An intelligent monitoring and control system for staged fracturing of coalbed methane mining

Abstract

The present invention belongs to the technical field of coalbed methane exploitation fracturing control, and specifically discloses an intelligent monitoring and control system for segmented fracturing of coalbed methane exploitation. Rock samples are collected from target coal seams, and microstructure detection is performed on the collected rock samples to eliminate rock samples with natural cracks. Then, equal stresses in different directions are applied to the rock samples by a servo motor to simulate fracturing, and crack expansion is monitored after the fracturing simulation. Thus, the crack expansion direction of the rock sample is associated with the stress application direction, and the dominant microstructure distribution characteristics of the crack expansion corresponding to the rock sample are obtained, thereby deepening the understanding of the crack expansion mechanism to the greatest extent, increasing the clarity of the crack expansion direction, and facilitating the optimization of the crack expansion effect when performing fracturing operations in coal seams without natural cracks, thereby improving the accuracy and effectiveness of fracturing.

Description

Technical Field

[0001] The invention belongs to the technical field of coalbed methane exploitation fracturing control, and specifically discloses an intelligent monitoring and control system for coalbed methane exploitation staged fracturing. Background Art

[0002] Coalbed methane is an unconventional natural gas resource stored in coal seams. It can be used as a clean energy source to increase the diversity of energy supply and reduce dependence on traditional fossil fuels. In coalbed methane mining, staged fracturing is an effective technical means to improve the recovery rate of coalbed methane. By implementing hydraulic fracturing at different depths in the wellbore, the gas flow conditions are improved by increasing the length of the formation fractures, thereby increasing gas production. Therefore, the monitoring and control in coalbed methane mining mainly focuses on the monitoring and control of formation fractures, specifically by monitoring the expansion direction of the fractures to ensure the effective expansion of the fractures.

[0003] In the prior art, a Chinese invention patent publication number CN109252847B proposes a method and device for controlling the expansion of coal seam cracks by alternating water and low-temperature fluid fracturing. The method aims to solve the problem that hydraulic fractures are easy to expand along natural cracks in coal seams, but are mainly concentrated near the wellbore, and it is difficult to effectively fracture distant coal seams, resulting in a small range of reservoir transformation. Specifically, water is injected into the coalbed methane well for water fracturing to form artificial fractures that expand along natural fractures, and then low-temperature fluid is injected into the coalbed methane well. The expansion force generated by the freezing of low-temperature water expands the existing fractures, generating a line that expands along the direction of the maximum principal ground stress of the formation. Artificial main cracks are created, and segmented freezing of coal seams is achieved through alternating fracturing with water and low-temperature fluids, thereby controlling the direction of artificial cracks and increasing the crack expansion rate. In this invention, although low-temperature fluids help to increase the crack expansion rate, due to the lack of specific data support, it is impossible to obtain accurate optimization parameters in actual operations, which makes it more difficult to predict the crack expansion effect and is prone to waste of resources due to blindly increasing the injection rate of low-temperature fluids. In addition, this invention relies on the natural cracks in the coal seams. For coal seams without natural cracks, this method cannot effectively control the direction of the cracks, limiting the scope of application.

[0004] Another Chinese invention patent publication number CN114607331B proposes a horizontal well segmented volume fracturing simulation test device and method. This method collects rock samples and uses a servo motor to apply stress for fracturing simulation. It can simulate the process of horizontal well segmented fracturing and study the effects of different segmented fracturing sequences and parameters on crack expansion. Although the invention can obtain accurate optimization parameters for crack expansion through fracturing simulation data, it ignores the effect of the microstructure of the rock sample on crack expansion. When stress is applied to the rock sample, the crack expansion direction will be affected by the natural cracks in the presence of natural cracks, and may be affected by the distribution of the rock sample microstructure in the absence of natural cracks. This leads to an incomplete understanding of the crack expansion mechanism and increases the uncertainty of the crack expansion direction, making the obtained optimization parameters inaccurate and affecting the control of the fracturing effect. Summary of the invention

[0005] In order to solve the above technical problems or at least partially solve the above technical problems, the present application provides an intelligent monitoring and control system for segmented fracturing of coalbed methane extraction, which uses fracturing simulation to obtain the correlation between the crack propagation direction and the rock microstructure for coal seams without natural cracks, thereby achieving precise optimization of coal seam fracturing control.

[0006] The purpose of the present invention can be achieved through the following technical solutions: an intelligent monitoring and control system for staged fracturing of coalbed methane mining, including: a rock sample collection module, used for collecting rock samples from a target coal seam.

[0007] The rock sample microstructure detection module is used to detect natural cracks in the collected rock samples, thereby eliminating rock samples with natural cracks, retaining the remaining rock samples as usable rock samples, and performing microstructure detection on the usable rock samples to obtain microstructure distribution characteristics.

