Multi-cycle fracturing method, device, medium and program product for deep coal reservoirs

Abstract

This application provides a method, apparatus, medium, and program product for multi-round fracturing in deep coal reservoirs. It relates to the field of deep coal reservoir stimulation technology. Each round of multi-round fracturing includes hydraulic fracturing and well shut-in. A simulated fracturing scheme for the nth round corresponding to the target deep coal reservoir is obtained. If n is 2, the fracturing fluid system in the simulated fracturing scheme is a variable viscosity slickwater fracturing fluid system; if n is not 2, the fracturing fluid system in the simulated fracturing scheme is a low-concentration guar gum fracturing fluid system. Based on the real-time wellhead pressure, real-time microseismic information obtained in the (n-1)th round, and the fracture network morphology after well shut-in in the (n-1)th round, an unconventional fracture propagation model is used to predict the fracture network morphology corresponding to hydraulic fracturing in the nth round, according to the simulated fracturing scheme of the nth round. Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to hydraulic fracturing in the nth round, the well shut-in time for the nth round is determined. This aims to achieve balanced stimulation of deep coal reservoirs and improve EUR (Earnings Equivalent to Fluid Regulator).

Description

Technical Field

[0001] This application relates to the field of deep coal reservoir stimulation technology, and in particular to a method, apparatus, medium and program product for multi-round fracturing of deep coal reservoirs. Background Technology

[0002] In recent years, the development depth of coal reservoirs has expanded from shallow to medium-deep and deep layers. Deep coal reservoirs possess enormous oil and gas development potential, and the rational and efficient development of these resources will significantly alleviate the severe energy shortage. Deep coal reservoirs have low water content and high gas content, with both free and adsorbed gas coexisting, but adsorbed gas remains dominant. Therefore, only by implementing volumetric modification of deep coal reservoirs, breaking up the adsorbed gas matrix, and significantly reducing the seepage distance and driving pressure differential from the matrix to fractures, can the adsorbed gas in the micro-Darcy level coal reservoir matrix be converted into effective oil and gas production.

[0003] In related technologies, the black gold target fracturing process is comprehensively promoted to carry out volumetric modification of deep coal reservoirs by continuously optimizing segment and cluster parameters. However, the problem of insufficient modification of deep coal reservoirs still exists, which leads to low estimated ultimate recovery (EUR).

[0004] Therefore, there is an urgent need to provide a new fracturing scheme for deep coal reservoirs to form balanced complex fractures and provide effective support, thereby improving EUR. Summary of the Invention

[0005] This application provides a method, apparatus, media, and procedure for multi-round fracturing of deep coal reservoirs to achieve balanced and full stimulation of deep coal reservoirs and improve the effectiveness of EUR (Effective Fluctuation).

[0006] In a first aspect, this application provides a multi-round fracturing method for deep coal reservoirs, wherein each round of fracturing includes hydraulic fracturing and well shut-in. The multi-round fracturing method for deep coal reservoirs includes:

[0007] Obtain the simulated fracturing scheme for the nth round corresponding to the target deep coal reservoir, where n is a positive integer and less than or equal to N, and N is an integer greater than or equal to 3. If n is 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a variable viscosity slickwater fracturing fluid system; if n is not 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a low concentration guar gum fracturing fluid system.

[0008] Based on the real-time wellhead pressure, real-time microseismic information obtained in the (n-1)th round, and the fracture network morphology after well blockage in the (n-1)th round of fracturing, according to the simulated fracturing scheme of the nth round, the unconventional fracture propagation model is used to predict the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing.

[0009] Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing, the shut-in time corresponding to the nth round of fracturing is determined.

[0010] In one possible implementation, the shut-in time corresponding to the nth round of hydraulic fracturing is determined based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round, including:

[0011] Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing, the reservoir stress evolution characteristics and permeability evolution characteristics are obtained.

[0012] Based on the reservoir stress evolution characteristics and permeability evolution characteristics, the shut-in time corresponding to the nth round of fracturing is determined.

[0013] In one possible implementation, based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing, the reservoir stress evolution characteristics and permeability evolution characteristics are obtained, including:

[0014] Real-time monitoring and acquisition of wellhead pressure and microseismic information are used to obtain real-time wellhead pressure and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing.

[0015] Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing, an unconventional fracture propagation model is used to predict and determine the reservoir stress evolution characteristics and permeability evolution characteristics of the target deep coal reservoir during the well shut-in process.

[0016] In one possible implementation, the shut-in time corresponding to the nth round of fracturing is determined based on the reservoir stress evolution characteristics and permeability evolution characteristics, including:

[0017] Based on the characteristics of reservoir stress evolution, the time of the first inflection point when the stress evolution trend slows down is obtained;

[0018] Based on the characteristics of permeability evolution, the time of the second inflection point when the permeability evolution trend slows down is obtained;

[0019] Based on the first inflection point time and the second inflection point time, determine the shut-in time corresponding to the nth round of fracturing.

[0020] In one possible implementation, if n is greater than or equal to 3, it further includes:

[0021] Based on the fracture network morphology after well blockage in the nth round of fracturing and the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir, determine whether to terminate the fracturing of the target deep coal reservoir. The fracture network morphology includes the fracture volume.

[0022] If not, trigger the (n+1)th round of fracturing of the target deep coal reservoir.

[0023] In one possible implementation, based on the fracture network morphology after well blockage in the nth round of fracturing and the simulated fracturing scheme for the (n+1)th round corresponding to the target deep coal reservoir, it is determined whether to terminate the fracturing of the target deep coal reservoir, including:

[0024] Based on the fracture network morphology, reservoir stress evolution characteristics, and permeability evolution characteristics corresponding to hydraulic fracturing in the nth round of fracturing, an unconventional fracture propagation model is adopted to obtain the fracture network morphology after well blockage in the nth round of fracturing.

[0025] Based on the fracture network morphology after the well is shut down in the nth round of fracturing, and according to the simulated fracturing scheme of the n+1th round corresponding to the target deep coal reservoir, an unconventional fracture propagation model is used to predict the fracture network morphology after the n+1th round of fracturing. The predicted fracture network morphology includes the predicted fracture volume.

[0026] Determine the ratio of the predicted fracture network volume corresponding to the (n+1)th round of fracturing to the fracture volume of the nth round, and obtain the fracture volume ratio;

[0027] If the fracture volume ratio is greater than or equal to the fracture volume ratio threshold, then it is determined that the target deep coal reservoir will continue to undergo the (n+1)th round of fracturing.

[0028] If the fracture volume ratio is less than the fracture volume ratio threshold, the fracturing of the target deep coal reservoir is terminated.

[0029] In one possible implementation:

[0030] If the joint volume ratio is less than the joint volume ratio threshold, determine whether the number of adjustments is less than M times;

[0031] If the number of adjustments is less than M, based on the fracture network morphology after the well is blocked in the nth round of fracturing, adjust the simulated fracturing scheme for the (n+1)th round corresponding to the target deep coal reservoir to obtain a new simulated fracturing scheme for the (n+1)th round, and update the number of adjustments.

[0032] For the new simulated fracturing scheme of the (n+1)th round, the following steps are taken: based on the fracture network morphology after the well is blocked in the fracturing of the nth round, and according to the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir, an unconventional fracture propagation model is used to predict and obtain the predicted fracture network morphology after the fracturing of the (n+1)th round.

[0033] If the number of adjustments is greater than or equal to M, the fracturing of the target deep coal reservoir is terminated.

[0034] Secondly, this application provides a multi-stage fracturing device for deep coal reservoirs, comprising:

[0035] The acquisition module is used to acquire the simulated fracturing scheme for the nth round corresponding to the target deep coal reservoir, where n is a positive integer and n is less than or equal to N, and N is an integer greater than or equal to 3. If n is 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a variable viscosity slickwater fracturing fluid system; if n is not 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a low concentration guar gum fracturing fluid system.

[0036] The processing module is used to predict the fracture network morphology corresponding to hydraulic fracturing in the nth round based on the real-time wellhead pressure, real-time microseismic information and fracture network morphology after well blockage in the n-1th round of fracturing, according to the simulated fracturing scheme of the nth round, using an unconventional fracture propagation model.

[0037] The determination module is used to determine the shut-in time corresponding to the nth round of fracturing based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing.

[0038] In one possible implementation, the determining module is specifically used for:

[0039] Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing, the reservoir stress evolution characteristics and permeability evolution characteristics are obtained.

[0040] Based on the reservoir stress evolution characteristics and permeability evolution characteristics, the shut-in time corresponding to the nth round of fracturing is determined.

[0041] In one possible implementation, the determining module is further configured to:

[0042] Real-time monitoring and acquisition of wellhead pressure and microseismic information are used to obtain real-time wellhead pressure and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing.

