Method for detecting fracture networks in unconventional reservoirs based on full-diameter core CT scanning

Abstract

The present invention discloses a method for detecting the fracture network of unconventional reservoirs based on full-diameter core CT scanning. This method for detecting the fracture network of unconventional reservoirs based on full-diameter core CT scanning utilizes digital quantitative CT non-destructive testing technology, combines deep learning to extract the three-dimensional fracture network of the full-diameter core, and accurately judges the artificial fracture network and fracturing effect of the full-diameter core through artificial intelligence comparison of the three-dimensional fracture networks of the full-diameter core before and after fracturing. It provides quantitative three-dimensional spatial fracture network data for unconventional oil and gas exploration and development, optimizes the "sweet spots" for unconventional oil and gas exploration and development, improves the accuracy of evaluating favorable target areas for unconventional oil and gas exploration and development, improves the efficiency of unconventional oil and gas reservoir exploration and development, and reduces the cost of unconventional oil and gas reservoir exploration and development.

Description

Technical Field

[0001] The present invention belongs to the technical field of unconventional oil and gas exploration, development engineering design and application, and particularly relates to a method for detecting fracture networks in unconventional reservoirs based on full-diameter core CT scanning. Background Art

[0002] The detection of three-dimensional fracture networks in unconventional reservoir fracturing has always been a world-class top technical problem that has long been in need of solution but has not been fundamentally solved in oil and gas exploration and development engineering. Due to the limitations of the technical principles of current imaging logging and microseismic with low resolution, it is impossible to intuitively and effectively obtain the artificial fracture development network in unconventional reservoirs thousands of meters underground, and it is impossible to fully grasp the development status of artificial fractures in unconventional reservoirs, resulting in the inability to obtain technical guarantees for subsequent evaluation of artificial fracturing effects, design and implementation of development plans. With the emergence of CT non-destructive testing technology, combined with machine learning, deep learning and artificial intelligence simulation technology, it provides a new technical guarantee for the detection of artificial fracture networks in unconventional reservoirs. As oil and gas exploration deepens, the areas available for exploration of conventional oil and gas are becoming fewer and fewer, and it is becoming more and more difficult to make new discoveries. Therefore, unconventional oil and gas exploration has gradually become the focus of current and future exploration, and the difficulty of artificial fracturing of reservoirs will also gradually increase. The artificial fracturing transformation of unconventional reservoirs is the cornerstone of the exploration effect and benefit of unconventional oil and gas, and is one of the core contents in the drilling engineering of unconventional oil and gas wells.

[0003] Existing imaging logging and microseismic have low resolution and cannot accurately and effectively reveal the true state of the three-dimensional fracture network of artificial fracturing in unconventional reservoirs, resulting in the inability to control whether the effect of artificial fracturing in unconventional reservoirs meets the expected design requirements, the inability to effectively implement the design requirements, and the unknowability of how to transform the "sweet spots" of oil and gas enrichment, resulting in low success rate and efficiency in unconventional oil and gas exploration.

[0004] There is an urgent need to develop a new method for detecting three-dimensional fracture networks in unconventional reservoir fracturing based on full-diameter core CT scanning, which can accurately characterize the development degree and differences of natural fractures in each sub-section of the cored interval, the three-dimensional fracture network of artificial fractures and their differences, evaluate the control effect of natural fractures on the three-dimensional fracture network of artificial fractures and the artificial fracturing effect, optimize excellent fracturing intervals, provide technical information for fine exploration of unconventional oil and gas and design of development plans, which is not only conducive to controlling the success rate of exploration of "sweet spots" of oil and gas enrichment, but also better guiding the in-depth exploration of unconventional oil and gas, improving exploration efficiency and fine development benefits, and reducing risks. Summary of the Invention

[0005] The object of the present invention is to overcome the deficiencies of the above-mentioned background technology, and provide a method for detecting the fracture network of unconventional reservoirs based on full-diameter core CT scanning, so as to accurately evaluate the development degree and differences of natural fractures in each sub-section of the cored section, the three-dimensional fracture network of artificial fracturing fractures and their differences, evaluate the control effect of natural fractures on the three-dimensional fracture network of artificial fracturing fractures and the artificial fracturing effect, optimize excellent fracturing sections, improve the monitoring level of the fracturing transformation effect of unconventional oil and gas exploration reservoirs and the efficiency of oil and gas exploration, and reduce the costs of oil and gas exploration and development.