[0008] The rock sample grouping module is used to group the available rock samples into several rock sample groups according to microstructure detection, and obtain the microstructure distribution characteristics corresponding to each rock sample group.

[0009] The rock sample fracturing simulation module is used to perform perforation operations on each rock sample group, and use a servo motor to apply equal stress in different stress directions to each rock sample group. Then, the hydraulic servo pump is activated to inject fracturing fluid into the perforations of each rock sample group for hydraulic fracturing. At the same time, the injection pressure is monitored to identify whether the hydraulic fracturing is completed. When the hydraulic fracturing is completed, the low-temperature fluid is injected into the rock sample through the perforations, and the injection rate is controlled and monitored during the injection process.

[0010] The crack expansion monitoring module is used to monitor crack expansion during low-temperature fluid fracturing to obtain the crack expansion direction and crack expansion rate.

[0011] The fracture extension correlation module is used to correlate the fracture extension direction of each rock sample in each rock sample group with the stress application direction of the rock sample, and to correlate the fracture extension rate with the injection rate, so as to comprehensively obtain fracture extension correlation information.

[0012] The coal seam fracturing control module is used to perform actual coal seam fracturing control based on fracture extension correlation information.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The present invention collects rock samples from the target coal seam, performs microstructural detection on the collected rock samples, removes rock samples with natural cracks, and then uses a servo motor to apply equal stresses in different directions to the rock samples for fracturing simulation, and monitors the crack expansion after the fracturing simulation. By associating the crack expansion direction of the rock sample with the stress application direction, the dominant microstructural distribution characteristics of the crack expansion corresponding to the rock sample are obtained, which deepens the understanding of the crack expansion mechanism to the greatest extent and increases the clarity of the crack expansion direction, which is conducive to optimizing the crack expansion effect when performing fracturing operations in coal seams without natural cracks, and improving the accuracy and effectiveness of fracturing.

[0014] 2. When the present invention simulates the fracturing of rock samples, water fracturing is first performed, and then low-temperature fluid is injected for low-temperature fracturing. During this process, the injection rate and the crack extension rate are monitored in real time, and the injection rate is associated with the crack extension rate to determine the ideal injection rate and the critical injection rate. Applying these optimized parameters to the actual coalbed methane fracturing control can effectively avoid the waste of resources caused by excessive injection of low-temperature fluid, thereby achieving effective fracturing while reducing costs, and has high practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0016] Figure 1 It is a schematic diagram of the connection of each module of the system of the present invention.

[0017] Figure 2 It is a schematic diagram of the rock sample grouping operation in the present invention.

[0018] Figure 3 It is a schematic diagram of the implementation of actual coal seam fracturing control based on fracture extension correlation information in the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Reference Figure 1 As shown, an intelligent monitoring and control system for staged fracturing of coalbed methane mining includes a rock sample collection module, a rock sample microstructure detection module, a rock sample grouping module, a rock sample fracturing simulation module, a crack extension monitoring module, a crack extension association module and a coalbed fracturing control module, wherein the rock sample collection module is connected to the rock sample microstructure detection module, the rock sample microstructure detection module is connected to the rock sample grouping module, the rock sample grouping module is connected to the rock sample fracturing simulation module, the rock sample fracturing simulation module is connected to the crack extension monitoring module, the crack extension monitoring module, the rock sample microstructure detection module and the rock sample fracturing simulation module are all connected to the crack extension association module, and the crack extension association module is connected to the coalbed fracturing control module.

[0021] The rock sample collection module is used to collect rock samples from the target coal seam.

[0022] It should be pointed out that since the present invention studies the expansion mechanism of cracks under non-natural crack conditions, it is necessary to collect rock samples from outside the crack zone when collecting rock samples. This can eliminate the interference of natural cracks and better study the crack expansion mechanism under non-natural crack conditions. At the same time, it is necessary to collect multiple rock samples and locate and record the rock sample collection positions.

[0023] The rock sample microstructure detection module is used to perform natural crack detection on the collected rock samples, thereby eliminating rock samples with natural cracks, retaining the remaining rock samples as usable rock samples, and performing microstructure detection on the usable rock samples to obtain microstructure distribution characteristics.

[0024] Applied to the above scheme, the natural crack detection of the collected rock samples can be carried out by three-dimensional scanning. For example, computer tomography is used to provide a three-dimensional structural image of the rock sample. The specific operation is to place the rock sample on the sample table of the scanner to ensure that the sample is fixed and stable, and use computer tomography to scan the rock sample at multiple angles to generate a three-dimensional image. Through image reconstruction software, the scan data is reconstructed into a three-dimensional image to display the internal structure of the rock sample. Finally, the three-dimensional image is processed using image analysis software to identify and measure the size, shape and distribution of the cracks.

