Method for realizing high-multiple water flooding core microcosmic residual oil dynamic characterization
By using imaging and image processing technologies, the micro-pore regions of the core are delineated, and the changes in reservoir core properties are dynamically characterized. This solves the problem of the difficulty in quantifying the micro-dynamic changes in the reservoir and improves the accuracy of oil and gas field development.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TSINGHUA UNIVERSITY
- Filing Date
- 2023-01-17
- Publication Date
- 2026-07-24
Smart Images
Figure CN116051511B_ABST
Abstract
Description
Technical Field
[0001] This article relates to, but is not limited to, the fields of new energy and high-efficiency energy conservation, specifically to the field of oil and gas exploration, development and utilization, and particularly to, but is not limited to, a method for achieving dynamic characterization of microscopic residual oil in high-magnification water-drive cores. Background Technology
[0002] Intensifying the exploration, development, and utilization of oil and gas is one of the important tasks facing my country's current energy security crisis and achieving sustainable socio-economic development. my country's oilfields have complex geological conditions and significant reservoir heterogeneity. Oilfields developed using waterflooding have now entered high and ultra-high water-cut stages, but the remaining oil and gas reserves still account for a large proportion. Effectively exploiting these remaining reservoir resources and improving reservoir recovery rates are crucial issues for energy security and the efficient development and utilization of oil and gas resources. However, the development history of ultra-high water-cut oilfields is long and the development methods are complex. After long-term reservoir scouring and multiple development operations, the reservoir water cut changes significantly, and the microstructure and properties of the core also differ. The remaining oil and gas resources exhibit a complex and diverse distribution. The impact of the micro-dynamic changes in the core after reservoir scouring on seepage characteristics is still unclear, making the existing understanding of oil and gas reservoir microstructure insufficient for the effective implementation of precise and efficient development in ultra-high water-cut stages. Current research lacks effective quantitative analysis methods to reveal the laws governing the micro-dynamic changes in reservoir cores and their impact on the formation and distribution of remaining oil and gas, directly limiting the accurate characterization of oil and gas reservoir dynamics. Therefore, developing dynamic characterization methods for reservoir core displacement is of great significance for understanding the laws governing formation hydrocarbon transport and utilization. However, the microstructure of reservoir cores is complex, with numerous pores and significant differences in pore morphology. Traditional methods provide statistical parameters (pore size distribution curves, wettability distribution curves, fluid volume distribution, etc.) that do not show significant changes in parameter variation when characterizing the microstructure and displacement behavior of displaced cores. This makes it difficult to intuitively and quantitatively reflect the relationship between the core displacement process and local pore structure characteristics, wettability, mineral distribution, and hydrocarbon migration behavior, thus lacking feasible dynamic characterization methods. Summary of the Invention
[0003] The following is an overview of the subject matter described in detail herein. This overview is not intended to limit the scope of the claims.
[0004] To capture the dynamic changes in the microstructure and properties of reservoir cores during long-term displacement development, this application provides a method for dynamic characterization of residual oil in high-expansion water-drive cores. This method can accurately divide the complex core microstructure into individual pore regions, intuitively reflecting the micro-dynamics of reservoir cores during long-term displacement from a local perspective. It establishes a direct link between the micro-changes in individual pore regions and the overall core structure, providing a new quantitative research approach for analyzing the dynamic changes in reservoir core microstructure and the formation and utilization of residual oil and gas resources.
[0005] This application provides a method for dynamic characterization of residual oil in high-magnification water-drive cores, the method comprising:
[0006] 1) Digital images of pore space distribution, core mineral distribution, and microscopic residual oil distribution at different displacement times were obtained using imaging methods during high-magnification waterflooding experiments in core samples.
[0007] 2) Based on the digital image of the pore space distribution at the initial displacement moment obtained in step 1), calculate the shortest distance from each pore space pixel in the digital image to the solid wall, and assign the calculated shortest distance value to the pixel to form a distance distribution map of the pore system at the initial displacement moment.
[0008] 3) Based on the pore system distance distribution map obtained in step 2), form a maximum sphere for each pixel with the shortest distance as the radius, using the pixel as the center.