[0043] Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing, an unconventional fracture propagation model is used to predict and determine the reservoir stress evolution characteristics and permeability evolution characteristics of the target deep coal reservoir during the well shut-in process.

[0044] In one possible implementation, the determining module is further configured to:

[0045] Based on the characteristics of reservoir stress evolution, the time of the first inflection point when the stress evolution trend slows down is obtained;

[0046] Based on the characteristics of permeability evolution, the time of the second inflection point when the permeability evolution trend slows down is obtained;

[0047] Based on the first inflection point time and the second inflection point time, determine the shut-in time corresponding to the nth round of fracturing.

[0048] In one possible implementation, if n is greater than or equal to 3, the acquisition module is further configured to:

[0049] Based on the fracture network morphology after well blockage in the nth round of fracturing and the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir, determine whether to terminate the fracturing of the target deep coal reservoir. The fracture network morphology includes the fracture volume.

[0050] If not, trigger the (n+1)th round of fracturing of the target deep coal reservoir.

[0051] In one possible implementation, the acquisition module is further configured to:

[0052] Based on the fracture network morphology, reservoir stress evolution characteristics, and permeability evolution characteristics corresponding to hydraulic fracturing in the nth round of fracturing, an unconventional fracture propagation model is adopted to obtain the fracture network morphology after well blockage in the nth round of fracturing.

[0053] Based on the fracture network morphology after the well is shut down in the nth round of fracturing, and according to the simulated fracturing scheme of the n+1th round corresponding to the target deep coal reservoir, an unconventional fracture propagation model is used to predict the fracture network morphology after the n+1th round of fracturing. The predicted fracture network morphology includes the predicted fracture volume.

[0054] Determine the ratio of the predicted fracture network volume corresponding to the (n+1)th round of fracturing to the fracture volume of the nth round, and obtain the fracture volume ratio;

[0055] If the fracture volume ratio is greater than or equal to the fracture volume ratio threshold, then it is determined that the target deep coal reservoir will continue to undergo the (n+1)th round of fracturing.

[0056] If the fracture volume ratio is less than the fracture volume ratio threshold, the fracturing of the target deep coal reservoir is terminated.

[0057] In one possible implementation, the acquisition module is further configured to:

[0058] If the joint volume ratio is less than the joint volume ratio threshold, determine whether the number of adjustments is less than M times;

[0059] If the number of adjustments is less than M, based on the fracture network morphology after the well is blocked in the nth round of fracturing, adjust the simulated fracturing scheme for the (n+1)th round corresponding to the target deep coal reservoir to obtain a new simulated fracturing scheme for the (n+1)th round, and update the number of adjustments.

[0060] For the new simulated fracturing scheme of the (n+1)th round, the following steps are taken: based on the fracture network morphology after the well is blocked in the fracturing of the nth round, and according to the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir, an unconventional fracture propagation model is used to predict and obtain the predicted fracture network morphology after the fracturing of the (n+1)th round.

[0061] If the number of adjustments is greater than or equal to M, the fracturing of the target deep coal reservoir is terminated.

[0062] Thirdly, this application provides an electronic device, including: a memory and a processor;

[0063] The memory stores instructions that the computer executes;

[0064] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0065] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible embodiments of the first aspect.

[0066] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0067] The deep coal reservoir multi-round fracturing method, apparatus, media, and program products provided in this application alternately use a low-concentration guar gum fracturing fluid system and a variable viscosity slickwater fracturing fluid system in multi-round fracturing. Because the variable viscosity slickwater fracturing fluid system has lower viscosity and weaker proppant-carrying capacity compared to the low-concentration guar gum fracturing fluid system, using the variable viscosity slickwater fracturing fluid system can achieve temporary plugging of the fracture network in previous rounds of fracturing, reduce reservoir stress differentials, and mitigate the impact of tectonic stress on fracture network width. The low-concentration guar gum fracturing fluid system produces lower residue content, effectively avoiding residue residue in the reservoir, reducing the risk of pore throat blockage, minimizing reservoir damage, maintaining fracture conductivity, and promoting oil and gas well production. Furthermore, the low-concentration guar gum fracturing fluid system has good temperature and shear resistance, maintaining stable performance under high temperature and shear conditions, ensuring the successful execution of fracturing operations. By alternating the use of two fracturing fluids, a more balanced and complex fracture network is formed, enabling adsorbed gas in the micro-Darcy matrix to be converted into effective oil and gas production, thus improving the exploitation efficiency of deep coal reservoirs. Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information, the shut-in time is determined to ensure effective fracture propagation and achieve the desired results. This helps increase reservoir permeability, improve oil and gas recovery, and avoids unnecessary damage to the reservoir caused by excessive fracturing, such as reservoir fracture or fracture closure. Through these methods, the coal reservoir is fully stimulated, the fracture network width is increased, and the EUR (Effective Recovery Rate) is improved. Attached Figure Description

[0068] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0069] Figure 1 A flowchart illustrating the multi-round fracturing method for deep coal reservoirs provided in this application embodiment. Figure 1 ;

[0070] Figure 2 A schematic diagram of the minimum principal stress distribution after the first round of fracturing provided in this application embodiment;

[0071] Figure 3 This application provides a fracture morphology feature diagram after the first round of hydraulic fracturing.

[0072] Figure 4 A flowchart illustrating the method for determining well stagnation time provided in an embodiment of this application;

[0073] Figure 5 The reservoir stress evolution characteristic diagram in the first round of well blockage provided in this application embodiment;

[0074] Figure 6 The diagram showing the minimum principal stress distribution in the first round of well blockage provided in this application embodiment;

[0075] Figure 7 The permeability evolution characteristic diagram in the first round of suffocation wells provided in the embodiments of this application;

[0076] Figure 8 A flowchart illustrating the multi-round fracturing determination method provided in this application embodiment;

[0077] Figure 9 A flowchart illustrating the multi-round fracturing method for deep coal reservoirs provided in this application embodiment. Figure 2 ;

[0078] Figure 10 This is a schematic diagram of the hydraulic fracture morphology for each round provided in the embodiments of this application;

[0079] Figure 11 A schematic diagram of the fracture volume and total fracture mesh volume for each round of fracturing provided in the embodiments of this application;

[0080] Figure 12 A schematic diagram of the structure of a multi-round fracturing device for deep coal reservoirs provided in the embodiments of this application;

[0081] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0082] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0083] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0084] In related technologies, due to the well-developed microstructures of coal reservoirs, the fracture network morphology formed by fracturing is significantly affected by tectonic stress. In the initial stage of fracturing, the fracture network is influenced by the principal stress direction, resulting in insufficient fracture width, making it difficult to achieve balanced stimulation of the coal reservoir and limiting oil and gas extraction. Secondly, the strong heterogeneity of coal reservoir properties means that fracture formation is influenced by both natural fractures and the heterogeneity of coal reservoir properties, making the design and implementation of fracturing processes more complex and difficult to implement precise strategies for different reservoir characteristics, thus affecting fracturing effectiveness. In summary, there are technical problems such as insufficient coal reservoir stimulation, low single-well production, rapid decline, and difficulty in achieving the expected recovery rate.

[0085] The multi-round fracturing method for deep coal reservoirs provided in this application considers that, compared with the low-concentration guar gum fracturing fluid system, the variable-viscosity slickwater fracturing fluid system has lower viscosity and weaker proppant carrying capacity. Using the variable-viscosity slickwater fracturing fluid system for fracturing can temporarily plug the fracture network formed in the previous fracturing rounds, reduce stress differentials, minimize the impact of tectonic stress on fracture network width, and balance the negative impact of reservoir heterogeneity on fracture network extension. Meanwhile, the low-concentration guar gum fracturing fluid system has a lower residue content, effectively avoiding residue residue in the reservoir, reducing the risk of pore throat blockage, minimizing damage to the reservoir, maintaining fracture conductivity, and promoting increased oil and gas well production. It also maintains stable performance under high temperature and shear stress, ensuring the successful execution of fracturing operations. By alternating the use of the two fracturing fluids, a more balanced and complex fracture network is formed, achieving the effects of fully modifying the coal reservoir, increasing fracture network width, and improving EUR (Earning Equivalent to EUR). Therefore, alternating the use of low-concentration guar gum fracturing fluid systems and variable viscosity slickwater fracturing fluid systems in multiple fracturing cycles enhances fracture support and conductivity, reduces fracture closure and fluid flow resistance, ensures fracture propagation efficiency, and thus improves the EUR of coal reservoir oil and gas.