[0025] It should be understood that after collecting rock samples from outside the fracture zone, natural fracture detection is carried out, thereby eliminating rock samples with natural fractures. This can strengthen the guarantee that the research object is a purely artificial fracture condition, thereby better controlling and understanding the fracture propagation mechanism.

[0026] Further application of the above scheme, the microstructure detection of rock samples is essentially to detect the mineral distribution, rock layer structure distribution, and pore distribution status. The mineral distribution mainly refers to the arrangement direction of minerals such as quartz, feldspar, clay, etc. in the rock sample. The rock layer structure distribution mainly refers to the arrangement direction of bedding structures such as folds and faults in the rock sample. The pore distribution mainly refers to the size arrangement direction of pore types in the rock sample such as primary pores and secondary pores.

[0027] The mineral distribution detection of the above-mentioned rock samples can be carried out by X-ray fluorescence spectroscopy. The specific operations are as follows: clean the surface of the rock sample to ensure that the surface is flat, then place the rock sample on the sample table of the X-ray fluorescence spectrometer to ensure that the sample position is fixed, start the X-ray fluorescence spectrometer, scan the surface of the rock sample, collect fluorescence spectrum data, and determine the types and contents of various elements in the rock sample by analyzing the fluorescence spectrum, and then infer the distribution of minerals.

[0028] The above-mentioned mineral distribution detection can be carried out by neutron activation analysis, and the specific operation is as follows: clean the surface of the rock sample to ensure that the surface is flat, place the rock sample on the sample table of the neutron activation analysis instrument to ensure that the sample position is fixed, start the neutron activation analysis instrument, irradiate the rock sample with a neutron beam, collect gamma-ray data of radioactive nuclides, and determine the types and contents of various elements in the rock sample by analyzing the energy and intensity of gamma-rays, thereby inferring the distribution of minerals.

[0029] The above-mentioned mineral distribution detection can also be carried out by infrared spectroscopy. The specific operation is as follows: clean the surface of the rock sample to ensure that the surface is flat, place the rock sample on the sample table of the infrared spectrometer to ensure that the sample position is fixed, start the infrared spectrometer, irradiate the surface of the rock sample with infrared light, collect absorption spectrum data, and identify the chemical bonds and mineral composition of the rock sample by analyzing the absorption spectrum to infer the distribution of minerals.

[0030] The above-mentioned mineral distribution detection methods are all non-destructive testing, which can obtain the mineral distribution information of the rock sample without destroying the original structure of the rock sample, while avoiding the impact of rock sample destruction on fracturing simulation.

[0031] The rock structure distribution and pore distribution of the above-mentioned rock samples can be detected by computer tomography, which is also a non-destructive test.

[0032] See also Figure 2As shown, the rock sample grouping module is used to group available rock samples into several rock sample groups according to microstructure detection, and obtain the microstructure distribution characteristics corresponding to each rock sample group.

[0033] Preferably, the available rock samples are grouped as follows: the available rock samples that are retained are numbered, and each available rock sample is extracted in sequence according to the numbering sequence as a main rock sample to form a main rock sample set with other rock samples.

[0034] In the above operation example, assuming that the reserved rock samples are numbered 1, 2, 3, 4, 5, 6, 7, and 8, the available rock sample numbered 1 is used as the main rock sample to form the main rock sample set. The main rock sample set consisting of the available rock sample numbered 2 as the main rock sample is The main rock sample set consisting of the available rock sample numbered 3 as the main rock sample is The main rock sample set consisting of the available rock sample numbered 4 as the main rock sample is The main rock sample set consisting of the available rock sample numbered 5 as the main rock sample is , until the available rock sample numbered 7 is used as the main rock sample to form the main rock sample set. .

[0035] In the main rock sample set, the main rock sample and other rock samples are compared according to the microstructure detection results to calculate the microstructure similarity between the main rock sample and other rock samples, and compared with the similarity threshold initially set by the system. For example, the similarity threshold is 0.9, and other rock samples whose microstructure similarity reaches the similarity threshold are selected from them to form a rock sample group with the main rock sample.

[0036] In a further example of the above operation, in In the main rock sample set, it is assumed that the microstructural similarity of 1 and 2, and 1 and 6 reaches the similarity threshold, then rock samples 2 and 6 are grouped with the main rock sample 1 to form a rock sample group.

