Multi-scale characterization methods and devices, reservoir identification methods and devices

Abstract

This invention provides a multi-scale characterization method and apparatus, a reservoir identification method and apparatus, a storage medium, a processor, and a computer program product, belonging to the field of oil and gas exploration technology. The multi-scale characterization method includes: extracting local images of fracture bodies, fracture zones, and fracture zones that make up the fracture bodies layer by layer from the profile images of geological outcrops within the target area; sequentially measuring the first-scale characterization of the fracture bodies from the extracted local images; the second-scale characterization of the fracture zones and fracture zones; and the characterization of the faults, cavities, fractures, and bedrock properties that constitute each fracture zone and fracture zone, serving as the third-scale characterization of each fracture body. This achieves three levels of characterization of the fracture bodies in the research target and surrounding area: outline, internal structure, and structural details. The characterization results are then used to guide reservoir fine description and prediction, reserve evaluation, and development well deployment, among other related work.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration technology, specifically to a multi-scale characterization method and apparatus, a reservoir identification method and apparatus, a storage medium, a processor, and a computer program product. Background Technology

[0002] Fractured bodies refer to reservoirs developed within a strike-slip fault context, consisting of faults, associated fractures, and tight, low-permeability sandstone altered by these faults, with impermeable argillaceous rocks and tight layers sealing off the upper and lateral sides. From the fault outwards, based on the degree of fracture development, they are successively divided into breccia zones and fracture zones, with occasional cavities developing in the fault core. Fractured bodies are a promising sweet spot type in tight reservoirs, identified in recent years during tight oil exploration and development in the southern margin of the Ordos Basin, and represent a favorable target for high-yield and efficient tight oil development. Exploration and development practice shows that fractured bodies develop in association with strike-slip faults, with the strike-slip faults controlling the size and distribution of fractured bodies.

[0003] Currently, the geological understanding of fractured bodies mainly focuses on the macroscopic level, including their development scale, geological boundaries, distribution patterns, and reservoir formation models. However, many geological problems and unresolved geological parameters still exist at the reservoir description level, which seriously restricts the detailed description and prediction of fractured body reservoirs, reserve evaluation, and deployment of development wells.

[0004] In the process of realizing this invention, the inventors of this application discovered that the above-mentioned problems have not yet been effectively solved. Summary of the Invention

[0005] The purpose of this invention is to provide a method for characterizing fracture bodies, which can characterize the parameter information of fracture bodies in a holistic, detailed, and multi-scale manner.

[0006] To achieve the above objectives, embodiments of the present invention provide a multi-scale characterization method for fracture bodies based on geological outcrops, including: Acquire profile images of geological outcrops within the target area; Identify one or more fracture bodies distributed in the geological outcrop from the profile image, and measure the first-scale characterization of each fracture body; Determine the first local profile image corresponding to each fracture body, extract the crack zone and fracture zone that make up the corresponding fracture body from the local profile image, and measure the second-scale characterization of the crack zone and fracture zone. Determine the corresponding second local profile image for each fracture zone, and determine the fault characterization, cavity characterization, fracture characterization and bedrock physical property characterization of the corresponding fracture zone based on the second local profile image; Determine the corresponding third local profile image for each fracture zone, and based on the third local profile image, determine the fracture characterization and bedrock physical property characterization of the corresponding fracture zone; and Fault characterization, cavity characterization, fracture characterization, and bedrock physical property characterization are used as the third scale characterization of fracture bodies.

[0007] Optionally, the first-scale characterization includes the geometry of the fracture body profile and a first characterization parameter, which includes one or more of the following: measurement, statistical value, and / or correlation coefficient: width, height, perimeter, area.

[0008] Optionally, the second-scale characterization of the fault zone includes the structural combination of the fault zone profile, the geometry, and a second characterization parameter, which includes one or more of the following: measurement, statistical value, and / or correlation coefficient: width, height, perimeter, area; The second-scale characterization of the fracture zone includes the geometry of the fracture zone profile and the third characterization parameter, which includes one or more of the following measurements, statistics, and / or correlation coefficients: width, height, perimeter, and area.

[0009] Optionally, fault characterization includes fault properties and a fourth characterization parameter, which includes measurements, statistics, and / or correlation coefficients of one or more of the following: strike, dip, height, and length; Cavity characterization includes filling characteristics and a fifth characterization parameter, which includes measurements, statistics, and / or correlation coefficients of one or more of the following: orientation, dip angle, height, and width; Fracture characterization includes background lithofacies, filling characteristics, and a sixth characterization parameter, which includes measurements, statistics, and / or correlation coefficients of one or more of the following: strike, dip angle, height, aperture, and density. Bedrock physical property characterization includes measurements, statistical values, and / or correlation coefficients of sandstone porosity and permeability.

[0010] Optionally, acquire profile images of geological outcrops within the target area, including: Original profile images of geological outcrops are acquired from multiple angles using image acquisition equipment; The original profile image is processed into a point cloud and then 3D registration of the point cloud is performed to obtain the registered point cloud model. A white body model of a TIN network is constructed based on a registered point cloud model. The dissection and analysis of the acquired original cross-sectional images from multiple angles are projected onto the white body model to obtain a measurable three-dimensional model of the geological outcrop and cross-sectional images from multiple angles.

[0011] Furthermore, one or more fracture bodies distributed in the geological outcrops are identified from the profile images, and a first-scale characterization of each fracture body is measured, including: Identifying the external contours of fractures distributed in geological outcrops based on 3D models and profile images; and Each identified fracture body is assigned a number, and the first-scale characterization measurements of different parts of each fracture body are determined according to a preset direction. The preset directions are from top to bottom, from left to right, from bottom to top, or from right to left.

[0012] Furthermore, a first local cross-sectional image corresponding to each fracture body is determined, and the crack zone and rupture zone constituting the corresponding fracture body are extracted from the local cross-sectional image. A second-scale characterization of the crack zone and rupture zone is measured, including: Extract the first local cross-sectional image corresponding to the current fracture body from the cross-sectional image based on the identified external contour; Based on the dissection and analysis of the first partial cross-sectional image, the structural combination and geometric shape of the current fracture body are identified, wherein the structural combination is a single-core structural combination or a multi-core structural combination, and the geometric shape is conical, spindle-shaped, or cylindrical; and The second-scale characterization measurements of different parts of each fracture zone or break zone are determined according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left.

[0013] Furthermore, a second local profile image is determined for each fracture zone. Based on the second local profile image, the fault characterization, cavity characterization, fracture characterization, and bedrock physical property characterization of the corresponding fracture zone are determined, including: Based on the identified structural combinations and geometry, extract the corresponding second local profile image of the current fracture zone from the first local profile image; Based on the dissection and analysis of the second local profile image, identify each fault, cavity, and fracture in the current fracture zone, and determine: the fault nature of each fault, the filling characteristics of each cavity, and the background lithofacies and filling characteristics of each fracture; The measurements representing the third-scale characterization of different parts of each fault, cavity, and fracture are determined according to a preset direction, where the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and The porosity and permeability of the bedrock obtained from rock samples at the corresponding location of the current fracture zone are used as the physical properties characterization of the bedrock of the current fracture zone.

[0014] Furthermore, a third local profile image corresponding to each fracture zone is determined, and based on the third local profile image, fracture characterization and bedrock physical property characterization of the corresponding fracture zone are determined, including: Based on the identified structural combinations and geometric shapes, extract the corresponding third local profile image of the current fracture zone from the first local profile image; Based on the dissection and analysis of the third local profile images, the background lithofacies, filling characteristics, and each fracture of the current fracture zone are identified; The third-scale measurements of different locations along each crack are determined according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and The porosity and permeability of the bedrock obtained from rock samples at the corresponding locations of the current fracture zone are used as the physical properties characterization of the bedrock of the current fracture zone.