[0006] To solve the above technical problems, the present invention is realized through the following technical solutions:

[0007] A method for detecting the fracture network of unconventional reservoirs based on full-diameter core CT scanning includes the following steps:

[0008] S1. Based on the geological background of unconventional oil and gas, obtain the rock types, burial depths, formation pressures, and core fracture network detection requirements of unconventional reservoirs. Based on the drilling methods and well types in drilling geology and engineering design, and the requirements for core pressure and shape preservation, confirm the types and models of the core pressure and shape preservation sleeves before and after fracturing;

[0009] S2. Adopt the full-diameter core CT scanning method to perform systematic CT scanning on the core before fracturing, collect the natural fracture data of the core, and establish a natural fracture grayscale model; through machine learning recognition of the established natural fracture grayscale model, establish a three-dimensional network model of the development of natural fractures;

[0010] S3. Adopt the full-diameter core CT scanning method to perform systematic CT scanning on the core after artificial fracturing, collect the natural and artificial fracturing fracture data of the core, and establish a natural and artificial fracturing fracture grayscale model; through machine learning recognition of the established natural and artificial fracturing fracture grayscale model, establish a mixed network three-dimensional model of the development of natural and artificial fracturing fractures;

[0011] S4. Adopt the deep learning method to perform deep learning recognition on the three-dimensional network model established in step S2 and the mixed network three-dimensional model established in step S3, establish a three-dimensional fracture network model of the deep learning training core before and after fracturing, and then establish a three-dimensional fracture network model of the deep learning of the core before and after fracturing in the entire cored section;

[0012] S5. Adopt the artificial intelligence recognition method to perform intelligent recognition and judgment on the three-dimensional fracture network model of the deep learning established in step S4, so as to extract the net artificial fracturing fracture three-dimensional network model after removing natural fractures after core fracturing, and then characterize the development degree and differences of natural fractures in each sub-section of the cored section, the three-dimensional fracture network of artificial fracturing fractures and their differences, evaluate the control effect of natural fractures on the three-dimensional fracture network of artificial fracturing fractures and the artificial fracturing effect, and optimize excellent fracturing sections.

[0013] Preferably, in the step S1, the selection criteria for the type and model of the coring pressure and shape preservation sleeve for the three-dimensional fracture network detection of unconventional reservoir fracturing based on full-diameter core CT scanning are as follows: The type and model of the pressure and shape preservation sleeve selected based on the unconventional rock type should protect the core from secondary changes during the coring process.

[0014] More preferably, the secondary changes include the generation of secondary fractures.

[0015] More preferably, in the step S1, the type and model of the pressure and shape preservation sleeve selected based on the unconventional rock type should reduce the shielding effect of the metal sleeve on the penetration of X-rays.

[0016] Even more preferably, in the step S1, based on the selected sleeve model and the compactness of the core, the selection criteria for the ray source current and voltage are as follows: The level of the current and voltage should penetrate the sleeve and the rock to obtain the rock fractures and their spatial fracture networks.

[0017] Preferably, in the steps S2 and S3, the selection criteria for the cores before and after the three-dimensional fracture network detection of unconventional reservoir fracturing based on full-diameter core CT scanning are as follows: Cores drilled from the same well and the same target layer or cores drilled from adjacent wells and the same target layer are selected to ensure the consistency of the natural fracture development of the cores.

[0018] Preferably, in the steps S2 and S3, the size or identification criteria of the gray values of natural and artificial fracturing fractures can effectively identify and distinguish natural fractures and networks, artificial fracturing fractures and networks.

[0019] Preferably, in the step S4, the size of the CT gray value of the natural fractures of the core in the three-dimensional fracture network detection of unconventional reservoir fracturing by full-diameter core CT scanning can effectively identify the natural fractures and their spatial distribution networks, and establish a three-dimensional spatial fracture network model of the natural fractures of the core in the cored section.

[0020] More preferably, in the step S4, the size of the CT gray value of the artificial fracturing fractures of the core in the three-dimensional fracture network detection of unconventional reservoir fracturing by full-diameter core CT scanning can effectively distinguish the artificial fracturing fractures and their spatial distribution networks from the natural fractures and their spatial distribution networks, and establish a three-dimensional spatial fracture network model of the artificial fracturing fractures of the core in the cored section.

[0021] Even more preferably, in the step S4, establish the artificial fracturing fractures and networks controlled by the natural fractures and their networks of the core, clarify the control mechanism of the natural fractures of the core on the artificial fracture network, and provide technical information for the direction, method and pressure magnitude of artificial fracturing in unconventional reservoirs.