[0009] When the largest spheres formed by different pixels have a complete containment relationship, the largest sphere with a smaller radius value merges into the largest sphere with a larger radius value, and the shortest distance value of the center pixel of the contained sphere (the largest sphere with a smaller radius value) is changed to the radius value of the contained sphere (the largest sphere with a larger radius value);
[0010] When the largest spheres formed by the different pixels intersect and do not belong to a complete containment relationship, the radius value of the different pixels is taken as the largest shortest distance among the different pixels;
[0011] Using the radius of each pixel determined in step 3) as the radius, and taking each pixel as the center, form the largest sphere of each pixel, thus forming a spatial distribution map of the pore system size at the initial displacement moment;
[0012] 4) Using the digital image of the pore space distribution at the initial displacement moment obtained in step 1) as a reference, extract the pore space topological skeleton, compare it with the pore system size spatial distribution map at the initial displacement moment formed in step 3), assign pore size values to the pixels on the pore space topological skeleton (the points on the topological skeleton will definitely be on the pore system size spatial distribution map, that is, the points on the topological skeleton will definitely overlap with the points on the pore size spatial distribution map, and the value of the point on the topological skeleton is the value of the overlapping point on the pore size spatial distribution map), and obtain the pore size change curve on the pore space topological skeleton (when the topological skeleton has branches, different topological skeletons will partially overlap, the pore size change curves of the overlapping parts are the same and the maximum absolute value of the derivative of the local region is the same, the cross section of the dividing region is the same, the additional branch part will determine the maximum absolute value of the derivative of the new local region, and the cross section of the dividing region), determine the maximum absolute value of the derivative of the local region in the pore size change curve, take the pixel of the maximum absolute value of the derivative of the local region as the starting point, connect the shortest line to the pore wall to form a spatial cross section, thereby dividing the different pore regions at the initial displacement moment.
[0013] The maximum absolute value of the derivative of the local region is the maximum absolute value of the derivative of the curve change within the local region, and the local region is the region within a distance of 5 nearby pixels.
[0014] 5) Using the different pore regions at the initial time as a reference, the overall pore space at different displacement times obtained in step 1) is divided, and the dynamic changes of the core micro properties in each pore region with different displacement times are measured to achieve dynamic characterization of the micro residual oil in the high-magnification water-driven core.
[0015] In one embodiment provided in this application, the imaging method in step 1) includes obtaining two-dimensional planar micro-displacement features of the core or obtaining three-dimensional structural micro-displacement features of the core.
[0016] In one embodiment provided in this application, the microscopic displacement features of the core in two-dimensional plane are obtained using scanning electron microscopy imaging and / or optical microscopy imaging; and the microscopic displacement features within the three-dimensional structure of the core are obtained using computed tomography imaging and / or nuclear magnetic resonance imaging.
[0017] In one embodiment provided in this application, the displacement in step 1) is selected from one or more of water displacement, chemical displacement, gas displacement, water displacement, and chemical displacement.
[0018] In one embodiment provided in this application, the different displacement times mentioned in step 1) include the time when the displacement reaches 100 PV or more and the initial displacement time.
[0019] In one embodiment provided in this application, the different displacement times are selected from any two or more of the following: before displacement, at the initial displacement time, at displacement times of 0.5 PV, 1 PV, 3 PV, 10 PV, 50 PV, and 500 PV.
[0020] In one embodiment provided in this application, the method for calculating the shortest distance from each pore space pixel in the digitized image to the solid wall in step 2) is the Euclidean distance transformation method.
[0021] In one embodiment provided in this application, the Euclidean distance transformation method is the Euclidean distance transformation method described in the following literature: T. Saito and J. Toriwaki, (1994) New algorithms for Euclidean distance transformation on an n-dimensional digitized picture with applications, Pattern Recognition 27:1551-1565; the specific technical name is DistanceTransformation.
[0022] In one embodiment provided in this application, the extraction of the pore space topological skeleton in step 4) includes the pore skeleton curve extracted by the two-dimensional pore structure corrosion method, the pore skeleton curve extracted by the three-dimensional pore structure corrosion method, and other curves used to describe the interconnection relationship of the pore structure.
[0023] In one embodiment provided in this application, the method for extracting the topological skeleton of the pore space is based on the method in the literature Building skeleton models via 3-D medial surface / axis thinning algorithms. (1994) Computer Vision, Graphics, and Image Processing, 56(6):462–478, 1994.