[0086] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0087] Figure 1 A flowchart illustrating the multi-round fracturing method for deep coal reservoirs provided in this application embodiment. Figure 1 .like Figure 1 As shown, the method includes:

[0088] S101. Obtain the simulated fracturing scheme for the nth round corresponding to the target deep coal reservoir, where n is a positive integer and n is less than or equal to N, and N is an integer greater than or equal to 3. If n is 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a variable viscosity slick water fracturing fluid system; if n is not 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a low concentration guar gum fracturing fluid system.

[0089] For example, simulated fracturing schemes can be designed using computer simulation technology to optimize actual fracturing operations for specific geological reservoirs (such as deep coal reservoirs).

[0090] Fracturing fluid systems are the fracturing fluids used in fracturing operations. For example, fracturing fluid systems can include variable viscosity slickwater fracturing fluid systems and guar gum fracturing fluid systems. Variable viscosity slickwater fracturing fluid systems use water as the dispersion medium and are formulated with drag-reducing agents and other additives. Guar gum fracturing fluid systems are high-permeability water-based fracturing fluids that use water as the main solvent and contain guar gum, crosslinking agents, antibacterial agents, etc. Through chemical modification, functional groups are introduced into the guar gum or hydroxypropyl guar gum molecular chains. These functional groups swell in aqueous solution and repel each other, promoting better molecular chain unfolding and thus increasing the viscosity of the fracturing fluid. The guar gum concentration in low-concentration guar gum fracturing fluid systems is much lower than that in conventional fracturing. Optionally, in conventional fracturing, the guar gum concentration in the guar gum fracturing fluid is 0.6%. In this case, the guar gum concentration in the low-concentration guar gum fracturing fluid system must be much less than 0.6%.

[0091] In this step, N represents the number of rounds in the multi-round fracturing method. Different fracturing fluid systems are flexibly selected based on the round, combining the fracturing effects of two different systems to achieve better fracturing results. The low-concentration guar gum fracturing fluid system has good sand-carrying performance and stability, significantly reducing the fluid loss rate and improving fracture creation efficiency. It maximizes the construction of the main fracture network along the direction of maximum principal stress, enabling efficient extension of the main fracture in complex natural fractures. The variable viscosity slickwater fracturing fluid system has lower viscosity and weaker sand-carrying capacity. Combined with the high sand ratio fracturing method, it allows a large amount of proppant to form artificial sand plugs in the existing hydraulic fractures. After the proppant settles, it forms a low-permeability stress wall, thereby temporarily plugging the microfractures from the previous rounds and causing the fracture network to shift and densify in the fracture width direction. At the same time, the sand in the sand plug can provide flow conduction capacity, prevent the fracture from extending in the fracture length direction, open more cleavage fractures to form branch fractures in the fracture width direction, and make the fracture-making mechanism in subsequent cycles more inclined to open complex fractures, thereby improving the EUR of oil and gas in coal reservoirs.

[0092] S102. Based on the real-time wellhead pressure, real-time microseismic information obtained in the (n-1)th round, and the fracture network morphology after well blockage in the (n-1)th round of fracturing, according to the simulated fracturing scheme of the nth round, the unconventional fracture propagation model is used to predict and obtain the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing.

[0093] For example, fracture network morphology represents the distribution, shape, and connectivity of a fracture network composed of natural fractures and hydraulically fractured fractures in the geology. Fracture network morphology includes: fracture network width, fracture network length, fracture size, fracture direction, fracture distribution, fracture length, fracture width, and fracture volume. Real-time wellhead pressure in round n-1 represents the pressure value at the wellhead of an oil and gas well requiring multiple rounds of fracturing operations in round n-1. Real-time microseismic information in round n-1 represents the microseismic activity data caused by fracture propagation and reservoir stimulation during the fracturing process in round n-1. For example, if n=1, real-time wellhead pressure represents the pressure value at the wellhead of the oil and gas well acquired before fracturing; real-time microseismic information represents the microseismic activity data of the formation acquired before fracturing. For example, unconventional fracture propagation models can more accurately describe and predict the morphology, distribution, and evolution characteristics of fractures in heterogeneous, low-permeability, and other unconventional reservoirs. Hydraulic fracturing refers to the process of creating fractures in rocks by pumping fracturing fluid under high pressure, thereby improving the permeability of oil and gas reservoirs.

[0094] By combining real-time wellhead pressure, real-time microseismic information, and the fracture network morphology after well blockage in the (n-1)th round of fracturing, an unconventional fracture propagation model is used to simulate and predict the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing, making the simulated fracture network morphology more closely resemble reality. By incorporating real-time wellhead pressure and real-time microseismic information, the spatial distribution characteristics of fractures can be obtained in real time, enabling a more accurate simulation of the complexity and dynamic changes of fractures, and obtaining a precise fracture network morphology.

[0095] Optionally, when n=1, the fracture network morphology after well shut-in in the (n-1)th round of fracturing, i.e., the fracture network morphology after well shut-in in the 0th round of fracturing, can be represented by the original fracture network morphology. For example, the original fracture network morphology is the fracture network morphology formed by natural fractures in the geology before fracturing.

[0096] To facilitate understanding of the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing, this application uses the fracture network morphology corresponding to hydraulic fracturing in the first round of fracturing when n=1 as an example for detailed explanation.

[0097] Figure 2 This is a schematic diagram showing the minimum principal stress distribution after the first round of fracturing, provided in an embodiment of this application. The minimum principal stress is represented by a black curve, and the location of the points is indicated by geodetic coordinates, where:

[0098] The black curves in the diagram represent the directions of principal stresses. The directions overlapping with or roughly parallel to the black curves are generally considered to be the directions of minimum principal stress, which are mostly in the north-south direction. The direction perpendicular to the black curves is the direction of maximum principal stress, which is mostly in the east-west direction. Under the influence of the direction of maximum principal stress, rocks are more likely to deform or fracture along this direction; that is, fractures formed by hydraulic fracturing are more likely to propagate in the east-west direction.

[0099] Geodetic coordinates are a coordinate system used to determine the location of a point on Earth. In the geodetic coordinate system, coordinates are divided into two dimensions: Y-axis and X-axis. Y-axis represents the vertical coordinate, and X-axis represents the horizontal coordinate. The coordinate pair (Y-axis, X-axis) formed by Y-axis and X-axis can uniquely represent the location of a point.

[0100] Figure 3 The image shows the fracture morphology after the first round of fracturing, as provided in the embodiments of this application. Figure 3 exist Figure 2 Based on this, the fracture morphology characteristics after the first round of hydraulic fracturing are described in detail, including: path AB, path CD, measuring point 1, measuring point 2, measuring point 3, fracture and geodetic coordinates.

[0101] Path AB represents the direction of maximum principal stress, and path CD represents the direction of minimum principal stress. Measuring point 1, located at the wellhead of the oil and gas well, directly monitors the stress state and fracture development around the well, indicating the condition of the well perimeter. Measuring point 2, along the direction of maximum principal stress, accurately captures the influence of maximum principal stress on rock fracturing and fracture formation, indicating the condition in the fracture length direction. Measuring point 3, along the direction of minimum principal stress, reveals the constraint effect of minimum principal stress on rock fracturing and fracture morphology, indicating the condition in the fracture width direction. The line segments in the figure represent the morphology of fractures along the directions of maximum and minimum principal stress. The length of the line segments reflects the size of the fracture, the direction of the line segments reflects the direction of the fracture, and the distribution of the line segments reflects the distribution of fractures. Fractures can reflect the stress state and fracturing characteristics of the reservoir rock.

[0102] S103. Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing, determine the shut-in time corresponding to the nth round of fracturing.

[0103] The term "shutdown time" can be understood as the process of stopping pumping after fracturing operations during the gas extraction process in deep coal reservoirs, allowing the pressure and temperature inside the gas well to reach equilibrium.

[0104] Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing, the propagation of fractures, changes in wellhead pressure, and the distribution of microseismic events are analyzed to determine a reasonable shut-in time. This ensures that the pressure within the fractures is fully released, altering the distribution of geostress and the permeability of the gas reservoir. Simultaneously, it avoids unnecessary damage or economic losses to the reservoir, such as reservoir rupture or fracture closure, caused by excessive fracturing. By real-time monitoring and analysis of fracture network morphology, wellhead pressure, and microseismic information, fracturing strategies and shut-in times are adjusted promptly according to the complexity of the fracture network, maximizing production efficiency and ultimate recovery rate.