[0015] Furthermore, this multi-scale characterization method also includes: Acquire imaging logging data of the near-surface and subsurface portions of geological outcrops within the target area; Based on the interpretation of imaging logging data, the first-scale, second-scale, and third-scale characteristics of the near-surface and subsurface portions of each fracture body are identified.

[0016] On the other hand, embodiments of this application provide a multi-scale characterization method for fracture bodies based on geological outcrops, including: Based on the multi-scale characterization method of this application, multi-scale characterization data of geological outcrops in the target area are determined, and training and test datasets are constructed. A multi-scale representation model is trained using a training dataset and validated using test data; and Based on the validated multi-scale characterization model, multi-scale characterization data of underground fracture bodies in the target area are predicted to guide the quantitative characterization and prediction of underground fracture bodies.

[0017] Optionally, the multi-scale representation model includes a first prediction model, a second prediction model, and a third prediction model, which are used to predict the first-scale representation, the second-scale representation, and the third-scale representation, respectively. The input data for the first prediction model are the external contour data of the geological outcrop and the geometry of the fracture body profile, and the output is the first-scale representation. The input data for the second prediction model are the structural combination of the fracture zone profile, the geometry of the fracture zone profile, the geometry of the fracture zone profile, and the first-scale representation, and the output is the second-scale representation. The input data for the third prediction model are fault properties, cavity filling characteristics, background lithofacies of fractures, filling characteristics and second characterization parameters, and the output is a third-scale characterization.

[0018] On the other hand, embodiments of this application provide a reservoir identification method, including: Based on the multi-scale characterization method of this application, multi-scale characterization data of multiple geological outcrops within the target area are determined; Obtain reservoir identification results for fractured bodies at multiple geological outcrop locations; By combining multi-scale characterization data and reservoir identification results, training and testing datasets are constructed. A reservoir identification model was trained using a training dataset, and the model was validated using test data; and Based on the validated reservoir identification model, predict whether fracture bodies in or around the target area are usable reservoirs.

[0019] On the other hand, embodiments of this application provide a multi-scale characterization device for fracture bodies based on geological outcrops, including: an image acquisition module and a multi-scale measurement module. The image acquisition module is used to acquire profile images of geological outcrops within the target area; The multi-scale measurement module is configured as follows: Identify one or more fracture bodies distributed in the geological outcrop from the profile image, and measure the first-scale characterization of each fracture body; Determine the first local profile image corresponding to each fracture body, extract the crack zone and fracture zone that make up the corresponding fracture body from the local profile image, and measure the second-scale characterization of the crack zone and fracture zone. Determine the corresponding second local profile image for each fracture zone, and determine the fault characterization, cavity characterization, fracture characterization and bedrock physical property characterization of the corresponding fracture zone based on the second local profile image; Determine the corresponding third local profile image for each fracture zone, and based on the third local profile image, determine the fracture characterization and bedrock physical property characterization of the corresponding fracture zone; and Fault characterization, cavity characterization, fracture characterization, and bedrock physical property characterization are used as the third scale characterization of fracture bodies.

[0020] Optionally, the first-scale characterization includes the geometry of the fracture body profile and a first characterization parameter, which includes one or more of the following: measurement, statistical value, and / or correlation coefficient: width, height, perimeter, area.

[0021] Optionally, the second-scale characterization of the fault zone includes the structural combination of the fault zone profile, the geometry, and a second characterization parameter, which includes one or more of the following: measurement, statistical value, and / or correlation coefficient: width, height, perimeter, area; The second-scale characterization of the fracture zone includes the geometry of the fracture zone profile and the third characterization parameter, which includes one or more of the following measurements, statistics, and / or correlation coefficients: width, height, perimeter, and area.

[0022] Optionally, fault characterization includes fault properties and a fourth characterization parameter, which includes measurements, statistics, and / or correlation coefficients of one or more of the following: strike, dip, height, and length; Cavity characterization includes filling characteristics and a fifth characterization parameter, which includes measurements, statistics, and / or correlation coefficients of one or more of the following: orientation, dip angle, height, and width; Fracture characterization includes background lithofacies, filling characteristics, and a sixth characterization parameter, which includes measurements, statistics, and / or correlation coefficients of one or more of the following: strike, dip angle, height, aperture, and density. Bedrock physical property characterization includes measurements, statistical values, and / or correlation coefficients of sandstone porosity and permeability.

[0023] Optionally, the image acquisition module is configured as follows: Original profile images of geological outcrops are acquired from multiple angles using image acquisition equipment; The original profile image is processed into a point cloud and then 3D registration of the point cloud is performed to obtain the registered point cloud model. A white body model of a TIN network is constructed based on a registered point cloud model. The dissection and analysis of the acquired original cross-sectional images from multiple angles are projected onto the white body model to obtain a measurable three-dimensional model of the geological outcrop and cross-sectional images from multiple angles.

[0024] Furthermore, the multi-scale measurement module is also configured as follows: Identifying the external contours of fractures distributed in geological outcrops based on 3D models and profile images; and Each identified fracture body is assigned a number, and the first-scale characterization measurements of different parts of each fracture body are determined according to a preset direction. The preset directions are from top to bottom, from left to right, from bottom to top, or from right to left.

[0025] Furthermore, the multi-scale measurement module is also configured as follows: Extract the first local cross-sectional image corresponding to the current fracture body from the cross-sectional image based on the identified external contour; Based on the dissection and analysis of the first partial cross-sectional image, the structural combination and geometric shape of the current fracture body are identified, wherein the structural combination is a single-core structural combination or a multi-core structural combination, and the geometric shape is conical, spindle-shaped, or cylindrical; and The second-scale characterization measurements of different parts of each fracture zone or break zone are determined according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left.

[0026] Furthermore, the multi-scale measurement module is also configured as follows: Based on the identified structural combinations and geometry, extract the corresponding second local profile image of the current fracture zone from the first local profile image; Based on the dissection and analysis of the second local profile image, identify each fault, cavity, and fracture in the current fracture zone, and determine: the fault nature of each fault, the filling characteristics of each cavity, and the background lithofacies and filling characteristics of each fracture; The measurements representing the third-scale characterization of different parts of each fault, cavity, and fracture are determined according to a preset direction, where the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and The porosity and permeability of the bedrock obtained from rock samples at the corresponding location of the current fracture zone are used as the physical properties characterization of the bedrock of the current fracture zone.

[0027] Furthermore, the multi-scale measurement module is also configured as follows: Based on the identified structural combinations and geometric shapes, extract the corresponding third local profile image of the current fracture zone from the first local profile image; Based on the dissection and analysis of the third local profile images, the background lithofacies, filling characteristics, and each fracture of the current fracture zone are identified; The third-scale measurements of different locations along each crack are determined according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and The porosity and permeability of the bedrock obtained from rock samples at the corresponding locations of the current fracture zone are used as the physical properties characterization of the bedrock of the current fracture zone.

[0028] Optionally, the image acquisition module is also configured to acquire imaging logging data of the near-surface and subsurface portions of geological outcrops within the target area; The multi-scale measurement module is also configured to identify the first-scale, second-scale, and third-scale representations of the near-surface and subsurface portions of each fracture body based on the interpretation results of the imaging logging data.

[0029] On the other hand, embodiments of this application provide a multi-scale characterization device for fracture bodies based on geological outcrops, including: a multi-scale characterization model and a prediction module. The training dataset and test dataset used to train the multi-scale representation model are derived from the multi-scale representation data of geological outcrops in the target area determined by the multi-scale representation method of this application. The training dataset is used to train the multi-scale representation model, and the test data is used to verify the multi-scale representation model. The prediction module is configured to predict multi-scale representation data of unrepresented underground fracture bodies within the target area, based on a validated multi-scale representation model.