[0022] The unconventional reservoir fracture network detection method based on full-diameter core CT scanning provided by the present invention uses CT non-destructive testing technology and the gray-scale quantitative index of fracture development, and through machine learning, deep learning and artificial intelligence simulation, it identifies natural fractures, artificial fracturing fractures and their identification criteria, accurately evaluates the development degree and differences of natural fractures in each sub-section of the cored section, the three-dimensional fracture network of artificial fracturing fractures and their differences, evaluates the control effect of natural fractures on the three-dimensional fracture network of artificial fracturing fractures and the artificial fracturing effect, optimizes excellent fracturing sections, improves the monitoring level of the fracturing transformation effect of unconventional oil and gas exploration reservoirs and the efficiency of oil and gas exploration, and reduces the costs of oil and gas exploration and development.

[0023] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0024] 1) It fills the quantitative evaluation method for the detection of three-dimensional fracture networks in unconventional reservoir fracturing. By using the quantitative indexes of the development network of natural and artificial fracturing fractures in unconventional reservoirs collected by CT scanning and their gray-scale spatial changes, and with the help of machine learning, deep learning and artificial intelligence simulation, it accurately evaluates natural fractures, artificial fracturing fractures and their changes in unconventional reservoirs, providing more effective technical information for unconventional oil and gas exploration and development;

[0025] 2) It improves the efficiency of oil and gas exploration and drilling and reduces costs. The present invention uses CT non-destructive testing technology, applies machine learning and deep learning methods to establish the identification of natural fractures, artificial fracturing fractures and their identification and evaluation indexes, establishes the identification methods and technical standards for natural fractures, artificial fracturing fractures and their identification and evaluation under the geological conditions of this region, uses artificial intelligence simulation to accurately evaluate the development degree and differences of natural fractures in each sub-section of the cored section, the three-dimensional fracture network of artificial fracturing fractures and their differences, evaluates the control effect of natural fractures on the three-dimensional fracture network of artificial fracturing fractures and the artificial fracturing effect, improves the fracturing transformation effect of the drilling in the "sweet spot" section of the target layer, improves the drilling efficiency of unconventional oil and gas exploration, and reduces the costs of unconventional oil and gas exploration and development. Specific embodiments

[0026] In order to better explain the present invention, the following will be described in detail with reference to specific embodiments.

[0027] The unconventional reservoir fracture network detection method based on full-diameter core CT scanning of the present invention includes the following steps:

[0028] YL110: Based on the unconventional oil and gas geological background, obtain the rock type, burial depth, formation pressure, and core fracture network detection requirements of the unconventional reservoir. Based on the drilling methods and well types in the drilling geology and engineering design, and the requirements for core pressure and shape preservation, confirm the types and models of the core pressure and shape preservation sleeves before and after fracturing;

[0029] Furthermore, the selection criteria for the type and model of the coring pressure and shape preservation sleeve before and after fracturing for the three-dimensional fracture network detection of unconventional reservoirs based on full-diameter core CT scanning are as follows: The type and model of the pressure and shape preservation sleeve selected based on unconventional rock types must well protect the core from secondary changes during the coring process, especially the generation of secondary fractures.

[0030] Furthermore, the type and model of the pressure and shape preservation sleeve selected based on unconventional rock types must minimize the shielding effect of the metal sleeve on X-ray penetration to the greatest extent possible.

[0031] Furthermore, based on the selected sleeve model and the compactness of the core, the criteria for selecting the ray source current and voltage are as follows: The level of the current and voltage must be appropriate to effectively penetrate the sleeve and the rock and well obtain the rock fractures and their spatial fracture networks.

[0032] YL120: Using the full-diameter core CT scanning method, systematically scan the core before fracturing by CT, collect the natural fracture data of the core, and establish a natural fracture CT gray scale model. Through machine learning recognition based on the established natural fracture gray scale model, establish a three-dimensional network model of the development of natural fractures.

[0033] Furthermore, the selection criteria for the core before and after fracturing for the three-dimensional fracture network detection of unconventional reservoirs based on full-diameter core CT scanning are as follows: Cores drilled from the same well and the same target layer or cores drilled from adjacent wells and the same target layer should ensure good consistency in the development of natural fractures in the core.

[0034] Furthermore, the size or recognition criteria of the CT gray scale values of natural and artificial fracturing fractures can effectively identify and distinguish natural fractures and networks, artificial fracturing fractures and networks.

[0035] YL130: According to the full-diameter core CT scanning method, systematically scan the core after artificial fracturing by CT, collect the natural and artificial fracturing fracture data of the core, and establish a natural and artificial fracturing fracture CT gray scale model. Through machine learning recognition based on the established natural and artificial fracturing fracture gray scale model, establish a mixed network three-dimensional model of the development of natural and artificial fracturing fractures.

