Microseismic and numerical simulation mutual feedback fracturing crack propagation dynamic measurement and control method

Abstract

The present invention discloses a dynamic measurement and control method for hydraulic fracture expansion based on mutual feedback between microseismic and numerical simulation, comprising: constructing a simulation calculation model for hydraulic fracture expansion; monitoring microseismic waveforms, obtaining the spatial distribution of earthquake sources and microseismic characteristic parameters based on the microseismic waveforms and generating a distribution law; screening fracture zones based on the distribution law; determining the spatial distribution of rock fracture mechanics parameters in the fracture zone based on a correlation model between the microseismic characteristic parameters of the fracture zone and the nonlinear fracture characteristics of the rock; and substituting the mechanical parameters into the simulation calculation model to predict hydraulic fracture expansion. The above method can dynamically update the physical and mechanical parameters of the numerical simulation model along with microseismic monitoring; and finally, through the dynamic mutual feedback between microseismic and numerical simulation, it can achieve real-time prediction and control of the morphology and trajectory of hydraulic fracture expansion in engineering.

Description

TECHNICAL FIELD

[0001] The present application relates to the exploitation of underground geological new energy, and in particular to a microseismic and numerical simulation mutual feedback fracturing fracture propagation dynamic measurement and control method. BACKGROUND

[0002] Dry hot rock geothermal, unconventional oil and gas and coalbed methane are important strategic replacement geological new energy in China, among which dry hot rock geothermal has the dual advantages of large reserves and clean and low carbon.

[0003] Fracturing fracture network to improve reservoir permeability is the core technology for exploiting dry hot rock geothermal, unconventional oil and gas and coalbed methane. Dry hot rock mainly composed of granite is very dense. If it is to be exploited by circulating hot water through injection wells (injecting cold water) and extraction wells (extracting hot water exchanged by heat), it must be fractured by high-pressure fluid to break the rock, so as to form an artificial fracture network in the reservoir, so that the fluid flows in the artificial fracture network, thereby improving the heat exchange efficiency of the injected fluid in the artificial fracture network. Unconventional oil and gas resources and coalbed methane are also in need of forming an artificial fracture network in the reservoir to improve the permeability of the reservoir, thereby improving the recovery rate of oil and gas in the reservoir. In addition, fracturing is also a key technology for controlling the surrounding rock of mine and improving the permeability of coalbed methane.

[0004] Since the fractures driven by fracturing expand in the rock formation, high-precision monitoring of the fractures and real-time control of the fracture expansion will greatly improve the efficiency of reservoir permeability improvement. However, fracturing fractures have always been difficult to monitor and control. Since the correlation between microseismic monitoring characteristic parameters and numerical simulation theory and numerical simulation model has not been established, microseismic monitoring of fracturing fractures and numerical simulation prediction of fracturing fracture expansion are independent of each other, and fracturing fracture monitoring and numerical simulation are difficult to be real-time mutual feedback, so it is difficult to control the fracture morphology and expansion trajectory by dynamically adjusting process parameters. SUMMARY

[0005] The purpose of the present application is to provide a microseismic and numerical simulation mutual feedback fracturing fracture propagation dynamic measurement and control method to realize the prediction and control of the expansion morphology and trajectory of fracturing fractures in engineering.

[0006] To solve the above technical problems, the embodiments of the present application provide a microseismic and numerical simulation mutual feedback fracturing fracture propagation dynamic measurement and control method, which comprises constructing a fracturing fracture propagation simulation calculation model; monitoring the microseismic waveform, obtaining the spatial distribution of the seismic source and the microseismic characteristic parameters according to the microseismic waveform and generating the distribution rule; screening out the fracture zone according to the distribution rule; determining the spatial distribution of the rock fracture mechanics parameters of the fracture zone according to the correlation model of the microseismic characteristic parameters of the fracture zone and the nonlinear fracture characteristics of the rock; and substituting the rock fracture mechanics parameters into the simulation calculation model to predict the fracturing fracture propagation.

[0007] In addition, the simulation calculation model comprises engineering conditions, physical and mechanical parameters and a calculation function.

[0008] In addition, the spatial distribution of the microseismic source and the microseismic characteristic parameters is obtained according to the microseismic waveform, and a distribution rule is generated, comprising: locating the microseismic source by using an acoustic emission and microseismic locating method based on full waveform analysis; analyzing and calculating the waveform and event evolution characteristics of acoustic emission and microseismic based on the spatial coordinates of the located point of the microseismic source to obtain microseismic characteristic parameters representing the characteristics of acoustic emission and microseismic, wherein the microseismic characteristic parameters comprise microseismic event density and microseismic energy; identifying a region in which the density of the spatial distribution of the microseismic event density and the microseismic energy is greater than a preset threshold, and obtaining the distribution rule according to the region.