[0105] This application embodiment utilizes two different types of fracturing fluid systems alternately in multiple fracturing operations. The low-concentration guar gum fracturing fluid system has a low residue content, effectively preventing residue buildup in the reservoir, reducing the risk of pore throat blockage, minimizing reservoir damage, maintaining good fracture conductivity, and ensuring efficient fracture propagation. This allows adsorbed gas to more smoothly form effective oil and gas production, contributing to increased well production. It also maintains stable performance under high temperature and shear stress, ensuring successful and stable fracturing operations. The variable viscosity slickwater fracturing fluid system has low viscosity and weak proppant carrying capacity. Using this system can temporarily plug the fracture network formed in previous fracturing operations, reducing stress differentials and balancing the negative impact of tectonic stress on fracture width extension, allowing for sufficient fracture width extension. By alternating between the low-concentration guar gum fracturing fluid system and the variable viscosity slickwater fracturing fluid system, the fracture network width can be increased, ensuring fracture conductivity and improving oil and gas production. Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information, the well shut-in time can be flexibly determined to ensure effective fracture propagation, increase reservoir permeability, and achieve the effects of fully transforming deep coal reservoirs, increasing fracture network width, and improving EUR.

[0106] Figure 4 This is a flowchart illustrating the method for determining the well stagnation time provided in an embodiment of this application. Figure 4 As shown, this embodiment, based on step S103, provides a detailed explanation of the method for determining the well stagnation time. This method includes:

[0107] S1031. Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing, obtain the reservoir stress evolution characteristics and permeability evolution characteristics.

[0108] For example, reservoir stress evolution characteristics represent the changes in the internal stress state of deep coal reservoirs over time during fracturing operations, reflecting the mechanical response of the reservoir rock and the formation and propagation of fractures. Permeability evolution characteristics represent the changes in the permeability of deep coal reservoirs as the fracturing operation progresses, indirectly reflecting the degree of fracture opening, the connectivity of the fracture network, and the fluid flow capacity within the fractures.

[0109] Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing, combined with porosity elasticity theory and the stress sensitivity characteristics of coal and rock permeability, reservoir stress evolution characteristics and permeability evolution characteristics are obtained. The mechanical response of the reservoir rock in the stalemate is assessed through the reservoir stress evolution characteristics; the reservoir productivity changes are predicted through the permeability evolution characteristics. By comprehensively analyzing the reservoir stress evolution characteristics and permeability evolution characteristics, the formation of fractures and stress changes in deep coal reservoirs are simulated, assisting in the design of fracturing operation parameters and the determination of stalemate time.

[0110] Optionally, reservoir stress evolution characteristics and permeability evolution characteristics can be calculated using an unconventional fracture propagation model.

[0111] In one possible implementation, wellhead pressure and microseismic information are monitored and collected in real time to obtain the real-time wellhead pressure and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing; based on the fracture network morphology, real-time wellhead pressure and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing, an unconventional fracture propagation model is used to predict and determine the reservoir stress evolution characteristics and permeability evolution characteristics corresponding to the target deep coal reservoir during the well shut-in process.

[0112] In the nth round of fracturing operations, the pressure changes of the wellhead fluid are monitored and recorded in real time to obtain the real-time wellhead pressure; the micro-seismic waves triggered by fracture propagation are captured to obtain real-time microseismic information.

[0113] Optionally, a high-precision pressure sensor can be installed at the wellhead to obtain real-time wellhead pressure. Seismic monitoring equipment, such as a seismograph array, can be deployed around the well site to obtain real-time microseismic information.

[0114] By employing an unconventional fracture propagation model, combined with the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing, the formation and propagation process of subsequent fractures is simulated and predicted to more accurately reflect the actual situation inside the reservoir. Through real-time monitoring and recording of wellhead pressure and real-time microseismic information, the reservoir stress evolution characteristics and permeability evolution characteristics of the target deep coal reservoir during the well shut-in process are determined. The unconventional fracture propagation model, by considering both micro and macro fractures, improves the simulation capability of fracture changes in the target deep coal reservoir. By simulating the dynamic response of fractures, the propagation, closure, and conductivity of fractures can be simulated in detail and dynamically, significantly improving the accuracy of the assessment of the fracturing effect of the target deep coal reservoir. This ensures that the predicted reservoir stress evolution characteristics and permeability evolution characteristics are more consistent with the actual situation, accurately solving the fracture propagation efficiency and reservoir permeability, and achieving precise control of reservoir fracturing.

[0115] This application uses the reservoir stress evolution characteristics and permeability evolution characteristics in the first round of well closure as examples to provide a detailed description of the reservoir stress evolution characteristics and permeability evolution characteristics corresponding to the target deep coal reservoir, including:

[0116] Figure 5 The reservoir stress evolution characteristic diagram in the first round of well blockage provided in this application embodiment. Figure 5 exist Figure 3 Based on this, the reservoir stress evolution characteristics in the first round of well blockage are described in detail, including:

[0117] exist Figure 5 In the diagram, the curve corresponding to point 1 depicts the changing trend of the minimum horizontal principal stress at point 1 with the well closure time; the curve corresponding to point 2 reflects the change in the minimum horizontal principal stress at point 2; and the curve corresponding to point 3 reflects the change in the minimum horizontal principal stress at point 3. The different minimum principal stress changes at the three points reflect the differences in coal reservoir stress. These three curves together constitute a comprehensive summary and display of the reservoir stress evolution characteristics of the coal reservoir, providing important reference for analyzing coal reservoir stability, predicting coal reservoir behavior, and determining well closure time. The well closure time is expressed in days.

[0118] The minimum principal stresses at measuring points 1, 2, and 3 initially increased with the duration of well closure, reaching 56.9 MPa and 61.4 MPa respectively after 4 days of closure. The changes in minimum principal stress at different measuring points were related to their distance from the wellbore; and the change in minimum principal stress along the fracture propagation normal (measuring point 3) was greater than that along the fracture propagation direction (measuring point 2). After 4 days of closure, the minimum principal stresses at measuring points 1, 2, and 3 decreased with time, decreasing to 53 MPa and 54.7 MPa respectively after 14 days of closure.

[0119] To illustrate in detail the variations of reservoir stress evolution characteristics in the target deep coal reservoir, Figure 6 The diagram shows the distribution of minimum principal stress in the first round of well blockage provided in this application embodiment. Figure 6 exist Figure 5 Based on this, the distribution of minimum principal stress in the first round of well blockage is described in detail, including:

[0120] The distribution of minimum principal stress in the days following the completion of fracturing includes: the minimum principal stress distribution after 0 days of well closure (i.e., the minimum principal stress distribution after fracturing), the minimum principal stress distribution after 1 day of well closure, the minimum principal stress distribution after 4 days of well closure, and the minimum principal stress distribution after 8 days of well closure.

[0121] Different colors are used to represent the magnitude of the minimum principal stress in the distribution of minimum principal stress; the redder the color, the greater the minimum principal stress, and the bluer the color, the smaller the minimum principal stress. At day 0 of well closure, the overall color is predominantly blue, indicating that the minimum principal stress remains within a small range. After day 1 of well closure, the minimum principal stress shows an increasing trend, spreading from the wellhead outwards with the seepage of fracturing fluid around the well. After day 4 of well closure, the minimum principal stress gradually increases to its maximum, at which point the disturbance range of the induced stress also increases to its maximum value. After day 8 of well closure, the minimum principal stress gradually decreases to a smaller range.

[0122] Figure 7 The permeability evolution characteristic diagram in the first round of suffocation wells provided for the embodiments of this application. Figure 7 exist Figure 3 Based on this, the permeability evolution characteristics in the first round of well blockage are described in detail, including:

[0123] Figure 7 The curve represented by midpoint 1 indicates the wellbore permeability evolution characteristic corresponding to measuring point 1; the curve represented by point 2 indicates the permeability evolution characteristic along the fracture length corresponding to measuring point 2; and the curve represented by point 3 indicates the permeability evolution characteristic along the fracture width corresponding to measuring point 3. The changes in permeability at these three measuring points comprehensively represent the permeability evolution characteristics of the coal reservoir. The permeability evolution characteristics demonstrate the permeability performance of the coal reservoir at different locations and time points, which can assist in analyzing reservoir fluid flow patterns, estimating the magnitude of the EUR (Effective Urge of Permeability), and selecting an appropriate well shut-in period, where the well shut-in period is expressed in days.

[0124] The permeability at measuring points 1, 2, and 3 increases with the duration of well closure. When the closure time is 0 days, the permeability at measuring point 1 is 0.94, at measuring point 2 it is 0.26, and at measuring point 3 it is 0.21. When the closure time is 8 days, the increase in permeability tends to level off. At this point, the permeability at measuring point 1 is 1.57, at measuring point 2 it is 0.50, and at measuring point 3 it is 0.33. The increase in permeability around the well at measuring point 1 is 1.57 - 0.94 = 0.63; the increase in permeability along the fracture length at measuring point 2 is 0.50 - 0.26 = 0.24; and the increase in permeability along the fracture width at measuring point 3 is 0.33 - 0.21 = 0.12. Therefore, the increase in permeability around the well is greater than the increase in permeability along the fracture length, which is greater than the increase in permeability along the fracture width, and the increase in permeability along the fracture width exhibits a lag.