[0037] In the manner that the above scheme can be implemented, the main rock sample is concentrated and the main rock sample and other rock samples are compared similarly according to the microstructure detection results. Specifically, the mineral arrangement direction, rock formation structure arrangement direction, and pore arrangement direction of the main rock sample and other rock samples can be converted into feature vectors, each feature vector containing multiple directional feature values, such as mineral arrangement direction feature vector: [mineral 1 direction, mineral 2 direction, ..., mineral n direction], rock formation structure arrangement direction feature vector: [stratification direction, fold direction, fault direction], pore arrangement direction feature vector: [pore 1 direction, pore 2 direction, ..., pore m direction], and then the direction data of the main rock sample and other rock samples belonging to the same mineral, the same rock formation, and the same pore in the mineral arrangement direction, rock formation structure arrangement direction, and pore arrangement direction are calculated using the direction cosine similarity calculation formula to calculate the similarity of the direction feature vectors to obtain the similarity corresponding to the mineral arrangement direction, rock formation structure arrangement direction, and pore arrangement direction, wherein the direction cosine similarity calculation formula is: , where , represents two directional eigenvectors, represents the dot product of vectors, , The modulus of the vector is represented, and weights are assigned to the mineral arrangement direction, rock structure arrangement direction, and pore arrangement direction. Finally, the similarities corresponding to the mineral arrangement direction, rock structure arrangement direction, and pore arrangement direction are combined with the weights to perform weighted average calculation to obtain the microstructural similarity between the main rock sample and other rock samples.

[0038] In the above example, it is assumed that there are two rock samples with mineral arrangement direction feature vectors: , , use direction cosine similarity to calculate similarity , ,at this time , , , substitute the data into the calculation formula .

[0039] It should be added that, when assigning weights to the mineral arrangement direction, rock structure arrangement direction, and pore arrangement direction, considering that the purpose is to study the mechanism of crack propagation, higher weights can be assigned to the mineral arrangement direction and rock structure arrangement direction. This is because the influence of the mineral arrangement direction and rock structure arrangement on crack propagation is more important. By way of example, the weight values ​​assigned to the mineral arrangement direction, rock structure arrangement direction, and pore arrangement direction can be 0.4, 0.4, and 0.2, respectively.

[0040] The present invention groups the collected rock samples according to the microstructure detection results so that rock samples with similar microstructures can be grouped together, which can provide the crack extension conditions of similar rock samples for subsequent rock sample fracturing simulation, avoid random errors caused by crack extension mechanism analysis based on the crack extension conditions of a single rock sample, and help improve the representativeness and reliability of the analysis results.

[0041] The rock sample fracturing simulation module is used to perform perforation operations on each rock sample group, and use a servo motor to apply equal stress in different stress directions to each rock sample group, and then activate the hydraulic servo pump to inject fracturing fluid into the perforations of each rock sample group for hydraulic fracturing, and monitor the injection pressure to identify whether the hydraulic fracturing is completed. When the hydraulic fracturing is completed, the low-temperature fluid is injected into the rock sample through the perforations, and the injection rate control monitoring is performed during the injection process.

[0042] The above-mentioned low-temperature fluid can be liquid nitrogen, propylene glycol solution, etc.

[0043] It should be noted that the purpose of perforating the rock samples before fracturing simulation is to simulate the perforation process in actual fracturing operations to ensure that the experimental conditions are consistent with the actual working conditions. The holes obtained through the perforation operation can be used as the starting points of the cracks to help study the process of crack expansion from these holes.

[0044] The specific perforating operation mentioned above is to select appropriate perforating equipment, such as a perforating gun or a perforating drill bit, calibrate the perforating equipment, and perform the perforating operation at a specified position (such as a center position) of the rock sample.

[0045] In the above preferred perforating operation, the rock samples in each rock sample group are perforated at the same position and using the same perforating parameters, wherein the perforating parameters may be perforation diameter, perforation depth, perforation angle, etc. This ensures that the experimental conditions of all rock samples are consistent, avoids the introduction of additional variables due to differences in perforation positions and parameters, and through unified perforating conditions, it is easier to compare and analyze the experimental results of different rock sample groups and evaluate the effects of different microstructures on crack propagation.

[0046] In the above operation example, it is assumed that there are three rock sample groups, each group contains 5 rock samples, and the microstructure of each rock sample is similar. By perforating at the center position of each rock sample, the perforation depth is 10 mm, and the perforation angle is perpendicular to the rock sample surface. Such operation ensures that the perforation conditions of all rock samples are consistent, thereby improving the comparability and reliability of the experimental results.

[0047] It should be added that when perforating a rock sample, multiple perforations can be performed on the rock sample to study the crack propagation at different locations.

[0048] After the perforating operation, the servo motor is used to apply equal stress in different stress directions to each rock sample group. In this operation, the servo motor is an electric motor that produces rotational motion. A stable loading frame is designed to fix the rock sample and the servo motor, and then a connecting device (such as a push rod, a pressure plate, etc.) is used to connect the output shaft of the servo motor to the rock sample.

[0049] Generally speaking, the servo motor applies stress to the rock sample in three directions: vertical, horizontal, and inclined. The vertical stress is to fix the rock sample vertically in the loading frame, and the servo motor contacts the top or bottom of the rock sample through the push rod, and the vertical stress is applied to the rock sample through the linear movement of the servo motor. The horizontal stress is to fix the rock sample horizontally in the loading frame, and the servo motor contacts the side of the rock sample through the push rod, and the horizontal stress is applied to the rock sample through the linear movement of the servo motor. The inclined stress is to fix the rock sample in the loading frame at an angle, and the servo motor contacts the inclined surface of the rock sample through the push rod, and the inclined stress is applied to the rock sample through the linear movement of the servo motor.