[0009] In addition, the region in which the density of the spatial distribution of the microseismic event density and the microseismic energy is greater than a preset threshold is identified, and the distribution rule is obtained according to the region, comprising: constructing a spatial unit body in the microseismic space; sequentially counting the cumulative amount of microseismic energy and the cumulative amount of microseismic events in each unit body; taking the peak point of the sum of the cumulative amount of microseismic energy and the cumulative amount of microseismic events as a central microseismic point, and extending the microseismic energy and the microseismic event statistics to the periphery of the microseismic space; comparing the sum of the cumulative amount of microseismic energy and the cumulative amount of microseismic events in each unit body with a preset threshold, and selecting a region in which the unit body is greater than the preset threshold; obtaining the distribution rule of the microseismic energy and the microseismic event according to the region.

[0010] In addition, the spatial distribution of the rock fracture mechanics parameters of the fracture zone is determined according to a correlation model of the microseismic characteristic parameters of the fracture zone and the nonlinear fracture characteristics of the rock, comprising: constructing a correlation model of the microseismic characteristic parameters of the fracture zone and the fracture and rupture characteristics of the rock; using acoustic emission and microseismic full waveform analysis methods and full waveform microseismic analysis methods to analyze and monitor the microseismic results of the fracture zone in real time to obtain the microseismic characteristic parameters of the fracture zone; inputting the microseismic characteristic parameters into the correlation model to obtain the spatial distribution of the rock fracture mechanics parameters of the fracture zone; wherein the correlation model comprises a rock fracture model, a fracturing fracture propagation physical model, a time-dependent rock subcritical fracture propagation model, a unit damage mechanics model and a spatial material point mechanics characteristic determination model.

[0011] In addition, after the fracturing fracture propagation prediction, it further comprises: judging whether the simulation result of the fracturing fracture propagation prediction value meets the fracturing design requirement; when the simulation result of the fracturing fracture propagation prediction value does not meet the fracturing design requirement, adjusting the engineering condition parameters until the simulation result of the fracturing fracture propagation prediction value meets the fracturing design requirement.

[0012] In addition, in the n+1th prediction, the crack area screened out in the nth time is taken as an encryption trial area and a fine partition of the initial value of the source positioning in the n+1th time, wherein n is an integer greater than or equal to 1.

[0013] Compared with the prior art, the present application has the following remarkable effects: in the present application, the physical and mechanical parameters of the numerical simulation simulation model are dynamically updated with the microseismic monitoring by constructing the correlation model of the microseismic characteristic parameters and the physical and mechanical parameters; the crack area can be more accurately determined and the distribution law can be identified through the combined analysis of the source energy and the spatial distribution of the source event; the mutual feedback of the microseismic and the numerical simulation is realized by predicting the subsequent extension law and trajectory of the fracturing crack under the current process and engineering parameters, and finally the real-time prediction and control of the fracturing crack extension form and trajectory in the engineering can be realized. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 The flow chart of the microseismic and numerical simulation mutual feedback fracturing crack extension dynamic measurement and control method is an embodiment of the present application;

[0015] Figure 2 The microseismic characteristic parameter and mechanical parameter correlation diagram is an embodiment of the present application;

[0016] Figure 3 The mutual feedback schematic diagram is an embodiment of the present application;

[0017] Figure 4 The mutual feedback flow schematic diagram is an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the embodiments of the present application will be described in detail below with reference to the drawings. However, those skilled in the art can understand that in the embodiments of the present application, many technical details are proposed in order to make the reader better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present application can be realized. The division of the following embodiments is for the convenience of description, and should not constitute any limitation on the specific implementation of the present application, and the embodiments can be combined and quoted with each other without contradiction.

[0019] An embodiment of the present application relates to a microseismic and numerical simulation mutual feedback fracturing fracture propagation dynamic measurement and control method, which can be applied to a fracturing measurement and control system, and in the embodiment of the present application, the measurement and control method comprises the following steps: a fracturing fracture propagation simulation calculation model is constructed; microseismic waveforms are monitored, and spatial distribution of a seismic source and microseismic characteristic parameters is obtained according to the microseismic waveforms and distribution rules are generated; a crack zone is screened out according to the distribution rules; rock fracture mechanics parameter spatial distribution of the crack zone is determined according to a correlation model of the microseismic characteristic parameters of the crack zone and nonlinear fracture characteristics of rock; and the mechanics parameters are substituted into the simulation calculation model to predict fracturing fracture propagation. The correlation model of the microseismic characteristic parameters and the physical mechanics parameters is constructed through the above method, physical mechanics parameters of a numerical simulation simulation model are dynamically updated according to microseismic monitoring, the subsequent propagation rules and trajectories of fracturing fractures under current process and engineering parameters are predicted, the dynamic mutual feedback of microseismic and numerical simulation is realized, and finally real-time prediction and control of fracturing fracture propagation morphology and trajectories in engineering can be realized. The implementation details of the microseismic and numerical simulation mutual feedback fracturing fracture propagation dynamic measurement and control method of the embodiment of the present application are described in detail below, and the following content is only provided for the implementation details for easy understanding, and is not necessary for implementing the scheme.