[0036] YL140: Using the deep learning method, conduct deep learning recognition on the three-dimensional fracture network models established before and after core fracturing, establish a deep learning training core fracture three-dimensional network model before and after core fracturing, and then establish a deep learning fracture three-dimensional network model before and after core fracturing in the entire cored well section.

[0037] Furthermore, the size of the CT gray scale value of natural fractures in the core for the three-dimensional fracture network detection of unconventional reservoirs by full-diameter core CT scanning can effectively identify natural fractures and their spatial distribution networks, and establish a three-dimensional spatial fracture network model of natural fractures in the cored section.

[0038] Furthermore, the CT gray value of the artificial fracturing cracks in the unconventional reservoir fracturing three-dimensional fracture network detection by full-diameter core CT scanning can effectively distinguish the artificial fracturing cracks and their spatial distribution network from the natural cracks and their spatial distribution network, and establish a three-dimensional spatial fracture network model of the artificial fracturing cracks in the cored section.

[0039] Furthermore, establish the artificial fracturing cracks and network controlled by the natural cracks and their network in the core, clarify the control mechanism of the natural cracks in the core on the artificial fracturing fracture network, and provide technical information for the artificial fracturing direction, method and pressure magnitude of the unconventional reservoir.

[0040] YL150: Apply the artificial intelligence recognition method to intelligently recognize and judge the three-dimensional fracture network model of deep learning fractures before and after core fracturing, so as to extract the net artificial fracturing fracture three-dimensional fracture network model after removing natural cracks after core fracturing. Then, conduct statistical analysis on the three-dimensional fracture network data to characterize the development degree and differences of natural cracks in each sub-section of the cored section, the three-dimensional fracture network of artificial fracturing cracks and their differences. By comparing the three-dimensional fracture networks of the two types of cracks, evaluate the control effect of natural cracks on the three-dimensional fracture network of artificial fracturing cracks and the artificial fracturing effect, and optimize the excellent fracturing section to provide technical information for the fine exploration and development plan design of unconventional oil and gas.

[0041] The unconventional reservoir fracture network detection method based on full-diameter core CT scanning provided by the present invention adopts CT non-destructive detection technology and gray-scale quantitative indexes of fracture development, and through machine learning, deep learning and artificial intelligence simulation, identifies natural cracks, artificial fracturing cracks and their identification criteria, accurately evaluates the development degree and differences of natural cracks in each sub-section of the cored section, the three-dimensional fracture network of artificial fracturing cracks and their differences, evaluates the control effect of natural cracks on the three-dimensional fracture network of artificial fracturing cracks and the artificial fracturing effect, optimizes the excellent fracturing section, improves the monitoring level of the fracturing transformation effect of the unconventional oil and gas exploration reservoir and the efficiency of oil and gas exploration, and reduces the oil and gas exploration and development costs.

[0042] The present invention provides solid basic information and data related to the artificial fracturing effect of the target layer reservoir and the development of reservoir "sweet spots" for the evaluation of unconventional oil and gas exploration effects and the design of development plans, accurately grasps the artificial fracturing state of high-quality sections, aims at the fine development target, thus effectively improving the accuracy of artificial fracturing transformation of the target target area, and avoiding the risk of failure in oil and gas drilling and development caused by not knowing the artificial fracturing transformation status of the reservoir in the well and the fracturing differences in different sections and being unable to provide accurate data. Since fracturing transformation is one of the core cornerstones of unconventional exploration and development, the guarantee rate of successful drilling in unconventional oil and gas exploration is greatly improved, thus accelerating the progress of unconventional oil and gas exploration and greatly reducing the exploration and development costs.

[0043] The above are only the preferred embodiments of the present invention, and do not impose any form of limitation on the present invention. Any simple modifications and equivalent changes made to the above embodiments based on the technical essence of the present invention all fall within the protection scope of the present invention.