[0024] In one embodiment provided in this application, the core microstructure parameters in step 5) are selected from the micropore radius value, residual oil volume, mineral content, and fluid contact angle, which quantitatively characterize any one of the core pore structure distribution, mineral distribution, core wettability distribution, and micro residual oil volume changes during the process from the initial stage of water injection to high-multiplication water drive.
[0025] In one embodiment provided in this application, the dynamic characterization of the microscopic residual oil in the high-magnification water-driven core in step 5) can be achieved by plotting the displacement time as the horizontal axis and the average value of the core microscopic properties at different displacement times as the vertical axis; or by plotting the change curve of the microscopic properties at different displacement times within a certain pore region as the research unit.
[0026] In one embodiment provided in this application, when the core microstructure parameter is the fluid contact angle, the angle between the water-oil-solid three phases in each pore region is measured, i.e., the fluid contact angle, to characterize the wettability of the water-oil two-phase fluid in that pore region. By combining the fluid contact angles in all pore regions, the wettability distribution of the core at a certain displacement time can be obtained. By comparing the digital images of the wettability distribution at different displacement times, the dynamic changes in the wettability distribution of the pore region at different displacement times can be obtained, realizing the dynamic characterization of the microscopic residual oil in high-magnification water-driven cores.
[0027] In one embodiment provided in this application, the digital image includes any one or more of the following: pore space size distribution, two-phase or multi-phase fluid space distribution, mineral distribution, or core wettability distribution characteristics.
[0028] The method provided in this application is a method for quantitatively characterizing the microscopic properties of cores and the dynamic characterization of microscopic residual oil during long-term waterflooding.
[0029] This invention utilizes image processing and analysis techniques to extract the microstructure, core properties, and water-oil two-phase distribution characteristics at different times during core displacement. To fully consider the coupled influence between fluid displacement behavior and core micro-dynamic changes, this invention starts from the microscopic perspective of single-pore local structure, dividing the complex pore system within the core into regions, and dynamically characterizing the core microstructure size, wettability, and remaining oil and gas content within each pore region during fluid displacement. Compared to existing methods that describe remaining oil and gas and analyze seepage characteristics based on constant core microstructure, the method provided in this application fully considers the micro-dynamic changes within the local structure of the displaced core and their impact, analyzing the dynamic response of core microstructure and internal fluid characteristics during displacement from the perspective of single-pore local structure. The resulting understanding of the micro-dynamic laws of displaced cores and the dynamic description of remaining oil and gas can provide more scientific guidance and a theoretical basis for formulating targeted development measures for high and ultra-high water-cut oil and gas fields to effectively utilize remaining oil and gas and improve reservoir recovery.
[0030] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. Other advantages of this application may be realized and obtained by means of the methods described in the description. Attached Figure Description
[0031] The accompanying drawings are used to provide an understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.
[0032] Figure 1 The first step of the method in this application embodiment is to calculate the spatial distribution map of the pore size of the core microstructure; this mainly includes the binarized distribution map of the pore structure of the digital core, the pore structure distance map, and the spatial distribution of the pore size. Figure 3 One operation step.
[0033] Figure 2 The second step of the method in this application embodiment is to divide the pore region according to the maximum absolute value of the derivative of the local region of pore structure size change; wherein (a) to (c) are respectively selecting the local location of the pore structure, drawing the pore size change curve and dividing the local pore region.
[0034] Figure 3 The images shown are the effect diagrams of the pore region division of the three-dimensional pore structure digital core in the embodiments of this application, namely: core pore spatial distribution map, core pore diameter spatial distribution map, core pore topology map, and core pore region distribution map.
[0035] Figure 4 This embodiment of the application shows the distribution characteristics of dynamic changes in pore size within the same pore region of the three-dimensional pore structure digital core before and after water drive. Detailed Implementation
[0036] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application are described in detail below. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be arbitrarily combined with each other.
[0037] This application provides a method for dynamic characterization of microscopic residual oil in high-magnification water-drive cores, the method comprising:
[0038] 1) Digital images of pore space distribution, core mineral distribution, and microscopic residual oil distribution at different displacement times were obtained using imaging methods during high-magnification waterflooding experiments in core samples.