[0030] Optionally, the multi-scale representation model includes a first prediction model, a second prediction model, and a third prediction model, which are used to predict the first-scale representation, the second-scale representation, and the third-scale representation, respectively. The input data for the first prediction model are the external contour data of the geological outcrop and the geometry of the fracture body profile, and the output is the first-scale representation. The input data for the second prediction model are the structural combination of the fracture zone profile, the geometry of the fracture zone profile, the geometry of the fracture zone profile, and the first-scale representation, and the output is the second-scale representation. The input data for the third prediction model are fault properties, cavity filling characteristics, background lithofacies of fractures, filling characteristics and second characterization parameters, and the output is a third-scale characterization.

[0031] On the other hand, embodiments of this application provide a reservoir identification device, including a reservoir identification model and an identification module. The identification module is configured to: predict whether fracture bodies in or around the target area are usable reservoirs using a reservoir identification model; The reservoir identification model is a reservoir identification model trained on a training dataset and validated with test data. The data in the training dataset and the test dataset are derived from: multi-scale characterization data of multiple geological outcrops in the target area determined by the multi-scale characterization method of this application and reservoir identification results of fracture bodies at multiple geological outcrop locations.

[0032] On the other hand, embodiments of this application provide a processor configured to: execute a multi-scale characterization method according to this application, or execute a reservoir identification method according to this application.

[0033] On the other hand, embodiments of this application provide a machine-readable storage medium storing instructions that, when executed by a processor, cause the processor to: perform a multi-scale characterization method according to this application, or perform a reservoir identification method according to this application.

[0034] On the other hand, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements either the multi-scale characterization method of this application or the reservoir identification method of this application.

[0035] Using the above technical solution, local images of fracture bodies, fracture zones, and fracture zones that make up each fracture body are extracted layer by layer from the profile images of geological outcrops in the target area. Then, the first-scale representation of each fracture body, the second-scale representation of the fracture zone and fracture zone, the fault representation, cavity representation, fracture representation, and bedrock physical property representation of each fracture zone, and the fracture representation and bedrock physical property representation of each fracture zone are measured sequentially from the extracted local images. The fault representation, cavity representation, fracture representation, and bedrock physical property representation are used as the third-scale representation of each fracture body. Thus, through the first, second, and third-scale representations, the outline, internal structure, and structural details of fracture bodies in the target area are represented at three levels, respectively. The representation results are then used to guide the detailed description of reservoirs, reserve evaluation, and development well placement in the target area.

[0036] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0037] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of an embodiment of the multi-scale characterization method of the present invention; Figure 2 yes Figure 1 A schematic diagram of the digital model of the fracture body obtained from the cross-sectional image captured by the UAV in the embodiment; Figure 3 From Figure 2 A schematic diagram of the structural composition of a fractured body identified in the image; Figure 4 This is a schematic diagram of the storage structure of a dataset of multi-scale representation data obtained based on the multi-scale representation method of this invention. Figure 5 This is a schematic diagram of the storage structure of a statistical data set obtained by statistical analysis of multi-scale representation data obtained based on the multi-scale representation method of this invention. Figure 6 It is based on Figure 5 The obtained statistical data are concentrated in the thermogram of the fracture dip angle of the fracture zone; Figure 7 It is based on Figure 5 The obtained statistical data are concentrated in the rose diagram of the fracture dip angle of the fracture zone; Figure 8 yes Figure 1 A schematic diagram of the digital model of the fracture body obtained based on imaging ranging data in the embodiment; and Figure 9 This is a structural diagram of an embodiment of the multi-scale characterization device of the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0039] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0040] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0041] The acquisition, transmission, storage, use, and processing of data in this application comply with relevant national laws and regulations. Furthermore, it should be noted that existing industry solutions such as software, components, and models may be mentioned in the embodiments of this application. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0042] Figure 1 The schematic diagram illustrates a flowchart of a multi-scale characterization method according to an embodiment of this application. In this embodiment, the multi-scale characterization method includes the following steps: Step 1: Obtain profile images of geological outcrops within the target area; Step 2: Identify one or more fracture bodies distributed in the geological outcrops from the profile images, and measure the first-scale characterization of each fracture body. Step 3: Determine the first local profile image corresponding to each fracture body, extract the crack zone and fracture zone that make up the corresponding fracture body from the local profile image, and measure the second-scale characterization of the crack zone and fracture zone. Step 4: Determine the corresponding second local profile image for each fracture zone, and determine the fault characterization, cavity characterization, fracture characterization and bedrock physical property characterization of the corresponding fracture zone based on the second local profile image. Step 5: Determine the corresponding third local profile image for each fracture zone, and based on the third local profile image, determine the fracture characterization and bedrock physical property characterization of the corresponding fracture zone; and Step 6: Fault characterization, cavity characterization, fracture characterization, and bedrock physical property characterization are used as the third-scale characterization of the fracture body.

[0043] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0044] In this embodiment, a field outcrop profile with well-developed faults, complete exposure, and typical fracture structure characteristics is preferred. First, a high-precision UAV is used to conduct a comprehensive planar scan of the outcrop to obtain basic information about the outcrop and the planar distribution characteristics and patterns of the fault (or fracture body). Then, detailed profile information such as faults, cavities, fractures, and lithology is obtained through orthophoto and oblique measurements of the UAV profile. The digital model of the fracture body obtained through the above steps is as follows: Figure 2 As shown, from Figure 2 The composition of a fractured body identified in the sample is as follows: Figure 3 As shown.

[0045] In some implementations, step 1 may include the following sub-steps: Step 101: Acquire original profile images of the geological outcrops from multiple angles using an image acquisition device; Step 102: Process the original profile image into a point cloud and perform 3D registration of the point cloud to obtain a registered point cloud model; Step 103: Construct a white body model of the TIN network based on the registered point cloud model. Project the collected original cross-sectional images from multiple angles into the white body model to obtain a measurable three-dimensional model of the geological outcrop and cross-sectional images from multiple angles.

[0046] The purpose of step 2 is to obtain the external contour information of the fracture body. In some implementations, it also includes the statistics, analysis and visualization of the external contour information.

[0047] In this embodiment, the first scale characterization includes the geometry of the fracture body profile and the first characterization parameter, which includes one or more of the following: measured values, statistical values, and / or correlation coefficients: width, height, perimeter, and area.

[0048] In some implementations, obtaining information about the external contour of the fracture body can be achieved by first obtaining easily accessible near-surface profile information such as faults, cavities, cracks, and lithology through manual measurement; then, a three-dimensional digital outcrop model can be established using high-precision UAV scanning image information, which can be used as a carrier to identify and measure geological information and data of fracture bodies at different levels.

[0049] In some implementations, the statistical analysis and visualization of external contour-related information includes: The qualitative information of the external contour of the fracture is the shape of the fracture. Based on the fracture number, the cross-sectional shape of different fractures is statistically analyzed, such as conical, spindle-shaped, cylindrical, etc. The quantitative data of the external contour of the fracture includes parameters such as width (W), height (H), perimeter (D), and area (A). Due to the irregular shape of the fracture, width data needs to be measured at different locations from top to bottom. Based on the fracture number, they are numbered W1-1, W1-2, W1-3, etc., and so on for fractures with different numbers. The height (H), perimeter (D), and area (A) parameters of each fracture are unique, and are numbered H1, H2, ..., D1, D2, ..., A1, A2, ...

[0050] By comprehensively analyzing parameters such as width (W), height (H), perimeter (D), and area (A) of different fracture surfaces, the magnitudes of quantitative parameters (including maximum, minimum, average, median, variance, and standard deviation) and the correlations between these parameters are determined. Finally, the various parameters and correlations are visualized using histograms, line graphs, graphs, box plots, etc., forming qualitative and quantitative knowledge of the external contour of the fracture surface.

[0051] In some implementations, step 2 may include the following sub-steps: Step 201: Identify the external contours of fracture bodies distributed in geological outcrops based on the 3D model and profile images; and Step 202: Determine the number of each identified fracture body, and determine the measurement value of the first scale characterization of different parts of each fracture body according to the preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left.

[0052] The purpose of step 3 is to obtain information on the internal composition and structure of the fracture body. In some implementations, this also includes the statistics, analysis, and visualization of the internal composition and structure information.