[0125] The significant increase in wellbore permeability is due to the combined effects of fluid pressure changes in the reservoir surrounding the wellbore, rock stress state, and fracturing, which promote the formation and expansion of fluid channels near the wellbore, thus significantly improving wellbore permeability. Permeability along the fracture length shows a certain increasing trend, as the fracture network provides a transport path for fluids; however, factors such as the degree of fracture opening, connectivity, and interactions along the fracture length limit the increase in permeability. The increase in permeability along the fracture width appears relatively lagging and the increase is limited. Due to the compactness of the matrix coal and rock, the complexity of the pore structure, and the interaction between fluid and rock, improvements in permeability along the fracture width typically require a longer timescale.

[0126] S1032. Based on the reservoir stress evolution characteristics and permeability evolution characteristics, determine the shut-in time corresponding to the nth round of fracturing.

[0127] Based on the reservoir stress evolution characteristics and permeability evolution characteristics, the shut-in time is determined by the time when the evolution trend slows down. This ensures that the shut-in time meets the requirements for sufficient fracture expansion, avoids unnecessary waiting time, and improves production efficiency.

[0128] In one possible implementation, the time of the first inflection point when the stress evolution trend slows down is obtained based on the reservoir stress evolution characteristics; the time of the second inflection point when the permeability evolution trend slows down is obtained based on the permeability evolution characteristics; and the well shut-in time corresponding to the nth round of fracturing is determined based on the first inflection point time and the second inflection point time.

[0129] For example, the first inflection point represents the point in time when the rate of increase in reservoir stress evolution slows down during the stress state change curve within the reservoir during oil and gas field fracturing operations, marking the entry of the stress state into a relatively stable or slowly changing stage. The second inflection point represents the point in time when the rate of increase in permeability slows down during the changes in permeability evolution characteristics as fracturing operations proceed, reflecting the turning point in the degree of improvement in reservoir fluid flow capacity.

[0130] The shut-in time is determined by using the first and second inflection point times to ensure that the fracturing fluid has sufficient time to diffuse and react in the coal reservoir, thereby improving the conductivity of the fractures and the fracturing effect. Simultaneously, extraction is avoided during periods of rapid stress or permeability changes to prevent wellbore instability caused by reservoir instability, ensuring the safety and stability of the extraction process, significantly improving the efficiency and effectiveness of fracturing operations, and reducing extraction risks.

[0131] This application's embodiments utilize the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing to obtain reservoir stress evolution characteristics reflecting the mechanical response of the reservoir rock, and permeability evolution characteristics reflecting the fluid's flow capacity in the fractures. Based on these reservoir stress and permeability evolution characteristics, a shut-in time is determined. This ensures that the determined shut-in time not only guarantees sufficient diffusion and reaction time for the fracturing fluid but also avoids safety issues such as wellbore instability, thereby improving production efficiency and reducing production risks.

[0132] Figure 8 This is a flowchart illustrating the multi-round fracturing determination method provided in an embodiment of this application. Figure 8 As shown, in this embodiment... Figure 1 Based on the embodiments, a method for determining multiple rounds of fracturing is described in detail. This method is used to determine the rounds of multiple fracturing operations, including:

[0133] S801. Based on the fracture network morphology after well blockage in the nth round of fracturing and the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir, determine whether to terminate the fracturing of the target deep coal reservoir. The fracture network morphology includes the fracture volume.

[0134] For example, fracture volume refers to the size of the fracture volume formed in the reservoir by injecting high-pressure fluid during a particular fracturing operation.

[0135] If the fracturing effect of the simulated fracturing scheme in the (n+1)th round is not significant, then fracturing of the target deep coal reservoir is performed; otherwise, the next round of fracturing of the target deep coal reservoir is continued. By analyzing the fracture network morphology after well blockage in the nth round of fracturing and the simulated fracturing scheme for the (n+1)th round corresponding to the target deep coal reservoir, unnecessary repeated fracturing is avoided, saving costs; maximizing the fracturing effect is ensured; and damage to the reservoir is reduced, avoiding reservoir destruction and permeability reduction that may result from excessive fracturing.

[0136] Optionally, this step may further include:

[0137] S8011. Based on the fracture network morphology, reservoir stress evolution characteristics, and permeability evolution characteristics corresponding to hydraulic fracturing in the nth round of fracturing, an unconventional fracture propagation model is adopted to obtain the fracture network morphology after well blockage in the nth round of fracturing.

[0138] For example, the fracture network morphology after well blockage in the nth round of fracturing reflects the current fracture propagation and permeability improvement of the reservoir.

[0139] S8012. Based on the fracture network morphology after the well is shut down in the nth round of fracturing, according to the simulated fracturing scheme of the n+1th round corresponding to the target deep coal reservoir, an unconventional fracture propagation model is used to predict the predicted fracture network morphology after the n+1th round of fracturing. The predicted fracture network morphology includes the predicted fracture volume.

[0140] An unconventional fracture propagation model was used to predict the fracture network morphology after the (n+1)th round of fracturing, and the fracturing effect of the (n+1)th round was evaluated. By predicting the fracture volume, the degree of improvement in reservoir permeability caused by fracturing operations and the contribution of the fracture network of the (n+1)th round to oil and gas flow in deep coal reservoirs were assessed.

[0141] S8013. Determine the ratio of the predicted fracture network volume corresponding to the (n+1)th round of fracturing to the fracture volume of the nth round, and obtain the fracture volume ratio.

[0142] Based on the fracture network morphology after well blockage in the nth round of fracturing, the fracture volume of the nth round is obtained; the ratio of the predicted fracture network volume to the fracture volume of the nth round is confirmed, and the fracture volume ratio of the nth round is obtained.

[0143] Optionally, the seam volume ratio = predicted seam mesh volume ÷ seam volume in the nth round.

[0144] S8014. If the fracture volume ratio is greater than or equal to the fracture volume ratio threshold, then it is determined that the target deep coal reservoir will continue to undergo the (n+1)th round of fracturing.

[0145] For example, the fracture volume ratio threshold is a critical value set based on actual conditions to evaluate the effectiveness of fracturing operations. Actual conditions include a combination of factors such as geological conditions, mining objectives, and economic benefits. This application does not impose specific limitations on the actual range of the fracture volume ratio threshold; the fracture volume ratio threshold is an appropriate value selected based on a comprehensive consideration of actual conditions.

[0146] If the fracture volume ratio is greater than or equal to the fracture volume ratio threshold, it indicates that the (n+1)th round of fracturing is effective and the reservoir stimulation is significant. Therefore, it is determined to continue fracturing the target deep coal reservoir for the (n+1)th round.

[0147] S8015. If the fracture volume ratio is less than the fracture volume ratio threshold, then the fracturing of the target deep coal reservoir shall be terminated.

[0148] If the fracture volume ratio is less than the fracture volume ratio threshold, it indicates that the current round of fracturing operations has failed to achieve the expected results. Therefore, the fracturing of the target deep coal reservoir is terminated.

[0149] Optionally, if the fracture volume ratio is less than the fracture volume ratio threshold, but a new simulated fracturing scheme for the (n+1)th round is obtained by adjusting the simulated fracturing scheme for the target deep coal reservoir, and the fracture volume ratio corresponding to the new simulated fracturing scheme for the (n+1)th round is greater than or equal to the fracture volume ratio threshold, then it is determined to continue fracturing the target deep coal reservoir for the (n+1)th round.

[0150] In one possible implementation, if the fracture volume ratio is less than the fracture volume ratio threshold, determine whether the number of adjustments is less than M. Further, if the number of adjustments is less than M, adjust the simulated fracturing scheme for the (n+1)th round corresponding to the target deep coal reservoir based on the fracture network morphology after well blockage in the nth round of fracturing, obtain a new simulated fracturing scheme for the (n+1)th round, and update the number of adjustments. For the new simulated fracturing scheme for the (n+1)th round, execute the step of using an unconventional fracture propagation model to predict the predicted fracture network morphology after the (n+1)th round of fracturing, based on the fracture network morphology after well blockage in the nth round of fracturing and according to the simulated fracturing scheme for the (n+1)th round corresponding to the target deep coal reservoir. Even further, if the number of adjustments is greater than or equal to M, terminate the fracturing of the target deep coal reservoir.

[0151] For example, the number of adjustments refers to the number of times the simulated fracturing scheme for the (n+1)th round corresponding to the target deep coal reservoir has been adjusted. Limiting the number of adjustments ensures the continuity and effectiveness of the simulation fracturing scheme adjustment process, avoids getting bogged down in an infinite number of adjustments, and guarantees overall efficiency.