[0039] 2) Based on the digital image of the pore space distribution at the initial displacement moment obtained in step 1), calculate the shortest distance from each pore space pixel in the digital image to the solid wall, and assign the calculated shortest distance value to the pixel to form a distance distribution map of the pore system at the initial displacement moment.
[0040] 3) Based on the pore system distance distribution map obtained in step 2), form a maximum sphere for each pixel with the shortest distance as the radius, using the pixel as the center.
[0041] When the largest spheres formed by different pixels have a complete containment relationship, the largest sphere with a smaller radius value merges into the largest sphere with a larger radius value, and the shortest distance value of the center pixel of the contained sphere (the largest sphere with a smaller radius value) is changed to the radius value of the contained sphere (the largest sphere with a larger radius value);
[0042] When the largest spheres formed by the different pixels intersect and do not belong to a complete containment relationship, the radius value of the different pixels is taken as the largest shortest distance among the different pixels;
[0043] Using the radius of each pixel determined in step 3) as the radius, and taking each pixel as the center, form the largest sphere of each pixel, thus forming a spatial distribution map of the pore system size at the initial displacement moment;
[0044] 4) Using the digital image of the pore space distribution at the initial displacement moment obtained in step 1) as a reference, extract the pore space topological skeleton, compare it with the pore system size spatial distribution map at the initial displacement moment formed in step 3), assign pore size values to the pixels on the pore space topological skeleton (the points on the topological skeleton will definitely be on the pore system size spatial distribution map, that is, the points on the topological skeleton will definitely overlap with the points on the pore size spatial distribution map, and the value of the point on the topological skeleton is the value of the overlapping point on the pore size spatial distribution map), and obtain the pore size change curve on the pore space topological skeleton (when the topological skeleton has branches, different topological skeletons will partially overlap, the pore size change curves of the overlapping parts are the same and the maximum absolute value of the derivative of the local region is the same, the cross section of the dividing region is the same, the additional branch part will determine the maximum absolute value of the derivative of the new local region, and the cross section of the dividing region), determine the maximum absolute value of the derivative of the local region in the pore size change curve, take the pixel of the maximum absolute value of the derivative of the local region as the starting point, connect the shortest line to the pore wall to form a spatial cross section, thereby dividing the different pore regions at the initial displacement moment.
[0045] The maximum absolute value of the derivative of the local region is the maximum absolute value of the derivative of the curve change within the local region, and the local region is the region within a distance of 5 nearby pixels.
[0046] 5) Using the different pore regions at the initial time as a reference, the overall pore space at different displacement times obtained in step 1) is divided, and the dynamic changes of the core micro properties in each pore region with different displacement times are measured to achieve dynamic characterization of the micro residual oil in the high-magnification water-driven core.
[0047] In the embodiments of this application, the imaging method in step 1) includes obtaining two-dimensional planar micro-displacement features of the core or obtaining three-dimensional structural micro-displacement features of the core.
[0048] In the embodiments of this application, the microscopic displacement features of the core in two-dimensional plane are obtained using scanning electron microscopy imaging and / or optical microscopy imaging; and the microscopic displacement features within the three-dimensional structure of the core are obtained using computed tomography imaging and / or nuclear magnetic resonance imaging.
[0049] In the embodiments of this application, the displacement in step 1) is selected from one or more of water displacement, chemical displacement, gas displacement, water displacement, and chemical displacement.
[0050] In this embodiment of the application, the different displacement times mentioned in step 1) include the time when the displacement reaches 100 PV or more and the initial displacement time.
[0051] In the embodiments of this application, the different displacement times are selected from any two or more of the following: before displacement, at the initial displacement time, at displacement times of 0.5PV, 1PV, 3PV, 10PV, 50PV, and 500PV.
[0052] In this embodiment of the application, the method for calculating the shortest distance from each pore space pixel in the digitized image to the solid wall in step 2) is the Euclidean distance transformation method.
[0053] In this embodiment, the Euclidean distance transformation method is the Euclidean distance transformation method described in the following literature: T. Saito and J. Toriwaki, (1994) New algorithms for Euclidean distance transformation on an n-dimensional digitized picture with applications, Pattern Recognition 27:1551-1565; the specific technical name is Distance Transformation.
[0054] In this embodiment of the application, the extraction of the pore space topological skeleton in step 4) includes the pore skeleton curve extracted by the two-dimensional pore structure corrosion method, the pore skeleton curve extracted by the three-dimensional pore structure corrosion method, and other curves used to describe the interconnection relationship of the pore structure.