[0053] In this embodiment, the second-scale characterization of the fracture zone includes the structural combination of the fracture zone profile, the geometry, and a second characterization parameter. The second characterization parameter includes one or more of the following measured values, statistical values, and / or correlation coefficients: width, height, perimeter, and area. The second-scale characterization of the crack zone includes the geometry of the crack zone profile and a third characterization parameter. The second characterization parameter includes one or more of the following measured values, statistical values, and / or correlation coefficients: width, height, perimeter, and area.

[0054] In some implementations, the basic information of the fracture zone includes its structural combination and geometry. Based on the fracture body number, the structural combinations of different fracture bodies are statistically analyzed, including single-core, multi-core, etc.; the cross-sectional shapes include conical, spindle-shaped, cylindrical, etc. Quantitative data for the fracture zone includes parameters such as fracture body width (W), height (H), perimeter (D), and area (A). Due to the irregular shape of the fracture zone, width data needs to be measured at different locations from top to bottom. Based on the fracture body number, they are numbered W1-1, W1-2, W1-3, etc., and so on for fracture bodies with different numbers. The height (H), perimeter (D), and area (A) parameters of each fracture zone are unique, and are numbered H1, H2, ..., D1, D2, ..., A1, A2, ... The basic information of the crack zone mainly concerns its geometry. Based on the fracture body number, the cross-sectional shapes of crack zones for different fracture bodies are statistically analyzed, including conical, spindle-shaped, cylindrical, etc. The quantitative data for the crack zone is consistent with that of the fracture zone.

[0055] In some implementations, parameters such as width (W), height (H), perimeter (D), and area (A) of different fracture zones in fracture bodies are comprehensively analyzed to determine the magnitude of quantitative parameters (including maximum, minimum, average, median, variance, and standard deviation) and the correlations between various parameters. Finally, the various parameters or correlations are visualized using histograms, line graphs, graphs, box plots, etc., forming qualitative and quantitative knowledge of fracture zones in fracture bodies. The quantitative characterization of fracture zones in fracture bodies is the same as that of fracture zones.

[0056] In some implementations, step 3 may include the following sub-steps: Step 301: Extract the first local cross-sectional image corresponding to the current fracture body from the cross-sectional image based on the identified external contour; Step 302: Based on the dissection and analysis of the first local cross-sectional image, identify the structural combination and geometric shape of the current fracture body, wherein the structural combination is a single-core structural combination or a multi-core structural combination, and the geometric shape is conical, spindle-shaped, or cylindrical. Step 303: Determine the measurement values ​​of the second-scale characterization of different parts of each crack zone or fracture zone according to the preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left.

[0057] The purpose of steps 4 and 5 is to obtain information related to the structural elements of the fracture zone and the crack zone, respectively. In some implementations, the information related to the structural elements is also statistically analyzed and visualized.

[0058] In this embodiment, fault characterization includes fault properties and a fourth characterization parameter, which includes one or more of the following measured values, statistical values, and / or correlation coefficients: strike, dip angle, height, and length; cavity characterization includes filling characteristics and a fifth characterization parameter, which includes one or more of the following measured values, statistical values, and / or correlation coefficients: strike, dip angle, height, and width; fracture characterization includes background lithofacies, filling characteristics, and a sixth characterization parameter, which includes one or more of the following measured values, statistical values, and / or correlation coefficients: strike, dip angle, height, aperture, and density; bedrock physical property characterization includes sandstone porosity and permeability measured values, statistical values, and / or correlation coefficients.

[0059] In some implementations, fault information includes fault properties and characterization parameters. Fault properties include extensional, compressional, and shear faults, etc.; characterization parameters include strike (T), dip (I), height (H), and length (L). Based on the fault body numbering, the corresponding characterization parameters of different fault bodies are statistically analyzed, numbered T1, T2, ..., I1, I2, ..., H1, H2, ..., L1, L2, ... The fault properties, strike (T), and dip (I) are comprehensively analyzed to determine the spatial development characteristics of the fault. Quantitative parameters are visualized using histograms, rose diagrams, etc. The height and length information of the fault (including maximum, minimum, average, median, variance, standard deviation, etc.), distribution patterns, and correlations are analyzed, and various parameters or correlations are visualized using histograms, line graphs, graphs, box plots, etc. The geometric characteristics of the fault are determined, forming qualitative and quantitative knowledge.

[0060] In some implementations, the cavity data includes basic information and characterization parameters. The filling properties of cavities corresponding to different fracture bodies are statistically analyzed, such as filled, partially filled, and unfilled. Cavity characterization parameters include width (W), orientation (T), inclination angle (I), height (H), and length (L). Due to the irregular shape of the cavities, width data needs to be measured at different locations from top to bottom. Based on the fracture body number, they are numbered W1-1, W1-2, W1-3, ..., and so on for cavities with different fracture body numbers. Based on the fracture body number, the corresponding characterization parameters of cavities corresponding to different fracture bodies are statistically analyzed, numbered T1, T2, ..., I1, I2, ..., H1, H2, ..., L1, L2, ... By comprehensively analyzing the cavity's filling properties, orientation (T), and tilt angle (I), the spatial development characteristics of the cavity are determined, and quantitative parameters are visualized using histograms, rose diagrams, and other methods. The height and length information of the cavity (including maximum, minimum, average, median, variance, standard deviation, etc.), distribution patterns, and correlations are analyzed, and various parameters or correlations are visualized using histograms, line graphs, graphs, box plots, heat maps, rose diagrams, and other methods. The geometric characteristics of the cavity are determined, forming qualitative and quantitative knowledge.

[0061] In some implementations, fracture data includes background lithofacies, infill characteristics, and characterization parameters, with separate statistics for the fracture zones and fracture zones of different fracture bodies. First, qualitative and quantitative data on fractures developed in the fracture zones are statistically analyzed. For the lithofacies types corresponding to the fracture zones (Lith1, Lith2, Lith3), the main lithofacies types corresponding to different fractures are statistically analyzed. For infill characteristics, the infill characteristics of different fractures are statistically analyzed, such as filled, partially filled, and unfilled, etc. Characterization parameters for fractures developed in the fracture zones include strike (T), dip angle (I), height (H), aperture (Ape), and density (D), where density (D) includes linear density and areal density. Each fracture in the fracture zone of each fracture body is statistically analyzed separately and numbered sequentially, with specific information including F1-T, F2-T, F3-T, ..., F1-I, F2-I, F3-I, ..., F1-H, F2-H, F3-H, ..., F1-Ape, F2-Ape, F3-Ape, ... The relevant information and data of the fracture zone are consistent with those of the breccia zone. A comprehensive analysis of the background facies, filling properties, strike (T), and dip angle (I) of the fractures determines their spatial development characteristics and effectiveness. Quantitative parameters are visualized using histograms, rose diagrams, etc. Information on fracture height (H) and length (L) (including maximum, minimum, average, median, variance, standard deviation, etc.) and correlations are analyzed, and various parameters or correlations are visualized using histograms, line graphs, graphs, box plots, heat maps, rose diagrams, etc. Figure 5 Determine the geometric characteristics of the cracks to form qualitative and quantitative knowledge.

[0062] In some implementations, bedrock physical property characterization mainly includes porosity and permeability. Sampling and analysis are performed on the modified bedrock of fracture zones and crack zones according to the fracture body numbering, taking physical properties as an example. Porosity data for fracture zones of different fracture bodies are statistically analyzed, numbered Por-1, Por-2, ..., and the porosity data for crack zones are numbered similarly. Permeability data for crack zones of different fracture bodies are statistically analyzed, numbered Perm-1, Perm-2, ..., and so on. Different fracture bodies are analyzed sequentially. For both fracture zones and crack zones, the maximum, minimum, average, median, variance, standard deviation, porosity-permeability correlation, and the relationship between physical property magnitude and distance from the fault are comprehensively analyzed. Finally, various parameters or correlations are visualized using histograms, line graphs, graphs, box plots, etc. The magnitude and characteristics of the physical properties of the modified bedrock in fracture zones and crack zones, and their relationship with the fault, are determined, forming quantitative knowledge.