[0152] When the fracture volume ratio is less than the fracture volume ratio threshold, the decision on whether to adjust the simulated fracturing scheme for the (n+1)th round corresponding to the target deep coal reservoir is made by confirming whether the number of adjustments is less than the maximum number of adjustments, M. Optionally, M is a positive integer. Those skilled in the art should understand that the value of M is set considering external influencing factors such as operational conditions, geological conditions, and EUR.

[0153] If the current number of adjustments has not yet reached the preset maximum number of adjustments M, the simulated fracturing scheme for the (n+1)th round is optimized by analyzing the fracture morphology, fracture distribution, and fracture connectivity in the fracture network after well blockage in the nth round of fracturing. This yields a new simulated fracturing scheme for the (n+1)th round and updates the number of adjustments. Optionally, the simulated fracturing scheme for the (n+1)th round includes: total fluid volume, total sand volume, and operational displacement.

[0154] For the new simulated fracturing scheme of the (n+1)th round, the steps of predicting the fracture network morphology after the well blockage in the (n)th round of fracturing will be repeated. Based on the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir, an unconventional fracture propagation model will be used to predict the fracture network morphology after the (n+1)th round of fracturing, so as to determine whether the new simulated fracturing scheme of the (n+1)th round can meet the requirements.

[0155] If, after multiple adjustments (i.e., the number of adjustments reaches or exceeds the preset maximum number M), the expected results are still not achieved, the fracturing of the target deep coal reservoir is terminated.

[0156] S802. If not, trigger the (n+1)th round of fracturing of the target deep coal reservoir.

[0157] If the fracturing of the target deep coal reservoir is not terminated, the next step will be carried out based on the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir. The simulated fracturing scheme of the (n+1)th round can be derived from the preliminary design or the results of previous simulations, or it can be optimized after multiple adjustments based on the feedback of the fracture network morphology after the well blockage in the nth round of fracturing.

[0158] S803. If so, terminate the fracturing of the target deep coal reservoir.

[0159] The multi-round fracturing determination method provided in this application predicts the fracturing effect of the (n+1)th round simulated fracturing scheme by simulating the fracture network morphology after well blockage in the nth round and the simulated fracturing scheme of the target deep coal reservoir in the (n+1)th round. Based on the predicted fracturing effect of the (n+1)th round simulated fracturing scheme, it determines whether to continue fracturing the target deep coal reservoir, avoiding unnecessary repeated fracturing and resource waste, while optimizing the mining strategy and improving mining efficiency.

[0160] Figure 9 A flowchart illustrating the multi-round fracturing method for deep coal reservoirs provided in this application embodiment. Figure 2 . Figure 9 exist Figure 1 The basic example details a multi-round fracturing method for deep coal reservoirs. For instance... Figure 9 As shown, the method includes:

[0161] This application selects Block A as the subject of study. Located in the southern part of the eastern edge of the Ordos Basin, this block geographically spans two major geological structural regions: the Yishan Slope and the Jinxi Fold Belt. Block A has a relatively simple geological structure and gentle reservoirs, providing favorable conditions for the exploration and development of oil and gas in deep coal reservoirs. Currently, the main target for deep coalbed methane exploration and development in Block A is the No. 8 coal seam. The No. 8 coal seam was formed in a lagoonal facies environment, with a thickness between 5 and 12 meters. The coal structure is mainly primary structure coal with well-developed cleavage, exhibiting a strong vitreous luster on the cleavage surfaces, indicating good reservoir performance. The coal reservoir is buried at a relatively deep depth, between 2000 and 2600 meters underground, falling into the category of deep coal reservoirs and possessing significant exploration and development potential.

[0162] Within Block A, well DJ55 was selected as the research object. DJ55 is a coalbed methane exploration well located deep in the Ordos Basin, primarily exploring the No. 8 coal seam of the Taiyuan Formation. The vertical depth of this coal seam in well DJ55 ranges from 2132.2 to 2137.4 meters, with a vertical thickness of 5.2 meters. In terms of geomechanical properties, the stress difference between the roof limestone and the coal seam in the No. 8 coal seam is 18.5 MPa, while the stress difference between the floor mudstone / sandy mudstone and the coal seam is 9.1 MPa. The relatively poor compressibility of the roof limestone and floor mudstone, coupled with the large stress difference between them and the coal seam, provides strong shielding capabilities, effectively limiting fracture propagation outside the coal reservoir and ensuring that fractures primarily extend within the coal reservoir. Therefore, well DJ55 and the No. 8 coal seam it contains possess unique geomechanical conditions and excellent coalbed methane reservoir potential.

[0163] S901. Obtain basic information about the target well and the simulated fracturing scheme corresponding to the target deep coal reservoir.

[0164] The basic data for the target well DJ55 includes geological data, well logging data, and core data. The parameters of the simulated fracturing scheme include fracturing cycle N, fracturing fluid type, total fluid volume, total sand volume, and discharge rate. Well logging data includes reservoir stress and mechanical properties; core data includes reservoir physical properties.

[0165] The parameters in the simulated fracturing scheme include: fracturing cycle M, fracturing fluid type, total fluid volume, total sand volume, and construction discharge rate.

[0166] Alternatively, the simulated fracturing scheme can be obtained directly or predicted using an unconventional fracture propagation model.

[0167] In one possible implementation, based on basic oil and gas well data and a fracture intersection discrimination criterion, the propagation mode after the intersection of fractures and structural planes formed by fracturing is determined. Combining the propagation mode and unconventional fracture propagation models, the fracture network morphology, reservoir stress evolution characteristics, and permeability evolution characteristics of different rounds of simulated fracturing schemes under fluid-structure interaction conditions are calculated. Based on the fracture network morphology and geological conditions, the EUR (Effective Urge) variation trend is predicted. Combining the fracture network morphology, reservoir stress evolution characteristics, permeability evolution characteristics, and predicted EUR variation trend, appropriate preset fracturing parameters are selected as the simulated fracturing scheme.

[0168] Table 1 shows the parameters of the simulated fracturing scheme for the target well DJ55 provided in the embodiments of this application. As shown in Table 1, the simulated fracturing scheme for the target well DJ55 is a multi-round fracturing. The first round uses a low-concentration guar gum fracturing fluid system, the second round uses a variable viscosity slickwater fracturing fluid system, and the third and subsequent rounds all use a low-concentration guar gum fracturing fluid system.

[0169] Table 1. Parameters of the Simulated Fracturing Scheme for Target Well DJ55

[0170] Round N Fracturing fluid type <![CDATA[Total liquid volume (m 3 )]]> <![CDATA[Total sand volume (m 3 )]]> <![CDATA[Construction displacement (m 3 / min)]]> 1 Low concentration guar gum fracturing fluid system 3000 400 11 2 Variable viscosity slippery water fracturing fluid system 3500 120 18 3 Low concentration guar gum fracturing fluid system 3000 400 11 … Low concentration guar gum fracturing fluid system 3000 400 11

[0171] S902. Based on the simulated fracturing scheme of the nth round, obtain the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing.

[0172] Based on the simulated fracturing scheme of the nth round, and combined with the fracture intersection discrimination criterion, the propagation mode of the fractures formed by fracturing and the structural surface after intersection is clarified. An unconventional fracture propagation model is used to calculate the fracture length, fracture height, and fracture network volume under fluid-structure interaction conditions, resulting in a fracture morphology feature map after the nth round of fracturing. For example, the fracture morphology feature map after the first round of fracturing is referenced. Figure 3 .

[0173] S903. Based on the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing, combined with the porosity elasticity theory and the stress sensitivity characteristics of coal and rock permeability, an unconventional fracture propagation model is used to predict and obtain the reservoir stress evolution characteristics and permeability evolution characteristics during the nth round of fracturing and subsequent well closure.

[0174] S904. Based on the reservoir stress evolution characteristics and permeability evolution characteristics during the nth round of well closure after pressure, the well closure time for the nth round is obtained.

[0175] Taking the first round as an example, the reservoir stress evolution characteristics corresponding to the first round are referenced. Figure 5The reference for determining the permeability evolution characteristics corresponding to the first round. Figure 7 Reservoir stress begins to decrease on the 4th day of well shut-in and gradually levels off by the 6th day. Therefore, the shut-in time based on reservoir stress is determined to be 4-6 days. The permeability evolution characteristics show a gradual increase in permeability between 6-8 days. Therefore, the shut-in time based on permeability is determined to be 6-8 days. To improve operational efficiency, the shut-in time corresponding to the nth round of fracturing is determined to be 6 days.

[0176] S905. Based on the n-round simulated fracturing scheme and the well shut-in time corresponding to the nth round of fracturing, obtain the hydraulic fracture morphology after the nth round of fracturing.