[0050] The present invention ensures that the stress on the rock sample in various directions is evenly distributed by applying equal stress to the rock sample in different directions, thereby avoiding the situation where the crack only expands along a certain direction due to excessive stress in that direction, resulting in a single crack expansion path and being unable to fully reflect the relationship between the microstructure of the rock sample and the crack expansion.

[0051] After stress is applied to the rock sample, high-pressure liquid pressure is generated by injecting fracturing fluid into the perforations, which causes the perforation channels in the rock sample to expand and form cracks. During this process, the injection pressure of the fracturing fluid usually goes through a gradual rise stage, eventually reaching a peak and tending to stabilize. When the injection pressure stabilizes, it indicates that the crack expansion has reached the expected state and the fracturing process is basically completed. Subsequently, the crack expansion rate is further increased by injecting low-temperature fluid.

[0052] Therefore, when injecting low-temperature fluid, it is necessary to determine whether hydraulic fracturing is completed. For specific identification of whether hydraulic fracturing is completed, refer to the following process: the injection pressure monitored in real time during hydraulic fracturing is subtracted from the injection pressure at the previous monitoring moment, and the absolute value is taken, and compared with the set equilibrium pressure difference. For example, the equilibrium pressure difference is 0.1 MPa. If the pressure difference at a certain monitoring moment reaches the equilibrium pressure difference, the monitoring moment is recorded as a stable monitoring moment.

[0053] The duration of the stable monitoring moment is recorded and compared with the set effective duration. For example, the effective duration is 5 minutes. If the duration of the stable monitoring moment reaches the effective duration, the completion of hydraulic fracturing is recognized at the current moment.

[0054] The present invention can avoid misidentification of hydraulic fracturing due to a short-term, non-continuous stable state by performing duration statistics after identifying the stable monitoring moment. This ensures that the hydraulic fracturing process is considered complete only after the stable state continues for a set effective duration.

[0055] More specifically, the cryogenic fluid injection rate control monitoring is performed as follows: the injection rate is gradually increased while injecting the cryogenic fluid into the rock sample through perforations, and the injection rate is monitored in real time.

[0056] The gradual increase in the injection rate mentioned above can increase the driving force of the cryogenic fluid in the rock sample, causing the fractures to expand more rapidly.

[0057] It should be noted that during the fracturing simulation of rock samples, attention should be paid to: monitoring the environmental conditions of the coal seam at the sampling location when collecting rock samples, where the environmental conditions may include temperature, humidity, etc.

[0058] In the fracturing simulation operation of each rock sample group, the fracturing environment is kept consistent with the coal seam environmental conditions at the sampling location. This is done to ensure that the experimental conditions are as consistent as possible with the actual working conditions and to improve the reliability and representativeness of the experimental results.

[0059] The crack extension monitoring module is used to monitor crack extension during low-temperature fluid fracturing to obtain crack extension direction and crack extension rate.

[0060] The above-mentioned crack expansion monitoring can use acoustic emission monitoring, specifically, by installing acoustic emission sensors around the rock sample to monitor the acoustic emission activities inside the rock sample, so as to infer the expansion of the crack.

[0061] It should be known that the principle of using acoustic emission to monitor crack expansion is: when the cracks inside the rock sample expand or break, elastic waves, namely acoustic emission signals, are released. These elastic wave signals can be captured by acoustic emission sensors installed around the rock sample, and the expansion direction and expansion speed of the cracks are inferred by analyzing the captured acoustic emission signals. The specific operations are as follows: During the low-temperature fluid fracturing of the rock sample, the acoustic emission sensor is used to record the signal captured by the acoustic emission sensor in real time, and the acoustic emission signal is amplified by a preamplifier to ensure the clarity and accuracy of the signal, and then the collected acoustic emission signal is stored in a computer, and the collected acoustic emission signal is processed using signal processing software to extract key parameters such as signal amplitude, frequency, duration, etc., and then the location of the acoustic emission source is determined through a multi-sensor array and time difference positioning technology, thereby inferring the expansion direction of the crack; then the crack expansion speed is calculated by analyzing the time series of the acoustic emission signal. The crack expansion speed can usually be estimated by calculating the number of acoustic emission events or energy changes per unit time.

[0062] The present invention uses acoustic emission to monitor crack expansion. On the one hand, it can continuously record the entire process of crack expansion without being limited by time. On the other hand, acoustic emission monitoring is a non-destructive testing technology that does not require physical cutting or destruction of rock samples, and can maintain the integrity and original state of the rock samples. On the other hand, acoustic emission sensors are very sensitive to tiny crack expansion and fracture activities, and can capture subtle crack expansion signals, which helps to improve the high sensitivity of crack expansion monitoring.