[0063] The fracture characterization and bedrock physical property characterization of the fracture zone are the same as those of the fracture zone, and will not be repeated here.

[0064] In some implementations, step 4 may include the following sub-steps: Step 401: Extract the corresponding second local profile image of the current fracture zone from the first local profile image based on the identified structural combination and geometry; Step 402: Based on the dissection and analysis of the second local profile image, identify each fault, cavity, and fracture in the current fracture zone, and determine: the fault nature of each fault, the filling characteristics of each cavity, and the background lithofacies and filling characteristics of each fracture. Step 403: Determine the third-scale characterization measurements of different locations of each fault, cavity, and fracture according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and Step 404: Obtain the bedrock porosity and permeability measured from the rock sample taken at the corresponding location of the current fracture zone as the bedrock physical property characterization of the current fracture zone.

[0065] In some implementations, step 5 may include the following sub-steps: Step 501: Extract the corresponding third local profile image of the current fracture zone from the first local profile image based on the identified structural combination and geometry; Step 502: Based on the dissection and analysis of the third local profile image, identify the background lithofacies, filling characteristics and each fracture of the current fracture zone; Step 503: Determine the third-scale measurement values ​​for different parts of each crack according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and Step 504: Obtain the bedrock porosity and permeability measured from the rock sample taken at the corresponding location of the current fracture zone as the bedrock physical property characterization of the current fracture zone.

[0066] In step 6, the data obtained from the first-scale representation, second-scale representation, and third-scale representation are combined to obtain a dataset of multi-scale representation data, the storage structure of which is as follows: Figure 4 As shown, the storage structure of the statistical data set obtained from multi-scale representation data is as follows: Figure 5 As shown, the heat map of the fracture dip angle parameter in the statistical data set is as follows: Figure 6 As shown, the rose diagram of the fracture dip angle parameter in the statistical data set is as follows: Figure 7 As shown.

[0067] In some implementations, the multi-scale characterization method may further include the following steps: Step 7: Obtain imaging logging data of the near-surface and subsurface portions of geological outcrops within the target area; Step 8: Based on the interpretation results of the imaging logging data, identify the first-scale, second-scale, and third-scale characteristics of the near-surface and subsurface portions of each fracture body.

[0068] Specifically, step 8 includes: Step 801, Quantitative Characterization of External Contour. Based on the interpretation results of imaging logging, combined with sonic transit time and resistivity logging, the degree of fracture development is identified. The boundary between fracture development and complete absence in the formation is determined as the fracture body boundary, and the width of the fracture development is determined, which is the width of the fracture body's external contour. Information from multiple wells is statistically analyzed to obtain quantitative information on the fracture body width (mean, median, maximum, and minimum values).

[0069] Step 802, Quantitative Characterization of Internal Structure. Based on the identification of the external contour of the fracture body, the internal structure of the fracture body is identified. First, the fracture zone of the fracture body is identified, and the area from the periphery of the fracture zone to the boundary of the fracture body is the fracture zone. Determining that the fracture density gradually decreases in the formation, and that there is no significant leakage of drilling fluid during actual drilling, the boundary of the fracture zone is defined, and the width of the fracture zone is calculated. The width of the fracture zone is the difference between the width of the external contour of the fracture body and the width of the fracture zone. Information from multiple wells is statistically analyzed to obtain quantitative information (mean, median, maximum, and minimum) on the width of the fracture zone and fracture segments of the fracture body.

[0070] Step 803, quantitative characterization of structural elements. Imaging logging mainly identifies the characterization parameters of faults and fractures in fractured bodies.

[0071] Quantitative fault characterization includes: imaging logging can identify the dip angle of faults. The most developed fracture zone is the location of fault development. The dip angle of the fault is calculated through imaging logging, and the characterization parameters of the fault dip angle (mean, median, maximum, and minimum values) are obtained.

[0072] Quantitative characterization of fractures includes obtaining fracture characterization parameters for fracture zones and fracture zones based on imaging logging information, including fracture orientation (T), dip angle (I), aperture (Ape), and density (D), and obtaining the average, median, maximum, and minimum values ​​of each characterization parameter.

[0073] Step 804 involves combining and analyzing the quantitative data of the three parts—external contour, internal structure, and structural elements—to form a digital model of the fractured body based on imaging logging identification, such as... Figure 8 As shown.

[0074] Digital models of fracture bodies identified by imaging logging can include the average, median, maximum, and minimum values ​​of several characterization parameters, such as fracture body width, fracture zone and fracture zone width, fault dip angle, fracture direction (T), dip angle (I), aperture (Ape), and density (D). This provides model guidance and data support for reservoir description, and guides the quantitative characterization and prediction of fracture bodies of different grades and types in adjacent wells.

[0075] Compared with the prior art, the technical advantages of this embodiment are as follows: Targeting fractured bodies within a strike-slip fault development context, this study selects typical fractured body outcrops and, guided by fractured body geological models, employs a hierarchical classification and nested approach to conduct qualitative and quantitative characterization of fractured bodies at three levels: external contour, internal structure, and structural elements. For each of these three levels, manual measurement and high-precision UAV scanning are used to acquire comprehensive, detailed outcrop information at different scales. Information is classified and analyzed according to type and level, summarizing and quantitatively characterizing the geological information of the fractured bodies. Combining the analysis of outcrop profile images and imaging logging data to obtain multi-scale characterization data of the aboveground and subsurface parts of the fractured bodies enables more accurate characterization. The study analyzes fractured bodies formed by faults of different types, such as those formed by extensional, compressional, and shear faults. This study analyzes the cross-sectional shape, perimeter, area, width, and height of fracture bodies controlled by each type of fault, and statistically analyzes the distribution range of these parameters for each type of fracture body. This provides a reference for the study of the external contour of underground fracture bodies, guides the calculation of their spatial volume, and ultimately forms qualitative and quantitative geological knowledge of different types of fracture bodies, guiding comprehensive research on underground fracture bodies. It also statistically analyzes the basic information and characterization parameters of fracture zones and crack zones, obtaining qualitative information on structural combinations and geometric shapes, and quantitative information on width, height, perimeter, and area. The distribution range of these parameters is statistically analyzed, providing qualitative models and quantitative parameters for the study of the internal structure of underground fracture bodies. Furthermore, it statistically analyzes the structural elements of fracture zones and crack zones, including qualitative and quantitative information on faults, cavities, cracks, and altered bedrock properties in fracture zones, and qualitative and quantitative information on cracks and bedrock properties in crack zones. The maximum, minimum, average, median, variance, and standard deviation of the quantitative information are statistically analyzed. This summarizes a quantitative geological model for fracture bodies, guiding the study of the complexity of their internal structures and the heterogeneity of underground fracture bodies, thus improving the reliability and accuracy of reservoir characterization. This invention provides a multi-scale characterization method for fracture bodies based on geological outcrops. First, a multi-scale characterization model is established according to the multi-scale characterization method of the previous embodiment. Then, the multi-scale characterization data of the fracture body is predicted based on the trained multi-scale characterization model. This multi-scale characterization method includes: Based on the multi-scale characterization method of this application, multi-scale characterization data of geological outcrops in the target area are determined, and training and test datasets are constructed. A multi-scale representation model is trained using a training dataset and validated using test data; and Based on the validated multi-scale characterization model, predict the multi-scale characterization data of uncharacterized underground fracture bodies within the target area.

[0076] Specifically, the multi-scale representation model may include a first prediction model, a second prediction model, and a third prediction model, which are used to predict the first-scale representation, the second-scale representation, and the third-scale representation, respectively. The input data for the first prediction model are the external contour data of the geological outcrop and the geometry of the fracture body profile, and the output is the first-scale representation. The input data for the second prediction model are the structural combination of the fracture zone profile, the geometry of the fracture zone profile, the geometry of the fracture zone profile, and the first-scale representation, and the output is the second-scale representation. The input data for the third prediction model are fault properties, cavity filling characteristics, background lithofacies of fractures, filling characteristics and second characterization parameters, and the output is a third-scale characterization.