[0055] In this embodiment, the method for extracting the topological skeleton of the pore space is based on the method in the literature Building skeleton models via 3-D medial surface / axis thinning algorithms. (1994) Computer Vision, Graphics, and Image Processing, 56(6):462–478, 1994.
[0056] In this embodiment of the application, the core microstructure parameters mentioned in step 5) are selected from the micropore radius value, residual oil volume, mineral content, and fluid contact angle, which quantitatively characterize any one of the core pore structure distribution, mineral distribution, core wettability distribution, and micro residual oil volume changes during the process from the initial stage of water injection to high-multiplication water drive.
[0057] In the embodiments of this application, the dynamic characterization of the microscopic residual oil in the high-magnification water-driven core in step 5) can be achieved by plotting the displacement time as the horizontal axis and the average value of the core microscopic properties at different displacement times as the vertical axis; or by plotting the change curve of the microscopic properties at different displacement times within a certain pore region as the research unit.
[0058] In this embodiment, when the core microstructure parameter is the fluid contact angle, the angle between the water-oil-solid three phases in each pore region is measured, i.e., the fluid contact angle. This is used to characterize the wettability of the water-oil two-phase fluid in that pore region. By combining the fluid contact angles in all pore regions, the wettability distribution of the core at a certain displacement time can be obtained. By comparing the digital images of the wettability distribution at different displacement times, the dynamic changes in the wettability distribution of the pore region at different displacement times can be obtained, realizing the dynamic characterization of the microscopic residual oil in high-magnification water-driven cores.
[0059] In this embodiment of the application, the digital image includes any one or more of the following: pore space size distribution, two-phase or multi-phase fluid space distribution, mineral distribution, or core wettability distribution characteristics.
[0060] The method provided in this application embodiment can be used to quantitatively characterize the microscopic properties of cores and the dynamic characterization of microscopic residual oil during long-term waterflooding.
[0061] Example 1
[0062] In this embodiment, a two-dimensional slice of a digital core with a real pore structure (a two-dimensional slice of a three-dimensional digital core with a real pore structure in Example 2, to visually demonstrate the beneficial effects of the method of this application) is used as the implementation object. A method for realizing dynamic characterization of microscopic residual oil in high-magnification water-drive cores is carried out according to the following steps:
[0063] 1) Real core samples from the Daqing Oilfield were selected, and the microscopic distribution of the core at different displacement times was obtained using computed tomography (CT) imaging. The digital core images obtained from the scans were then processed and analyzed using MATLAB to extract digital images of the core pore space distribution at different displacement times. In this embodiment, the digital image of the core pore space distribution includes two parts: the pore space and the core matrix, which are represented by the numbers 255 and 0, respectively. The resulting images show white and black areas, for example... Figure 1 (a) shows the two-dimensional pore space distribution of the core at the initial moment of displacement.
[0064] 2) For the digital images of pore space distribution at different displacement times obtained in step 1), the Euclidean distance transform method is used to calculate the shortest distance from each pore space pixel with a value of 255 to the solid wall with a value of 0 in the digital image, and the calculated shortest distance value is assigned to that pixel to form a distance distribution map of the pore system, such as... Figure 1 As shown in (b);
[0065] 3) Based on the pore system distance distribution map obtained in step 2), form the largest sphere that fills the local pore space with the pixel as the center and the shortest distance value as the radius; when the largest spheres formed at different pixels have a complete containment relationship, the largest sphere with a smaller radius value merges into the largest sphere with a larger radius value, and the shortest distance value of the center pixel of the contained sphere is changed to the radius value of the largest containing sphere.