[0063] The crack extension association module is used to associate the crack extension direction of each rock sample in each rock sample group with the rock sample stress application direction, and to associate the crack extension rate with the injection rate to obtain crack extension association information.

[0064] Preferably, the crack extension direction of each rock sample in each rock sample group is associated with the rock sample stress application direction by the following process: the crack extension direction of each rock sample in each rock sample group is compared with the stress application direction corresponding to the rock sample group to obtain the angle between the crack extension direction and each stress application direction.

[0065] The angles between the crack propagation direction and the stress application directions are compared to extract the maximum and minimum angles, and the angle range between the maximum and minimum angles is calculated, which is then compared with the allowable range configured by the system. When the angle range is greater than the allowable range, it is identified that there is a tendency in the crack propagation direction. At this time, the stress application direction corresponding to the minimum angle is selected as the principal stress direction of the crack.

[0066] It should be understood that when isotropic stress is applied to a rock sample, the crack propagation direction should theoretically be between these stress directions, and there is no significant propagation tendency. However, in actual experiments, due to the uneven distribution of the rock sample microstructure, crack propagation often shows a clear tendency in a certain direction.

[0067] It is further understood that the reason why the extreme value of the angle between the crack propagation direction and the stress application direction is used to reflect the tendency of the crack propagation direction is that the angle range refers to the difference between the maximum angle and the minimum angle among all the angles between the crack propagation directions and the stress application directions, which quantifies the degree of change of the crack propagation direction between different stress application directions. If the crack propagation direction is evenly distributed between the stress application directions, then the variation range of all angles will be very small, and the angle range will also be small. If the crack propagation direction shows an obvious tendency in a certain direction, then some angles will be significantly larger or smaller than other angles, resulting in an increase in the angle range. By setting an allowable angle range threshold, reliable identification of whether there is a tendency in the crack propagation direction can be achieved.

[0068] It should also be understood that when identifying the tendency of crack propagation direction, the stress application direction corresponding to the minimum angle is taken as the principal stress direction of the crack because the smaller the angle between the crack propagation direction and the stress application direction, the more direct the effect of the stress and the greater the driving force for crack propagation.

[0069] Based on the principal stress direction of the fracture corresponding to each rock sample in each rock sample group, the microstructure distribution characteristics of the rock sample in the principal stress direction of the fracture are retrieved to analyze which microstructure arrangement directions are consistent with the principal stress direction of the fracture.

[0070] The microstructural distribution characteristics of each rock sample in the same rock sample group in the direction of the principal stress of the fracture are compared, and the common microstructural distribution characteristics are extracted as the dominant microstructural distribution characteristics of the fracture extension corresponding to different rock samples.

[0071] In the example of the above scheme, assuming that the microstructural distribution characteristics of the five rock samples in the rock sample group in the direction of the principal stress of the fracture are respectively the mineral arrangement direction, the rock layer structure arrangement direction, the mineral arrangement direction, the mineral arrangement direction and the pore arrangement direction, then the mineral arrangement direction is taken as the dominant microstructural distribution characteristic of the fracture extension corresponding to the rock sample group.

[0072] Further preferably, the fracture growth rate is associated with the injection rate as follows: the fracture growth rate monitored in real time in fracture growth monitoring and the injection rate monitored in real time in low-temperature fracturing are time-mapped to obtain a plurality of mapping groups, each mapping group consisting of a fracture growth rate and an injection rate.

[0073] The above time mapping can ensure that the data of the fracture propagation rate and the injection rate are synchronized in time, that is, the data of the two parameters at the same time point can correspond one to one.

[0074] Arrange the mapping groups in chronological order, and extract the injection rate of each mapping group in sequence according to the arrangement order, and then divide the injection rate of the previous mapping group by the difference to obtain the injection rate increase of each mapping group. Similarly, compare the crack extension rate of each mapping group with the crack extension rate of the previous mapping group to calculate the crack extension increase of each mapping group.

[0075] The crack expansion increase of each mapping group is compared with the effective increase set by the system, where the effective increase is a pre-set threshold value used to determine whether the change in the crack expansion rate is significant. For example, the effective increase is 0.3. If the crack expansion increase of a mapping group is lower than the effective increase, the mapping group is used as the critical mapping group, and the crack expansion increase of the mapping group after the critical mapping group is compared with the effective increase. The duration that the crack expansion increase continues to be lower than the effective increase is counted and compared with the effective duration set by the system. If the crack expansion increase is still lower than the effective increase after the effective duration is reached, the injection rate in the critical mapping group is recorded as the critical injection rate.