[0077] Compared with the prior art, the technical advantage of this embodiment is that it combines the quantitative data of the three parts of external contour, internal structure and structural elements to construct training dataset and test dataset and train a multi-scale representation model, which provides pattern guidance and data support for reservoir description and guides the quantitative representation and prediction of different levels and different fracture bodies in adjacent wells.

[0078] This invention provides a reservoir identification method, comprising: Based on the multi-scale characterization method of this application, multi-scale characterization data of multiple geological outcrops within the target area are determined; Obtain reservoir identification results for fractured bodies at multiple geological outcrop locations; By combining multi-scale characterization data and reservoir identification results, training and testing datasets are constructed. A reservoir identification model was trained using a training dataset, and the model was validated using test data; and Based on the validated reservoir identification model, predict whether fracture bodies in or around the target area are usable reservoirs.

[0079] This invention provides a multi-scale characterization device, such as... Figure 9 As shown, it includes: an image acquisition module and a multi-scale measurement module. The image acquisition module is used to acquire profile images of geological outcrops within the target area. The multi-scale measurement module is configured to: determine one or more fracture bodies distributed in the geological outcrops from the profile images; measure the first-scale characterization of each fracture body; determine a corresponding first local profile image for each fracture body; extract the fracture zone and breccia zone that make up the corresponding fracture body from the local profile image; measure the second-scale characterization of the fracture zone and breccia zone; determine a corresponding second local profile image for each breccia zone; determine the fault characterization, cavity characterization, fracture characterization, and bedrock physical property characterization of the corresponding breccia zone based on the second local profile image; determine a corresponding third local profile image for each fracture zone; determine the fracture characterization and bedrock physical property characterization of the corresponding fracture zone based on the third local profile image; and use the fault characterization, cavity characterization, fracture characterization, and bedrock physical property characterization as the third-scale characterization of the fracture body.

[0080] In some implementations, the first scale characterization includes the geometry of the fracture body profile and a first characterization parameter, which includes one or more of the following: measurement, statistical value, and / or correlation coefficient: width, height, perimeter, area.

[0081] In some embodiments, the second-scale characterization of the fracture zone includes the structural combination of the fracture zone profile, the geometry, and a second characterization parameter, the second characterization parameter including one or more of the following measured values, statistical values, and / or correlation coefficients: width, height, perimeter, area; the second-scale characterization of the fracture zone includes the geometry of the fracture zone profile and a third characterization parameter, the second characterization parameter including one or more of the following measured values, statistical values, and / or correlation coefficients: width, height, perimeter, area.

[0082] In some embodiments, fault characterization includes fault properties and a fourth characterization parameter, which includes measurements, statistics, and / or correlation coefficients of one or more of the following: strike, dip, height, and length; cavity characterization includes filling characteristics and a fifth characterization parameter, which includes measurements, statistics, and / or correlation coefficients of one or more of the following: strike, dip, height, and width; fracture characterization includes background lithofacies, filling characteristics, and a sixth characterization parameter, which includes measurements, statistics, and / or correlation coefficients of one or more of the following: strike, dip, height, aperture, and density; bedrock physical property characterization includes measurements, statistics, and / or correlation coefficients of sandstone porosity and permeability.

[0083] In some implementations, the image acquisition module is configured to: acquire original profile images of the geological outcrop from multiple angles using an image acquisition device; process the original profile images into point clouds and perform three-dimensional registration of the point clouds to obtain a registered point cloud model; construct a white body model of a TIN network based on the registered point cloud model; and project the dissection and analysis of the acquired original profile images from multiple angles onto the white body model to obtain a measurable three-dimensional model of the geological outcrop and profile images from multiple angles.

[0084] In some implementations, the multi-scale measurement module is further configured to: identify the external contours of fracture bodies distributed in geological outcrops based on three-dimensional models and profile images; determine the number of each identified fracture body; and determine the measurement values ​​of the first-scale characterization of different parts of each fracture body in a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left.

[0085] In some implementations, the multi-scale measurement module is further configured to: extract a first local cross-sectional image corresponding to the current fracture body from the cross-sectional image based on the identified external contour; identify the structural combination and geometry of the current fracture body based on the dissection and analysis of the first local cross-sectional image, wherein the structural combination is a single-core structural combination or a multi-core structural combination, and the geometry is conical, spindle-shaped, or cylindrical; and determine the measurement values ​​of the second-scale characterization of different parts of each fracture zone or break zone in a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left.

[0086] In some implementations, the multi-scale measurement module is further configured to: extract a second local profile image corresponding to the current fracture zone from the first local profile image based on the identified structural combination and geometry; identify each fault, cavity, and fracture in the current fracture zone based on the dissection and analysis of the second local profile image, and determine: the fault nature of each fault, the filling characteristics of each cavity, and the background lithofacies and filling characteristics of each fracture; determine the measurement values ​​of the third-scale characterization of different parts of each fault, cavity, and fracture in a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and obtain the bedrock porosity and permeability measured from rock samples taken at the corresponding location of the current fracture zone as the bedrock physical property characterization of the current fracture zone.

[0087] In some implementations, the multi-scale measurement module is further configured to: extract a corresponding third local profile image of the current fracture zone from the first local profile image based on the identified structural combination and geometry; identify the background lithofacies, filling characteristics, and each fracture of the current fracture zone based on the dissection and analysis of the third local profile image; determine the measurement values ​​of the third-scale characterization of different parts of each fracture in a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and obtain the bedrock porosity and permeability measured from rock samples taken at the corresponding location of the current fracture zone as the bedrock physical property characterization of the current fracture zone.

[0088] In some implementations, the image acquisition module is further configured to acquire imaging logging data of the near-surface and subsurface portions of geological outcrops within the target area; the multi-scale measurement module is further configured to identify the first-scale, second-scale, and third-scale representations of the near-surface and subsurface portions of each fracture body based on the interpretation results of the imaging logging data.

[0089] This invention provides a multi-scale characterization device, which includes a processor and a memory. The image acquisition module and the multi-scale measurement module are both stored as program units in the memory, and the processor executes the program units stored in the memory to achieve the corresponding functions.

[0090] The processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and by adjusting the kernel parameters, the contour and internal structure of the fracture body within the target region can be characterized at multiple scales.

[0091] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0092] This invention provides a reservoir identification device, including a reservoir identification model and an identification module. The identification module is configured to: predict whether fracture bodies at or around a target area are usable reservoirs using the reservoir identification model. The reservoir identification model is a reservoir identification model trained on a training dataset and verified by test data. The training dataset and test dataset are derived from: multi-scale characterization data of multiple geological outcrops within the target area determined by the multi-scale characterization method of this application and reservoir identification results of fracture bodies at multiple geological outcrop locations.

[0093] This invention provides a reservoir identification device, which includes a processor and a memory. The reservoir identification model and identification module are stored in the memory as program units, and the processor executes the program units stored in the memory to achieve the corresponding functions.

[0094] The processor contains a kernel, which retrieves the corresponding program unit from memory. One or more kernels can be configured, and by adjusting the kernel parameters, the reservoir identification model can be used to predict whether fracture bodies in or around the target area are usable reservoirs.

[0095] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0096] This invention provides a storage medium storing a program that, when executed by a processor, implements the multi-scale characterization method or reservoir identification method of this application.

[0097] This invention provides a processor for running a program, wherein the program executes the multi-scale characterization method or reservoir identification method of this application.

[0098] This invention provides a device including a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of the multi-scale characterization method or reservoir identification method of this application. The device described herein can be a server, PC, PAD, mobile phone, etc.

[0099] This application also provides a computer program product that, when executed on a data processing device, is suitable for executing a program that initializes the multi-scale characterization method or reservoir identification method steps of this application.