[0066] When the largest spheres formed by different pixels intersect but are not completely contained, the value of each pixel is taken as the maximum value of the center pixel of the intersecting sphere (i.e., the largest shortest distance), forming a spatial distribution map of the pore system's size, such as... Figure 1 As shown in (c);
[0067] 4) Using the digital image of the pore space distribution at the initial moment of the displacement process obtained in step 1) as a reference, extract the pore space topological skeleton. Compare it with the size spatial distribution map of the pore system at the initial moment of displacement formed in step 3), assign pore size values to the pixels on the pore space topological skeleton, and obtain the pore size change curve on the pore space topological skeleton (when the topological skeleton has branches, different topological skeletons partially overlap, the pore size change curves of the overlapping parts are the same, and the maximum absolute value of the derivative of the local region is the same, the cross section of the dividing region is the same, the additional branch will determine the maximum absolute value of the derivative of the new local region, and the cross section of the dividing region). The flat stage of the curve indicates that the pixels of the pore space topological skeleton have similar or the same pore size, and the sloping stage of the curve indicates that the pore size of the pixels of the topological skeleton has a large change, such as Figure 2As shown in (d); by determining the maximum absolute value of the derivative of a local region of the pore size change curve, i.e., the maximum absolute value of the local slope in the pore size change curve; taking the pixel point of the maximum absolute value of the derivative of the local region as the starting point, and connecting it to the shortest line on the pore wall to form a spatial cross section, different pore regions within the pore system at the initial moment of displacement are divided, such as... Figure 2 The diagram shows the porosity region, where pixels with the same grayscale value represent areas divided into pore regions. Specifically, when multiple adjacent pixels have the same maximum absolute value of local slope, the middle pixel is taken as the starting point.
[0068] The maximum absolute value of the derivative of a local region is the maximum absolute value of the derivative of the curve change within that local region. The local region is defined as the area within a distance of 5 nearby pixels. The maximum point of the derivative in a local region is not necessarily the maximum point on the entire curve. Multiple maximum points of the derivative can exist in local regions on a curved curve of dimensional change. The criterion for determining this is that any area within a distance of 5 nearby pixels (i.e., 5 pixels representing 5 maximum spheres) is considered a local region.
[0069] 5) Using the pore regions at the initial displacement time as a reference, the pore spaces at different displacement times obtained in step 1) are divided, and the dynamic changes of the core micro-properties in each pore region with different displacement times are measured to achieve dynamic characterization of the micro-residual oil in the high-magnification water-driven core. For example, the dynamic changes of the microstructure and fluid distribution in some or all pore regions at different displacement times can be analyzed by comparing the digital images of the distribution of micro-displacement characteristics of the core at different displacement times, so as to achieve dynamic characterization of the displacement core.
[0070] from Figure 1 As can be seen, based on the spatial distribution map of core pores, a digital image containing information on the spatial distribution of core microstructure pore size can be generated using image analysis algorithms; based on Figure 2 It can analyze the local pore size changes in pore size distribution images, and determine the boundaries of different pore regions based on the derivative of the maximum local region of the pore size change curve. The method is simple and intuitive, and the divided pore regions can accurately capture the microstructural size characteristics of the rock core.
[0071] Example 2
[0072] The process in this embodiment is the same as in embodiment 1, except that the object of this embodiment is a three-dimensional porous structure digital core.
[0073] from Figure 3As can be seen, the method for realizing the microscopic dynamic characterization of displacement cores provided in this application can also effectively process digital cores with three-dimensional pore structures, divide different pore regions of the three-dimensional microstructure cores, observe the microscopic dynamic changes of the cores at different displacement times within the three-dimensional pore regions, and realize the microscopic dynamic characterization of digital cores with three-dimensional pore structures during the displacement process. For example... Figure 3 A total of 15,682 pore regions were delineated based on the three-dimensional pore structure at the initial moment of displacement. Within the same pore region, the difference in pore diameter and the pore diameter ratio of the local structure before and after long-term water injection displacement were calculated. Both the pore diameter difference and the pore diameter ratio of the core pore regions are microscopic dynamic changes in the displaced core. Figure 4 As shown, based on the pore regions divided by the method provided in this application, the difference in pore size and the pore size ratio before and after core displacement within the local pore regions are statistically analyzed. The pore size variation range is mainly from -20μm to 50μm, and the pore size ratio variation range is mainly from -0.5 to 1.5. Negative values indicate that the pore region within the three-dimensional structure becomes smaller, while positive values indicate that the pore region becomes larger. This clearly reflects the variation law of local pores before and after core displacement and the pore characteristics of micro-dynamic changes.