[0076] It should be pointed out that, under normal circumstances, the crack growth rate increases with the increase of cryogenic fluid injection rate, but this increase is not unlimited. When the crack growth rate reaches a certain threshold, even if the injection rate of cryogenic fluid is further increased, the crack growth rate will not increase significantly. This is because the crack growth rate tends to saturation due to the limitations of various physical and mechanical factors during the crack growth process.

[0077] The crack extension increases of all mapping groups before the critical mapping group are compared, and the mapping group corresponding to the maximum crack extension increase is extracted as the ideal mapping group, and the injection rate in the ideal mapping group is recorded as the ideal injection rate.

[0078] See also Figure 3 As shown, the coal seam fracturing control module is used to perform actual coal seam fracturing control based on fracture extension correlation information. The specific operation is as follows: in the actual coal seam methane exploitation of the target coal seam, the microstructure distribution characteristics of the fracture extension corresponding to the coal seam rock are screened out from the dominant microstructure distribution characteristics of the fracture extension corresponding to different rock samples through microstructure detection of the coal seam rock.

[0079] Based on the dominant microstructural distribution characteristics of crack extension corresponding to the coal seam rock, additional stress is applied to the coal seam rock to promote the expansion of cracks in the direction of the dominant microstructural distribution characteristics of crack extension in the coal seam rock, and water injection operations are performed on the coal seam rock to make the water injection direction consistent with the stress application direction to enhance the driving force for crack extension.

[0080] Through the above method, the crack extension direction in the coal seam rock can be effectively controlled, the crack extension efficiency can be improved, and thus the coal bed methane recovery rate can be increased. This method combines microstructure detection to ensure the consistency of the water injection direction and the stress application direction, optimizes the fracturing parameters, and improves the effect of coal bed methane extraction.

[0081] Further coal seam fracturing control also includes: injecting low-temperature fluid into the coal seam rock after completing the water injection operation, and controlling the injection rate during the injection process to maintain between the ideal injection rate and the critical injection rate, wherein the ideal injection rate is the optimal injection rate determined based on previous experiments and data analysis, and the critical injection rate is the upper limit of the injection rate identified through experiments that may lead to a decrease in the fracture expansion effect. By controlling the injection rate to ensure that it is within the optimal range, not only can the waste of low-temperature fluid resources be avoided, but also the fracture expansion effect can be optimized.

[0082] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. An intelligent monitoring and control system for coalbed methane mining and staged fracturing, characterized in that: include: A rock sample collection module is used to collect rock samples from the target coal seam; The rock sample microstructure detection module is used to detect natural cracks in the collected rock samples, thereby eliminating rock samples with natural cracks, and taking the remaining rock samples as usable rock samples, and performing microstructure detection on the usable rock samples to obtain microstructure distribution characteristics; A rock sample grouping module is used to group available rock samples into several rock sample groups according to microstructure detection, and obtain the microstructure distribution characteristics corresponding to each rock sample group; The rock sample fracturing simulation module is used to perform perforation operations on each rock sample group, and use a servo motor to apply equal stress in different stress directions to each rock sample group, and then use a hydraulic servo pump to inject fracturing fluid into the perforations of each rock sample group for hydraulic fracturing. At the same time, the injection pressure is monitored to identify whether the hydraulic fracturing is completed. When the hydraulic fracturing is completed, the low-temperature fluid is injected into the rock sample through the perforations, and the injection rate control monitoring is performed during the injection process; A crack expansion monitoring module is used to monitor crack expansion during low-temperature fluid fracturing to obtain crack expansion direction and crack expansion rate; The fracture extension correlation module is used to correlate the fracture extension direction of each rock sample in each rock sample group with the stress application direction of the rock sample, and to correlate the fracture extension rate with the injection rate, so as to comprehensively obtain fracture extension correlation information; The coal seam fracturing control module is used to perform actual coal seam fracturing control based on fracture extension correlation information.

2. The intelligent monitoring and control system for coalbed methane mining staged fracturing according to claim 1, characterized in that: The rock sample groups refer to the following grouping process: The available rock samples that are retained are numbered, and the available rock samples are extracted in sequence according to the numbering order as the main rock samples to form a main rock sample set with other rock samples; The main rock samples in the main rock sample set are compared with other rock samples according to the microstructure detection results, the microstructure similarity of the main rock sample and other rock samples is calculated, and compared with the similarity threshold initially set by the system, and other rock samples whose microstructure similarity reaches the similarity threshold are selected from them to form a rock sample group with the main rock sample.

3. The intelligent monitoring and control system for coalbed methane mining staged fracturing according to claim 1, characterized in that: The perforating operation on each rock sample group is implemented as follows: The rock samples in each rock sample group are perforated at the same position and using the same perforating parameters.

