residual oil extraction within the meta-grid, residual oil feature identification, and statistical analysis of the proportion of residual oil regularity levels.

9. The macro- and micro-analysis method for displacement development based on a sand-filling model according to claim 8, characterized in that, The extraction of residual oil within the meta-grid specifically includes: Using the micro-mesh of the acquired macroscopic image, each micro-mesh is grayscaled. The pores in each mesh are separated from the rock, and the pore portion in each mesh is retained while the rock portion is defined as an invalid region. The two fluids, oil and water, within the pores of each grid are further grayscaled. The two fluids are distinguished based on the color thresholds of the oil phase fluid and the water phase fluid. The oil phase fluid portion within each grid is retained, while the water phase portion is defined as an invalid region.

10. The macro- and micro-analysis method for displacement development based on a sand-filling model according to claim 8, characterized in that, The residual oil feature identification specifically includes: The geometric features of the oil phase fluid within each grid are extracted, based on shape factor, concavity coefficient, and aspect ratio; the relationship between the shape factor and the remaining oil shape is expressed as follows: In the formula, S a is the shape factor; S is the area occupied by the remaining oil; C is the perimeter of the remaining oil; The closer the shape factor is to half the average distance from the geometric center to the boundary within the remaining oil, the more regular the shape of the remaining oil. The relationship between the concavity coefficient and the shape of the remaining oil is expressed as follows: Among them, S b r is the concavity coefficient. min r is the minimum distance between the geometric center and the boundary of the remaining oil. max This is the maximum distance between the geometric center and the boundary of the remaining oil. The closer the concavity is to 1, the more regular it is, indicating that the difference in the boundary of the remaining oil edge is smaller, and the remaining oil; The relationship between the aspect ratio and the shape of the remaining oil is expressed as follows: Among them, S c The aspect ratio; W o Remaining oil width; L o Remaining oil length; The closer the aspect ratio is to 1, the closer the shape of the remaining oil is to oil droplets.

11. A macro- and micro-analysis system for displacement development based on a sand-filled model, employing the macro- and micro-analysis method for displacement development based on a sand-filled model as described in any one of claims 1-10, characterized in that, The analysis system includes: The simulated reservoir system construction module is used to construct a simulated reservoir system based on a visualized two-dimensional sand-filled model; Displacement image acquisition module, used to acquire displacement images; Oil saturation identification module, used to identify macroscopic oil saturation; The evaluation method establishment module is used to establish a regular evaluation method for micro-level residual oil.

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