[0177] Based on the n-round simulated fracturing scheme and the well shut-in time corresponding to the nth round of fracturing, an unconventional fracture propagation model is adopted to determine the effects of fracturing and well shut-in on the initiation, propagation direction and final morphology of fractures, and to obtain the hydraulic fracture morphology after the nth round of fracturing.

[0178] Optionally, real-time information is acquired through monitoring methods such as microseismic analysis, steady-state electric field analysis, optical fiber analysis, and high-frequency pressure monitoring at the wellhead. Based on this real-time information, and building upon the prediction of the hydraulic fracture morphology after the nth round of fracturing using an unconventional fracture propagation model, the fracture network morphology is further characterized in detail to obtain a new hydraulic fracture morphology after the nth round of fracturing. The real-time information includes real-time wellhead pressure and real-time microseismic information.

[0179] Figure 10 These are schematic diagrams illustrating the hydraulic fracture morphology at each stage, as provided in the embodiments of this application. Figure 10 As shown, the hydraulic fracture morphology provided in this embodiment is... Figure 2 Based on this, the crack width and crack morphology of the hydraulic fracture are described in detail, including:

[0180] The fracture patterns include: the first round of hydraulic fracture patterns, the second round of hydraulic fracture patterns, the third round of hydraulic fracture patterns, the fourth round of hydraulic fracture patterns, the fifth round of hydraulic fracture patterns, and the sixth round of hydraulic fracture patterns.

[0181] The crack patterns in each cycle are represented by lines. Different colors of the lines indicate the width of the cracks. The redder the line, the wider the crack; the bluer the line, the narrower the crack. The crack widths shown in the diagram range from 0m to 16m.

[0182] The first-round hydraulic fracturing morphology represents the fracturing pattern obtained using a low-concentration guar gum fracturing fluid system. The purpose of this first-round hydraulic fracturing is to increase fracture length, establish the main framework of the fracture network, and achieve efficient extension of the main fracture structure within the natural fracture. Since the direction of maximum principal stress is east-west, without intervention, the fractures formed by hydraulic fracturing will propagate along this east-west direction.

[0183] The second-round hydraulic fracture morphology indicates fracturing using a variable viscosity slickwater fracturing fluid system. This system opens more cleavage fractures in the fracture network, forming branching fractures in the fracture width direction and promoting transverse fracture deflection and densification. Compared to the first-round hydraulic fracture morphology, the second-round hydraulic fracture morphology shows overall fracture extension in a north-south direction. Compared to low-concentration guar gum fracturing fluid systems, the variable viscosity slickwater fracturing fluid system has lower viscosity and lower flow resistance, which facilitates deeper penetration of the fracturing fluid into the reservoir. Simultaneously, its higher filtration efficiency promotes fracture complexity, making the fracture creation mechanism more inclined to open multi-branched, complex fracture networks.

[0184] The hydraulic fracture patterns of the third, fourth, fifth, and sixth rounds were all obtained using a concentrated guar gum fracturing fluid system. Compared with the first and second rounds, the fractures all extended in a north-south direction. After being subjected to the variable viscosity slickwater fracturing fluid system, the fractures changed direction, resulting in denser fractures with smaller widths, forming a narrow and dense fracture network along the direction of minimum stress.

[0185] S906. Determine the fracturing cycle based on the hydraulic fracture morphology after n rounds of fracturing.

[0186] Based on the hydraulic fracture morphology after n rounds of fracturing, the fracture volume and total fracture network volume of each round are obtained. The fracture volume ratio is determined based on the fracture volume of each round, and the fracturing round is determined by comparing the fracture volume ratio with a threshold value.

[0187] Figure 11 This is a schematic diagram showing the fracture volume and total fracture network volume for each round of fracturing, as provided in the embodiments of this application. Figure 11 The figure shows the trend of the total volume of the fracture network under different fracturing cycles, where:

[0188] The volume of the first round of fracturing was 520 m³. 3 The maximum fracture volume created in the second round of fracturing was 615 m³. 3 The volume of the third round of fracturing was 445 m³. 3 The volume of the fourth round of fracturing was 403 m³. 3 The volume of the fifth round of fracturing was 395 m³. 3 The volume of the fracture created in the sixth round of fracturing was 291 m³. 3 From the third round onwards, the volume of the suture gradually decreased.

[0189] Optionally, the fracture volume ratio threshold corresponding to the target well DJ55 can be set to 0.75.

[0190] The fracture volume ratio for the fourth fracturing round is determined as follows: Fracture volume of the fourth round ÷ Fracture volume of the third round = 403 ÷ 445 = 0.9. Since 0.9 is greater than 0.75, the fracture volume ratio for the fourth round is greater than the fracture volume ratio threshold, so the fourth round of fracturing continues.

[0191] Using the same calculation method, the fracture volume ratio for the 5th fracturing round was found to be 0.98. Since the fracture volume ratio for the 5th round was greater than the threshold, the 5th round of fracturing continued. The fracture volume ratio for the 5th round was 0.73. Since the fracture volume ratio for the 6th round was less than the threshold, the 6th round of fracturing was not performed. Therefore, the total number of fracturing rounds was determined to be 5.

[0192] The multi-round fracturing method for deep coal reservoirs provided in this application obtains basic data of the target well and a simulated fracturing scheme. Based on the simulated fracturing scheme, the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing is determined. Based on the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing, combined with real-time wellhead pressure and real-time microseismic information, reservoir stress evolution characteristics and permeability evolution characteristics that are more closely aligned with actual conditions are obtained. This ensures the flexibility and reliability of determining the shut-in time, allowing the shut-in time to guarantee fracture propagation and improve permeability. Subsequently, the fracture network morphology corresponding to hydraulic fracturing in the (n+1)th round of fracturing is determined based on the simulated fracturing scheme. The fracturing round is determined based on the fracture network morphologies corresponding to hydraulic fracturing in the nth and (n+1)th rounds of fracturing, avoiding over-fracturing and under-fracturing, achieving maximum reservoir stimulation, maximizing the release of oil and gas resources in the reservoir, and realizing a balanced and sufficient stimulation effect in deep coal reservoirs.

[0193] Figure 12 A schematic diagram of the structure of a multi-stage fracturing device for deep coal reservoirs provided in this application embodiment. Figure 4 As shown, the deep coal reservoir multi-round fracturing device 12 provided in this embodiment includes:

[0194] The acquisition module 121 is used to acquire the simulated fracturing scheme for the nth round corresponding to the target deep coal reservoir, where n is a positive integer and n is less than or equal to N, and N is an integer greater than or equal to 3. If n is 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a variable viscosity slickwater fracturing fluid system; if n is not 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a low concentration guar gum fracturing fluid system.

[0195] The processing module 122 is used to predict the fracture network morphology corresponding to hydraulic fracturing in the nth round based on the real-time wellhead pressure, real-time microseismic information and fracture network morphology after well blockage in the n-1th round of fracturing, according to the simulated fracturing scheme of the nth round, using an unconventional fracture propagation model.

[0196] The determination module 123 is used to determine the well shut-in time corresponding to the nth round of fracturing based on the fracture network morphology, real-time wellhead pressure and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing.

[0197] In one possible implementation, the determining module 123 is specifically used for:

[0198] Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing, the reservoir stress evolution characteristics and permeability evolution characteristics are obtained.

[0199] Based on the reservoir stress evolution characteristics and permeability evolution characteristics, the shut-in time corresponding to the nth round of fracturing is determined.

[0200] In one possible implementation, the determining module 123 is further configured to:

[0201] Real-time monitoring and acquisition of wellhead pressure and microseismic information are used to obtain real-time wellhead pressure and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing.

[0202] Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing, an unconventional fracture propagation model is used to predict and determine the reservoir stress evolution characteristics and permeability evolution characteristics of the target deep coal reservoir during the well shut-in process.

[0203] In one possible implementation, the determining module 123 is further configured to:

[0204] Based on the characteristics of reservoir stress evolution, the time of the first inflection point when the stress evolution trend slows down is obtained;

[0205] Based on the characteristics of permeability evolution, the time of the second inflection point when the permeability evolution trend slows down is obtained;

[0206] Based on the first inflection point time and the second inflection point time, determine the shut-in time corresponding to the nth round of fracturing.

[0207] In one possible implementation, if n is greater than or equal to 3, the acquisition module 121 is specifically used for:

[0208] Based on the fracture network morphology after well blockage in the nth round of fracturing and the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir, determine whether to terminate the fracturing of the target deep coal reservoir. The fracture network morphology includes the fracture volume.

[0209] If not, trigger the (n+1)th round of fracturing of the target deep coal reservoir.