[0020] In the embodiment of the present application, the microseismic and numerical simulation mutual feedback fracturing fracture propagation dynamic measurement and control method flow is as shown in Figure 1 In step 101, a fracturing fracture propagation simulation calculation model is constructed.

[0021] Specifically, the simulation calculation model comprises engineering conditions, physical mechanics parameters and a calculation function; the calculation function calculates the physical mechanics parameters according to the engineering conditions. In an example, in the scene of deep high-temperature oil and gas reservoirs, geothermal heat reservoirs such as hot dry rock, and oil shale and coal seams that need high-temperature modification, the numerical simulation calculation model comprises but is not limited to a compression-shear thermal plasticity constitutive model and a thermal plasticity fracture model:

[0022] (1) In the compression-shear thermal plasticity constitutive model, a1 represents a plastic modulus representing strengthening and softening caused by stress change; a2 represents a temperature sensitive modulus representing strengthening and softening caused by temperature change; a3 is an elastic-plastic stiffness matrix; a4 is a temperature conversion tensor; the elastic-plastic stiffness matrix and the temperature conversion tensor can be updated in real time according to the thermal plasticity constitutive relationship to obtain the constitutive response relationship of stress-strain-temperature in the latest state;

[0023] (2) In the thermoplastic fracture model, b1 cohesive tensile strength, b2 critical crack opening displacement, b3 fracture process zone length, b4 fracture energy per unit length, b5 cumulative dissipated energy, b6 temperature sensitive modulus of process zone strength (softening) temperature directly caused by temperature, which characterize the thermoplastic fracture characteristics under the conditions of high temperature environment, high temperature thermal damage and thermal shock of temperature difference. The engineering conditions when using different processes include but are not limited to: displacement, viscosity, fracturing fluid type, fluid volume, proppant size type; elastic parameters, plasticity, strength, viscosity, fracture, and other solid mechanics parameters, permeability, porosity, filterability, and other physical parameters related to fluid seepage flow.

[0024] It should be pointed out that the microseism mentioned in the present application refers to the elastic wave in a broad sense, i.e. the elastic wave released by material rupture, which includes microseism and acoustic emission; the present method can be applied to all microseism monitoring and acoustic emission monitoring means, covers all field engineering and laboratory tests, and can be applied to all microseism sensing types, such as optical fiber type, piezoelectric type, vibration type and three-component type.

[0025] In step 102, the microseismic waveform is monitored, the spatial distribution of the source and the microseismic characteristic parameters is obtained according to the microseismic waveform, the distribution rule is generated, and the crack zone is screened out according to the distribution rule.

[0026] Specifically, step 102 includes positioning the source by using the acoustic emission and microseismic full waveform analysis method and the full waveform microseismic analysis method; based on the spatial coordinates of the positioning point of the source, the waveform and event evolution characteristics of the acoustic emission and the waveform and event evolution characteristics of the microseism are analyzed and calculated to obtain the microseismic characteristic parameters representing the acoustic emission and the microseism, wherein the microseismic characteristic parameters include source event density and source energy; the regions where the density of the source event density and the source energy in space is greater than a preset threshold value are identified, and the distribution rule is obtained according to the regions.

[0027] In one example, the positioning of the seismic source includes acoustic emission and microseismic positioning method using full waveform analysis: first, determine the microseismic sampling parameters and high-quality waveform characteristics, and then obtain the elastic waves generated by crack propagation and rock rupture, according to the frequency from low to high, the elastic waves can include microseismic and acoustic emission, and obtain high-quality waveforms. Further, on the basis of obtaining high-quality original waveforms, a group of waveforms corresponding to the same seismic source is determined, and the arrival time of each waveform is obtained; considering the prominent characteristics of the attenuation of wave velocity due to the development of micro-cracks when the rock material is fractured, the change of wave velocity due to rock deformation, and the difference of wave velocity in different strata, the dynamic wave velocity is preferably used for seismic source positioning. If the strata are homogeneous and the micro-crack area has little effect on the wave velocity, constant wave velocity can also be used for seismic source positioning. Based on the spatial coordinates of the accurately positioned seismic source points, the waveforms and event evolution characteristics of acoustic emission and microseismic events are further analyzed and calculated, and a plurality of microseismic characteristic parameters representing acoustic emission and microseismic characteristics are obtained, such as source event density, source energy, source wave velocity, source frequency spatial distribution, source mechanism, b value evolution and other all waveforms and evolution characteristics.