Claims

1. An unconventional reservoir fracture network detection method based on full-diameter core CT scanning, characterized in that, It includes the following steps: S1. Based on the unconventional oil and gas geological background, obtain the rock types, burial depths, formation pressures, and core fracture network detection requirements of unconventional reservoirs. Based on the drilling methods and well types in drilling geology and engineering design, and the requirements for core pressure and shape preservation, confirm the types and models of core pressure and shape preservation sleeves before and after fracturing; S2. Adopt the full-diameter core CT scanning method to conduct systematic CT scanning on the core before fracturing, collect natural fracture data of the core, and establish a natural fracture gray model; through machine learning recognition using the established natural fracture gray model, establish a three-dimensional network model of natural fracture development; S3. Adopt the full-diameter core CT scanning method to conduct systematic CT scanning on the core after artificial fracturing, collect natural and artificial fracture data of the core, and establish a natural and artificial fracture gray model; through machine learning recognition using the established natural and artificial fracture gray model, establish a three-dimensional mixed network model of natural and artificial fracture development; S4. Adopt the deep learning method to conduct deep learning recognition on the three-dimensional network model established in step S2 and the three-dimensional mixed network model established in step S3, establish a three-dimensional fracture network model of the core before and after fracturing for deep learning training, and then establish a three-dimensional fracture network model of the core before and after fracturing in the entire cored interval; S5. Adopt the artificial intelligence recognition method to conduct intelligent recognition and judgment on the three-dimensional fracture network model of deep learning established in step S4, so as to extract the three-dimensional net artificial fracture network model after removing natural fractures after core fracturing, and then characterize the development degree and differences of natural fractures in each sub-section of the cored interval, the three-dimensional fracture network of artificial fractures and their differences, evaluate the control effect of natural fractures on the three-dimensional fracture network of artificial fractures and the artificial fracturing effect, and optimize excellent fracturing intervals.

2. The unconventional reservoir fracture network detection method based on full-diameter core CT scanning according to claim 1, characterized in that In step S1, the selection criteria for the types and models of core pressure and shape preservation sleeves before and after fracturing for the three-dimensional fracture network detection of unconventional reservoirs based on full-diameter core CT scanning are: the types and models of pressure and shape preservation sleeves selected based on unconventional rock types need to protect the core from secondary changes during the coring process.

3. The method for detecting the fracture network of unconventional reservoirs based on full-diameter core CT scanning according to claim 2, wherein, The secondary changes include the generation of secondary fractures.

4. The method for detecting the fracture network of unconventional reservoirs based on full-diameter core CT scanning according to claim 1 or 2, characterized in that, In step S1, the types and models of pressure and shape preservation sleeves selected based on unconventional rock types need to reduce the shielding effect of the metal sleeve on X-ray penetration.

5. The unconventional reservoir fracture network detection method based on full-diameter core CT scanning according to claim 4, characterized in that In step S1, based on the selected sleeve model and the compactness of the core, the selection criteria for the ray source current and voltage are: the level of the current and voltage needs to penetrate the sleeve and the rock to obtain rock fractures and their spatial fracture networks.

6. The method for detecting the fracture network of unconventional reservoirs based on full-diameter core CT scanning according to claim 1, characterized in that, In steps S2 and S3, the selection criteria for the cores before and after fracturing for the three-dimensional fracture network detection of unconventional reservoirs based on full-diameter core CT scanning are: cores drilled from the same target layer of the same well or cores drilled from the same target layer of adjacent wells, ensuring the consistency of natural fracture development in the cores.

7. The method for detecting the fracture network of unconventional reservoirs based on full-diameter core CT scanning according to claim 1, wherein In steps S2 and S3, the size or recognition criteria of the gray values of natural and artificial fractures can effectively identify and distinguish natural fractures and networks, and artificial fractures and networks.

8. The unconventional reservoir fracture network detection method based on full-diameter core CT scanning according to claim 1, wherein In the step S4, the CT gray value of the natural fractures in the core for the three-dimensional fracture network detection of unconventional reservoir fracturing by full-diameter core CT scanning can effectively identify the natural fractures and their spatial distribution network, and establish a three-dimensional spatial fracture network model of the natural fractures in the cored section.

9. The method for detecting the fracture network of unconventional reservoirs based on full-diameter core CT scanning according to claim 1 or 8, characterized in that, In the step S4, the CT gray value of the artificial fracturing fractures in the core for the three-dimensional fracture network detection of unconventional reservoir fracturing by full-diameter core CT scanning can effectively distinguish the artificial fracturing fractures and their spatial distribution network from the natural fractures and their spatial distribution network, and establish a three-dimensional spatial fracture network model of the artificial fracturing fractures in the cored section.

10. The method for detecting the fracture network of unconventional reservoirs based on full-diameter core CT scanning according to claim 9, wherein In the step S4, establish the artificial fracturing fractures and network controlled by the natural fractures and their network in the core, clarify the control mechanism of the natural fractures in the core on the artificial fracture network, and provide technical information for the artificial fracturing direction, method and pressure magnitude of unconventional reservoirs.