4. The intelligent monitoring and control system for coalbed methane mining staged fracturing according to claim 1, characterized in that: The identification of whether hydraulic fracturing is completed refers to the following process: The injection pressure monitored in real time during hydraulic fracturing is subtracted from the injection pressure at the last monitoring time and the absolute value is taken, and compared with the set equilibrium pressure difference. If the pressure difference at a certain monitoring time reaches the equilibrium pressure difference, the monitoring time is recorded as the stable monitoring time; The duration of the stable monitoring moment is recorded and compared with the set effective duration. If the duration of the stable monitoring moment reaches the effective duration, the hydraulic fracturing is identified to be completed at the current moment.

5. The intelligent monitoring and control system for coalbed methane mining staged fracturing according to claim 1, characterized in that: The injection rate control monitors the following operations: The injection rate is gradually increased by injecting cryogenic fluid into the rock sample through perforations and the injection rate is monitored in real time.

6. The intelligent monitoring and control system for coalbed methane mining staged fracturing according to claim 1, characterized in that: The rock sample fracturing simulation module also includes the following operations: Monitor coal seam environmental conditions at the sampling location during rock sampling; During the fracturing simulation operation on each rock sample group, the fracturing environment was kept consistent with the coal seam environmental conditions at the sampling location.

7. The intelligent monitoring and control system for coalbed methane mining staged fracturing according to claim 1, characterized in that: The process of associating the crack extension direction of each rock sample in each rock sample group with the rock sample stress application direction is as follows: Compare the crack extension direction of each rock sample in each rock sample group with the stress application direction corresponding to the rock sample group to obtain the angle between the crack extension direction and each stress application direction; The angles between the crack extension direction and the stress construction directions are compared to extract the maximum and minimum angles, and the angle range between the maximum and minimum angles is calculated, and then compared with the allowable range configured by the system. When the angle range is greater than the allowable range, it is identified that there is a tendency in the crack extension direction. At this time, the stress application direction corresponding to the minimum angle is selected as the main stress direction of the crack; Based on the principal stress direction of the fracture corresponding to each rock sample in each rock sample group, the microstructure distribution characteristics of the rock sample in the principal stress direction of the fracture are retrieved; The microstructural distribution characteristics of each rock sample in the same rock sample group in the direction of the principal stress of the fracture are compared, and the common microstructural distribution characteristics are extracted as the dominant microstructural distribution characteristics of the fracture extension corresponding to different rock samples.

8. The intelligent monitoring and control system for coalbed methane mining staged fracturing according to claim 5, characterized in that: The correlation between the fracture propagation rate and the injection rate is implemented as follows: The crack extension rate monitored in real time in the crack extension monitoring and the injection rate monitored in real time in the low-temperature fracturing are time-mapped to obtain a plurality of mapping groups, each mapping group consisting of a crack extension rate and an injection rate; Arrange the mapping groups in chronological order, and extract the injection rate of each mapping group in the order of arrangement, and then divide the difference between the injection rate of the previous mapping group and the injection rate of the previous mapping group to obtain the injection rate increase of each mapping group. Similarly, compare the crack extension rate of each mapping group with the crack extension rate of the previous mapping group to calculate the crack extension increase of each mapping group; The crack extension increase of each mapping group is compared with the effective increase set by the system. If the crack extension increase of a mapping group is lower than the effective increase, the mapping group is taken as the critical mapping group, and the crack extension increase of the mapping group after the critical mapping group is compared with the effective increase. The duration of the crack extension increase being continuously lower than the effective increase is counted and compared with the effective duration set by the system. If the crack extension increase is still lower than the effective increase after reaching the effective duration, the injection rate in the critical mapping group is recorded as the critical injection rate; The crack extension increases of all mapping groups before the critical mapping group are compared, and the mapping group corresponding to the maximum crack extension increase is extracted as the ideal mapping group, and the injection rate in the ideal mapping group is recorded as the ideal injection rate.

9. The intelligent monitoring and control system for staged fracturing of coalbed methane mining according to claim 7, characterized in that: The actual coal seam fracturing control based on the fracture extension correlation information is performed as follows: In the actual coal-bed methane exploitation of the target coal seam, the dominant microstructure distribution characteristics of the fracture extension corresponding to the coal seam rock are screened out from the dominant microstructure distribution characteristics of the fracture extension corresponding to different rock samples through the microstructure detection of the coal seam rock; Based on the dominant microstructural distribution characteristics of the crack extension corresponding to the coal seam rock, additional stress is applied to the coal seam rock, and water injection is performed to the coal seam rock so that the injection direction is consistent with the stress application direction.

10. The intelligent monitoring and control system for coalbed methane mining staged fracturing according to claim 8, characterized in that: The actual coal seam fracturing control based on the fracture extension correlation information also includes the following process: After the water injection operation is completed, low-temperature fluid is injected into the coal seam rock, and the injection rate is controlled during the injection process to maintain between the ideal injection rate and the critical injection rate.

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