[0210] In one possible implementation, the acquisition module 121 is further configured to:

[0211] Based on the fracture network morphology, reservoir stress evolution characteristics, and permeability evolution characteristics corresponding to hydraulic fracturing in the nth round of fracturing, an unconventional fracture propagation model is adopted to obtain the fracture network morphology after well blockage in the nth round of fracturing.

[0212] Based on the fracture network morphology after the well is shut down in the nth round of fracturing, and according to the simulated fracturing scheme of the n+1th round corresponding to the target deep coal reservoir, an unconventional fracture propagation model is used to predict the fracture network morphology after the n+1th round of fracturing. The predicted fracture network morphology includes the predicted fracture volume.

[0213] Determine the ratio of the predicted fracture network volume corresponding to the (n+1)th round of fracturing to the fracture volume of the nth round, and obtain the fracture volume ratio;

[0214] If the fracture volume ratio is greater than or equal to the fracture volume ratio threshold, then it is determined that the target deep coal reservoir will continue to undergo the (n+1)th round of fracturing.

[0215] If the fracture volume ratio is less than the fracture volume ratio threshold, the fracturing of the target deep coal reservoir is terminated.

[0216] In one possible implementation, the acquisition module 121 is further configured to:

[0217] If the joint volume ratio is less than the joint volume ratio threshold, determine whether the number of adjustments is less than M times;

[0218] If the number of adjustments is less than M, based on the fracture network morphology after the well is blocked in the nth round of fracturing, adjust the simulated fracturing scheme for the (n+1)th round corresponding to the target deep coal reservoir to obtain a new simulated fracturing scheme for the (n+1)th round, and update the number of adjustments.

[0219] For the new simulated fracturing scheme of the (n+1)th round, the following steps are taken: based on the fracture network morphology after the well is blocked in the fracturing of the nth round, and according to the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir, an unconventional fracture propagation model is used to predict and obtain the predicted fracture network morphology after the fracturing of the (n+1)th round.

[0220] If the number of adjustments is greater than or equal to M, the fracturing of the target deep coal reservoir is terminated.

[0221] The deep coal reservoir multi-round fracturing device provided in this embodiment can perform the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0222] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 13As shown, the electronic device 13 provided in this embodiment includes at least one processor 1301 and a memory 1302. Optionally, the device 13 further includes a communication component 1303. The processor 1301, memory 1302, and communication component 1303 are connected via a bus 1304.

[0223] In a specific implementation, at least one processor 1301 executes computer execution instructions stored in memory 1302, causing at least one processor 1301 to perform the above-described method.

[0224] The specific implementation process of processor 1301 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0225] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0226] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0227] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings of this application are not limited to a single bus or a single type of bus.

[0228] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0229] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed, implement any of the methods described above.

[0230] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0231] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in application-specific integrated circuits (ASICs). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0232] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0233] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0234] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0235] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0236] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0237] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for multi-round hydraulic fracturing of deep coal reservoirs, characterized in that, In multi-round fracturing, each round includes hydraulic fracturing and well shut-in. The multi-round fracturing method for deep coal reservoirs includes: Obtain the simulated fracturing scheme for the nth round corresponding to the target deep coal reservoir, where n is a positive integer, less than or equal to N, and N is an integer greater than or equal to 3. If n is 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a variable viscosity slickwater fracturing fluid system; if n is not 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a low concentration guar gum fracturing fluid system. Based on the real-time wellhead pressure, real-time microseismic information obtained in the (n-1)th round, and the fracture network morphology after well blockage in the (n-1)th round of fracturing, according to the simulated fracturing scheme of the nth round, the unconventional fracture propagation model is used to predict the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing. Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing, the shut-in time corresponding to the nth round of fracturing is determined.

2. The multi-round fracturing method for deep coal reservoirs according to claim 1, characterized in that, The step of determining the well shut-in time corresponding to the nth round of fracturing based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round includes: Based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing, the reservoir stress evolution characteristics and permeability evolution characteristics are obtained. Based on the reservoir stress evolution characteristics and permeability evolution characteristics, the shut-in time corresponding to the nth round of fracturing is determined.

3. The multi-round fracturing method for deep coal reservoirs according to claim 2, characterized in that, The process of obtaining reservoir stress evolution characteristics and permeability evolution characteristics based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing includes: Real-time monitoring and acquisition of wellhead pressure and microseismic information are used to obtain the real-time wellhead pressure and real-time microseismic information corresponding to hydraulic fracturing in the nth round of fracturing. Based on the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing, the real-time wellhead pressure, and the real-time microseismic information, an unconventional fracture propagation model is used to predict and determine the reservoir stress evolution characteristics and permeability evolution characteristics corresponding to the target deep coal reservoir during the well shut-in process.

4. The multi-round fracturing method for deep coal reservoirs according to claim 2, characterized in that, The determination of the shut-in time corresponding to the nth round of fracturing based on reservoir stress evolution characteristics and permeability evolution characteristics includes: Based on the reservoir stress evolution characteristics, the time of the first inflection point when the stress evolution trend slows down is obtained; Based on the aforementioned permeability evolution characteristics, the time of the second inflection point when the permeability evolution trend slows down is obtained; Based on the first inflection point time and the second inflection point time, determine the shut-in time corresponding to the nth round of fracturing.

5. The multi-round fracturing method for deep coal reservoirs according to any one of claims 1 to 4, characterized in that, If n is greater than or equal to 3, it also includes: Based on the fracture network morphology after well blockage in the nth round of fracturing and the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir, determine whether to terminate the fracturing of the target deep coal reservoir. The fracture network morphology includes the fracture volume. If not, trigger the (n+1)th round of fracturing of the target deep coal reservoir.

6. The multi-round fracturing method for deep coal reservoirs according to claim 5, characterized in that, The step of determining whether to terminate the fracturing of the target deep coal reservoir based on the fracture network morphology after well blockage in the nth round of fracturing and the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir includes: Based on the fracture network morphology, reservoir stress evolution characteristics, and permeability evolution characteristics corresponding to hydraulic fracturing in the nth round of fracturing, an unconventional fracture propagation model is adopted to obtain the fracture network morphology after well blockage in the nth round of fracturing. Based on the fracture network morphology after the well is shut down in the nth round of fracturing, and according to the simulated fracturing scheme of the n+1th round corresponding to the target deep coal reservoir, an unconventional fracture propagation model is used to predict the predicted fracture network morphology after the n+1th round of fracturing. The predicted fracture network morphology includes the predicted fracture volume. Determine the ratio of the predicted fracture network volume corresponding to the (n+1)th round of fracturing to the fracture volume of the nth round, and obtain the fracture volume ratio; If the fracture volume ratio is greater than or equal to the fracture volume ratio threshold, then it is determined that the target deep coal reservoir will continue to undergo the (n+1)th round of fracturing. If the fracture volume ratio is less than the fracture volume ratio threshold, the fracturing of the target deep coal reservoir is terminated.

7. The multi-round fracturing method for deep coal reservoirs according to claim 6, characterized in that, Also includes: If the joint volume ratio is less than the joint volume ratio threshold, determine whether the number of adjustments is less than M times; If the number of adjustments is less than M, based on the fracture network morphology after the well is blocked in the nth round of fracturing, adjust the simulated fracturing scheme for the (n+1)th round corresponding to the target deep coal reservoir to obtain a new simulated fracturing scheme for the (n+1)th round, and update the number of adjustments. For the new simulated fracturing scheme of the (n+1)th round, the following steps are performed: based on the fracture network morphology after the well is blocked in the fracturing of the nth round, and according to the simulated fracturing scheme of the (n+1)th round corresponding to the target deep coal reservoir, an unconventional fracture propagation model is used to predict and obtain the predicted fracture network morphology after the (n+1)th round of fracturing. If the number of adjustments is greater than or equal to M, the fracturing of the target deep coal reservoir is terminated.

8. A multi-round fracturing device for deep coal reservoirs, characterized in that, include: The acquisition module is used to acquire the simulated fracturing scheme for the nth round corresponding to the target deep coal reservoir, where n is a positive integer and n is less than or equal to N, and N is an integer greater than or equal to 3. If n is 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a variable viscosity slickwater fracturing fluid system; if n is not 2, the fracturing fluid system corresponding to the simulated fracturing scheme is a low concentration guar gum fracturing fluid system. The processing module is used to predict the fracture network morphology corresponding to hydraulic fracturing in the nth round of fracturing based on the real-time wellhead pressure, real-time microseismic information and fracture network morphology after well blockage in the nth round of fracturing, according to the simulated fracturing scheme of the nth round, using an unconventional fracture propagation model. The determination module is used to determine the well shut-in time corresponding to the nth round of fracturing based on the fracture network morphology, real-time wellhead pressure, and real-time microseismic information corresponding to the hydraulic fracturing in the nth round of fracturing.

9. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

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