Claims
1. A method for dynamic characterization of residual oil at the microscopic level in high-magnification water-drive cores, wherein, The method includes: 1) Digital images of pore space distribution, core mineral distribution, and microscopic residual oil distribution at different displacement times, including the initial displacement time, were obtained from high-magnification waterflooding experiments using imaging methods. 2) Based on the digital image of the pore space distribution at the initial displacement moment obtained in step 1), calculate the shortest distance from each pore space pixel in the digital image to the solid wall, and assign the calculated shortest distance value to the pixel to form a distance distribution map of the pore system at the initial displacement moment. 3) Based on the pore system distance distribution map obtained in step 2), form a maximum sphere for each pixel with the shortest distance as the radius, using the pixel as the center. When the largest spheres formed by different pixels have a complete containment relationship, the largest sphere with a smaller radius value merges into the largest sphere with a larger radius value. The shortest distance value of the center pixel of the contained sphere (i.e., the largest sphere with a smaller radius value) is changed to the radius value of the contained sphere (i.e., the largest sphere with a larger radius value). When the largest spheres formed by the different pixels intersect and do not belong to a complete containment relationship, the radius value of the different pixels is taken as the largest shortest distance among the different pixels; Using the radius of each pixel determined in step 3) as the radius, and with each pixel as the center, form the largest sphere of each pixel, thus forming a spatial distribution map of the pore system size at the initial displacement moment; 4) Using the digital image of the pore space distribution at the initial displacement moment obtained in step 1) as a reference, extract the pore space topological skeleton, compare it with the pore system size spatial distribution map at the initial displacement moment formed in step 3), assign pore size values to the pixels on the pore space topological skeleton, and obtain the pore size change curve on the pore space topological skeleton. Determine the maximum absolute value of the derivative of the local region in the pore size change curve, and take the pixel with the maximum absolute value of the derivative of the local region as the starting point and connect it to the shortest line on the pore wall to form a spatial cross section, thereby dividing the different pore regions at the initial displacement moment. The maximum absolute value of the derivative of the local region is the maximum absolute value of the derivative of the curve change within the local region, and the local region is the region within a distance of 5 nearby pixels. 5) Using the different pore regions at the initial time as a reference, the overall pore space at different displacement times obtained in step 1) is divided, and the dynamic changes of the core micro properties in each pore region with different displacement times are measured to achieve dynamic characterization of the micro residual oil in the high-magnification water-driven core.
2. The method according to claim 1, wherein, Step 1) The imaging method includes obtaining two-dimensional planar micro-displacement features of the core or obtaining three-dimensional structural micro-displacement features of the core.
3. The method according to claim 2, wherein, Two-dimensional planar micro-displacement features of core samples obtained using scanning electron microscopy and / or optical microscopy. Microscopic displacement characteristics within the three-dimensional structure of cores obtained using computed tomography and / or nuclear magnetic resonance imaging.
4. The method according to claim 1, wherein, Step 1) refers to one or more of the following methods: water displacement, chemical displacement, gas displacement, water-gas displacement, and chemical displacement.
5. The method according to any one of claims 1 to 4, wherein, The different displacement times mentioned in step 1) include the time when the displacement reaches 100 PV or more and the initial time of displacement.
6. The method according to any one of claims 1 to 4, wherein, The different displacement times are selected from any two or more of the following: before displacement, at the initial displacement time, and at displacement times of 0.5 PV, 1 PV, 3 PV, 10 PV, 50 PV, and 500 PV.
7. The method according to any one of claims 1 to 4, wherein, The method for calculating the shortest distance from each pixel in the pore space of the digitized image to the solid wall in step 2) is the Euclidean distance transformation method.
8. The method according to any one of claims 1 to 4, wherein, Step 4) involves extracting the pore space topological skeleton, which includes pore skeleton curves extracted by the two-dimensional pore structure corrosion method, pore skeleton curves extracted by the three-dimensional pore structure corrosion method, and other curves used to describe the interconnection relationships of pore structures.
9. The method according to any one of claims 1 to 3, wherein, In step 5), the core microstructure parameters are selected from the micropore radius value, residual oil volume, mineral content, and fluid contact angle. These parameters quantify any one of the following: core pore structure distribution, mineral distribution, core wettability distribution, and changes in micro residual oil volume during the process from the initial stage of water injection to high-expansion water drive.
10. The method according to any one of claims 1 to 3, wherein, The digital image includes any one or more of the following: pore space size distribution, two-phase or multi-phase fluid space distribution, mineral distribution, or core wettability distribution characteristics.