[0100] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0101] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0102] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0103] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0104] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0105] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0106] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0107] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0108] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A multi-scale characterization method for fracture bodies based on geological outcrops, comprising: Acquire profile images of geological outcrops within the target area; Identify one or more fracture bodies distributed in the geological outcrop from the cross-sectional image, and measure the first-scale characterization of each fracture body; Determine a first local profile image corresponding to each fracture body, extract the crack zone and fracture zone that make up the corresponding fracture body from the local profile image, and measure the second-scale characterization of the crack zone and the fracture zone; Determine the corresponding second local profile image for each fracture zone, and determine the fault characterization, cavity characterization, fracture characterization and bedrock physical property characterization of the corresponding fracture zone based on the second local profile image; Determine the corresponding third local profile image for each fracture zone, and based on the third local profile image, determine the fracture characterization and bedrock physical property characterization of the corresponding fracture zone; and The fault characterization, cavity characterization, fracture characterization, and bedrock physical property characterization are used as the third-scale characterization of the fracture body.

2. The multi-scale characterization method according to claim 1, characterized in that, The first scale characterization includes the geometry of the fracture body profile and a first characterization parameter, which includes one or more of the following: measured values, statistical values, and / or correlation coefficients: width, height, perimeter, and area.

3. The multi-scale characterization method according to claim 1, characterized in that, The second-scale characterization of the fracture zone includes the structural combination of the fracture zone profile, the geometry, and a second characterization parameter, the second characterization parameter including one or more of the following: measurement value, statistical value, and / or correlation coefficient: width, height, perimeter, area; The second-scale characterization of the fracture zone includes the geometry of the fracture zone profile and a third characterization parameter, the second characterization parameter including one or more of the following measurements, statistics, and / or correlation coefficients: width, height, perimeter, and area.

4. The multi-scale characterization method according to claim 1, characterized in that, The fault characterization includes fault properties and a fourth characterization parameter, which includes one or more of the following: strike, dip, height, and length; The cavity characterization includes filling characteristics and a fifth characterization parameter, which includes one or more of the following: measurement values, statistical values, and / or correlation coefficients: orientation, tilt angle, height, and width; The fracture characterization includes background lithofacies, filling characteristics, and a sixth characterization parameter, which includes one or more of the following: strike, dip angle, height, aperture, and density. The bedrock physical property characterization includes measurements, statistical values, and / or correlation coefficients of sandstone porosity and permeability.

5. The multi-scale characterization method according to any one of claims 1 to 4, characterized in that, The acquisition of profile images of geological outcrops within the target area includes: The original profile images of the geological outcrop were acquired from multiple angles using image acquisition equipment; The original cross-sectional image is processed into a point cloud and then three-dimensional registration of the point cloud is performed to obtain a registered point cloud model. A white body model of a TIN network is constructed based on the registered point cloud model. The textures of the original cross-sectional images collected from multiple angles are projected onto the white body model to obtain a measurable three-dimensional model of the geological outcrop and cross-sectional images from multiple angles.

6. The multi-scale characterization method according to claim 5, characterized in that, The step of determining one or more fracture bodies distributed in the geological outcrop from the profile image, and measuring a first-scale characterization of each fracture body, includes: Based on the three-dimensional model and the cross-sectional image, the external contours of the fracture bodies distributed in the geological outcrops are identified; and Each identified fracture body is assigned a number, and the first-scale characterization measurements of different parts of each fracture body are determined according to a preset direction. The preset direction is from top to bottom, from left to right, from bottom to top, or from right to left.

7. The multi-scale characterization method according to claim 6, characterized in that, The process of determining a first local cross-sectional image corresponding to each fracture body, extracting the crack zone and fracture zone that make up the corresponding fracture body from the local cross-sectional image, and measuring the second-scale characterization of the crack zone and the fracture zone includes: Extract the first local cross-sectional image corresponding to the current fracture body from the cross-sectional image based on the identified external contour; Based on the dissection and analysis of the first partial cross-sectional image, the structural combination and geometric shape of the current fracture body are identified, wherein the structural combination is a single-core structural combination or a multi-core structural combination, and the geometric shape is conical, spindle-shaped, or cylindrical, etc. The second-scale characterization measurement values ​​of different parts of each crack zone or fracture zone are determined according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left.

8. The multi-scale characterization method according to claim 7, characterized in that, The step of determining the corresponding second local profile image for each fracture zone, and determining the fault characterization, cavity characterization, fracture characterization, and bedrock physical property characterization of the corresponding fracture zone based on the second local profile image, includes: Based on the identified structural combinations and geometric shapes, extract the corresponding second local profile image of the current fracture zone from the first local profile image; Based on the dissection and analysis of the second local profile image, each fault, cavity, and fracture in the current fracture zone is identified, and the following are determined: the fault nature of each fault, the filling characteristics of each cavity, and the background lithofacies and filling characteristics of each fracture. The measurements representing the third scale of different locations of each fault, cavity, and fracture are determined according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and The porosity and permeability of the bedrock obtained from rock samples at the corresponding location of the current fracture zone are used as the physical properties characterization of the bedrock of the current fracture zone.

9. The multi-scale characterization method according to claim 7 or 8, characterized in that, The process of determining the corresponding third local profile image for each fracture zone, and determining the fracture characterization and bedrock physical property characterization of the corresponding fracture zone based on the third local profile image, includes: Based on the identified structural combinations and geometric shapes, extract the corresponding third local profile image of the current fracture zone from the first local profile image; Based on the dissection and analysis of the third local profile image, the background lithofacies, filling characteristics, and each fracture of the current fracture zone are identified; The measurement values ​​representing the third scale of different parts of each crack are determined according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and The porosity and permeability of the bedrock obtained from rock samples at the corresponding locations of the current fracture zone are used as the physical properties characterization of the bedrock of the current fracture zone.

10. The multi-scale characterization method according to claim 1, characterized in that, Also includes: Acquire imaging logging data of the near-surface and subsurface portions of geological outcrops within the target area; Based on the interpretation results of the imaging logging data, the first-scale, second-scale, and third-scale characteristics of the near-surface and subsurface portions of each fracture body are identified.

11. A multi-scale characterization method for fracture bodies based on geological outcrops, comprising: According to any one of claims 1 to 10, the multi-scale characterization method determines the multi-scale characterization data of geological outcrops within the target area, and constructs a training dataset and a test dataset; A multi-scale representation model is trained using the training dataset, and the multi-scale representation model is validated using the test data. as well as Based on the validated multi-scale characterization model, multi-scale characterization data of underground fracture bodies within the target area are predicted to guide the quantitative characterization and prediction of underground fracture bodies.

12. The multi-scale characterization method according to claim 10, characterized in that, The multi-scale representation model includes a first prediction model, a second prediction model, and a third prediction model, which are used to predict the first-scale representation, the second-scale representation, and the third-scale representation, respectively. The input data of the first prediction model are the external contour data of the geological outcrop and the geometry of the fracture body profile, and the output is the first scale representation. The input data for the second prediction model are the structural combination of the fracture zone profile, the geometry of the fracture zone profile, the geometry of the crack zone profile, and the first-scale representation, and the output is the second-scale representation. The input data for the third prediction model are fault properties, cavity filling characteristics, background lithofacies of fractures, filling characteristics and second characterization parameters, and the output is the third-scale characterization.

13. A reservoir identification method, comprising: According to any one of claims 1 to 10, the multi-scale characterization method is used to determine multi-scale characterization data of multiple geological outcrops within the target area; Obtain reservoir identification results for fracture bodies at the multiple geological outcrop locations; By combining the multi-scale characterization data and the reservoir identification results, a training dataset and a test dataset are constructed. The reservoir identification model is trained using the training dataset, and the reservoir identification model is verified using the test data. as well as Based on the validated reservoir identification model, predict whether the fractured body in or around the target area is a usable reservoir.

14. A multi-scale characterization device for fracture bodies based on geological outcrops, characterized in that, include: Image acquisition module and multi-scale measurement module, The image acquisition module is used to acquire profile images of geological outcrops within the target area; The multi-scale measurement module is configured as follows: Identify one or more fracture bodies distributed in the geological outcrop from the cross-sectional image, and measure the first-scale characterization of each fracture body; Determine a first local profile image corresponding to each fracture body, extract the crack zone and fracture zone that make up the corresponding fracture body from the local profile image, and measure the second-scale characterization of the crack zone and the fracture zone; Determine the corresponding second local profile image for each fracture zone, and determine the fault characterization, cavity characterization, fracture characterization and bedrock physical property characterization of the corresponding fracture zone based on the second local profile image; Determine the corresponding third local profile image for each fracture zone, and based on the third local profile image, determine the fracture characterization and bedrock physical property characterization of the corresponding fracture zone; and The fault characterization, cavity characterization, fracture characterization, and bedrock physical property characterization are used as the third-scale characterization of the fracture body.

15. The multi-scale characterization device according to claim 14, characterized in that, The first scale characterization includes the geometry of the fracture body profile and a first characterization parameter, which includes one or more of the following: measured values, statistical values, and / or correlation coefficients: width, height, perimeter, and area.

16. The multi-scale characterization device according to claim 14, characterized in that, The second-scale characterization of the fracture zone includes the structural combination of the fracture zone profile, the geometry, and a second characterization parameter, the second characterization parameter including one or more of the following: measurement value, statistical value, and / or correlation coefficient: width, height, perimeter, area; The second-scale characterization of the fracture zone includes the geometry of the fracture zone profile and a third characterization parameter, the second characterization parameter including one or more of the following measurements, statistics, and / or correlation coefficients: width, height, perimeter, and area.

17. The multi-scale characterization device according to claim 14, characterized in that, The fault characterization includes fault properties and a fourth characterization parameter, which includes one or more of the following: strike, dip, height, and length; The cavity characterization includes filling characteristics and a fifth characterization parameter, which includes one or more of the following: measurement values, statistical values, and / or correlation coefficients: orientation, tilt angle, height, and width; The fracture characterization includes background lithofacies, filling characteristics, and a sixth characterization parameter, which includes one or more of the following: strike, dip angle, height, aperture, and density. The bedrock physical property characterization includes measurements, statistical values, and / or correlation coefficients of sandstone porosity and permeability.

18. The multi-scale characterization apparatus according to any one of claims 14 to 17, characterized in that, The image acquisition module is configured as follows: The original profile images of the geological outcrop were acquired from multiple angles using image acquisition equipment; The original cross-sectional image is processed into a point cloud and then three-dimensional registration of the point cloud is performed to obtain a registered point cloud model. A white body model of a TIN network is constructed based on the registered point cloud model. The textures of the original cross-sectional images collected from multiple angles are projected onto the white body model to obtain a measurable three-dimensional model of the geological outcrop and cross-sectional images from multiple angles.

19. The multi-scale characterization device according to claim 18, characterized in that, The multi-scale measurement module is also configured to: Based on the three-dimensional model and the cross-sectional image, the external contours of the fracture bodies distributed in the geological outcrops are identified; and Each identified fracture body is assigned a number, and the first-scale characterization measurements of different parts of each fracture body are determined according to a preset direction. The preset direction is from top to bottom, from left to right, from bottom to top, or from right to left.

20. The multi-scale characterization device according to claim 19, characterized in that, The multi-scale measurement module is also configured to: Extract the first local cross-sectional image corresponding to the current fracture body from the cross-sectional image based on the identified external contour; Based on the dissection and analysis of the first local cross-sectional image, the structural combination and geometric shape of the current fracture body are identified, wherein the structural combination is a single-core structural combination or a multi-core structural combination, and the geometric shape is conical, spindle-shaped, or cylindrical. and The second-scale characterization measurement values ​​of different parts of each crack zone or fracture zone are determined according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left.

21. The multi-scale characterization device according to claim 20, characterized in that, The multi-scale measurement module is also configured to: Based on the identified structural combinations and geometric shapes, extract the corresponding second local profile image of the current fracture zone from the first local profile image; Based on the dissection and analysis of the second local profile image, each fault, cavity, and fracture in the current fracture zone is identified, and the following are determined: the fault nature of each fault, the filling characteristics of each cavity, and the background lithofacies and filling characteristics of each fracture. The measurements representing the third scale of different locations of each fault, cavity, and fracture are determined according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and The porosity and permeability of the bedrock obtained from rock samples at the corresponding location of the current fracture zone are used as the physical properties characterization of the bedrock of the current fracture zone.

22. The multi-scale characterization device according to claim 20 or 21, characterized in that, The multi-scale measurement module is also configured to: Based on the identified structural combinations and geometric shapes, extract the corresponding third local profile image of the current fracture zone from the first local profile image; Based on the dissection and analysis of the third local profile image, the background lithofacies, filling characteristics, and each fracture of the current fracture zone are identified; The measurement values ​​representing the third scale of different parts of each crack are determined according to a preset direction, wherein the preset direction is from top to bottom, from left to right, from bottom to top, or from right to left; and The porosity and permeability of the bedrock obtained from rock samples at the corresponding locations of the current fracture zone are used as the physical properties characterization of the bedrock of the current fracture zone.

23. The multi-scale characterization device according to claim 14, characterized in that, The image acquisition module is also configured to acquire imaging logging data of the near-surface and subsurface portions of geological outcrops within the target area; The multi-scale measurement module is also configured to: identify the first-scale characterization, second-scale characterization, and third-scale characterization of the near-surface and subsurface portions of each fracture body based on the interpretation results of the imaging logging data.

24. A multi-scale characterization device for fracture bodies based on geological outcrops, characterized in that, include: Multi-scale representation model and prediction module, The training dataset and test dataset used to train the multi-scale representation model are derived from the multi-scale representation data of geological outcrops within the target area determined by the multi-scale representation method according to any one of claims 1 to 10, wherein the training dataset is used to train the multi-scale representation model and the test data is used to verify the multi-scale representation model. The prediction module is configured to predict multi-scale characterization data of underground fracture bodies within the target area based on a validated multi-scale characterization model, thereby guiding the quantitative characterization and prediction of underground fracture bodies.

25. The multi-scale characterization device according to claim 24, characterized in that, The multi-scale representation model includes a first prediction model, a second prediction model, and a third prediction model, which are used to predict the first-scale representation, the second-scale representation, and the third-scale representation, respectively. The input data of the first prediction model are the external contour data of the geological outcrop and the geometry of the fracture body profile, and the output is the first scale representation. The input data for the second prediction model are the structural combination of the fracture zone profile, the geometry of the fracture zone profile, the geometry of the crack zone profile, and the first-scale representation, and the output is the second-scale representation. The input data for the third prediction model are fault properties, cavity filling characteristics, background lithofacies of fractures, filling characteristics and second characterization parameters, and the output is the third-scale characterization.

26. A reservoir identification device, characterized in that, Includes reservoir identification models and identification modules. The identification module is configured to: predict whether a fractured body in or around the target area is a usable reservoir using the reservoir identification model; The reservoir identification model is a reservoir identification model trained on a training dataset and verified by test data, wherein the data in the training dataset and the test dataset are derived from: multi-scale characterization data of multiple geological outcrops in the target area determined by the multi-scale characterization method according to any one of claims 1 to 10 and reservoir identification results of fracture bodies at the locations of the multiple geological outcrops.

27. A processor, characterized in that, It is configured to: perform the multi-scale characterization method according to any one of claims 1 to 12, or perform the reservoir identification method according to claim 13.

28. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by a processor, this instruction causes the processor to be configured to: perform the multi-scale characterization method according to any one of claims 1 to 12, or perform the reservoir identification method according to claim 13.

29. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the multi-scale characterization method according to any one of claims 1 to 12, or the reservoir identification method according to claim 13.

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