[0028] Further, the spatial distribution rule is obtained by analyzing the microseismic characteristic parameters, and the crack zone (the crack zone includes macroscopic fracturing cracks and secondary cracks or micro-crack zone around the cracks) is identified. The microseismic characteristic parameters and the corresponding mechanical characteristics are as follows: the spatial aggregation zone of the microseismic event represents the macroscopic hydraulic fracture and the secondary crack zone (including micro-crack zone) around the cracks, the spatial distribution of microseismic energy represents the energy dissipation distribution of the hydraulic fracture and the secondary crack zone around the cracks, the spatial distribution of microseismic wave velocity describes the micro-fracture damage characteristics of the hydraulic fracture and the secondary crack zone around the cracks, the spatial distribution of microseismic frequency describes the size of the hydraulic fracture and the secondary crack zone around the cracks, and the source mechanism represents the tensile, shear and tensile-shear composite fracture mechanism in the hydraulic micro-crack zone. Specifically, the corresponding relationship between the microseismic characteristic parameters and the mechanical characteristics such as rock fracture is as shown in the following table. Figure 2 The identification method of the macroscopic fracturing cracks mainly identifies the region where the source energy and the spatial density of the source events are greater than the preset threshold, and analyzes the distribution rule thereof.

[0029] Specifically, the combination analysis of the source energy and the spatial distribution of the source event is mainly used to eliminate the potential risk of discontinuous distribution restricting crack identification under the condition of separate analysis of the two, and the best one of the two in the analysis of the spatial distribution continuity is used to determine the crack formation position. In addition, the analysis of the distribution rule includes first constructing a spatial unit body in the microseismic space, and then sequentially counting the source energy accumulation and the source event accumulation in each unit body; further, taking the peak point of the source energy and the source event accumulation as the center source point, the source energy and the source event are counted around the microseismic space, and then the source energy and the source event accumulation in each unit body are compared with the preset threshold (70% of the source energy and the source event density of the center source point), and the area exceeding the preset threshold is selected as the macro fracture crack formation area, and the distribution rule of the source energy and the source event is obtained. The setting of the preset threshold can be adjusted according to the actual production scene.

[0030] Based on the above distribution rule, we can introduce digital twin technology, specifically introduce artificial intelligence algorithm, intelligently identify macro crack and crack secondary crack area, and determine the spatial distribution rule of characteristic parameters. Specifically, after obtaining the macro fracture crack formation area and the distribution rule, linear regression model, logistic regression model, decision tree model, support vector machine (SVM) model, neural network model and ensemble learning model are used to fit and optimize the spatial distribution of microseismic characteristic parameters, and the discrete points of the parameters are picked up for regression processing, so as to improve the spatial distribution description accuracy of microseismic characteristic parameters, and accurately describe and identify the macro crack and crack secondary crack area.

[0031] In order to avoid the singleness and limitation of the microseismic characteristic parameter in describing and identifying the macro crack and crack secondary crack area, the correlation analysis model, the regression analysis model, the neural network model, the ensemble learning model, the support vector machine (SVM) model, the Bayesian network model and the hidden Markov (HMM) model are used to analyze the correlation between the microseismic characteristic parameters (including the macro hydraulic fracture and its surrounding secondary crack area (including micro crack area) represented by the spatial aggregation area of microseismic event, the energy dissipation distribution of the hydraulic fracture and its surrounding secondary crack area represented by the spatial distribution of microseismic energy, the micro fracture damage characteristics of the hydraulic fracture and its surrounding secondary crack area represented by the spatial distribution of microseismic wave velocity, the size of the hydraulic micro crack area represented by the spatial distribution of microseismic frequency, and the correlation between the tensile, shear and tensile-shear composite fracture mechanisms in the hydraulic micro crack area represented by the source mechanism), and the spatial distribution of the microseismic characteristic parameters is fitted and optimized, and the macro crack and crack secondary crack area described by multiple parameters are further obtained.

[0032] In step 103, the spatial distribution of the rock fracture mechanics parameters of the crack area is determined according to the correlation model of the microseismic characteristic parameters of the crack area and the nonlinear fracture characteristics of the rock.

[0033] Specifically, the method comprises: constructing a correlation model of microseismic characteristic parameters and rock fracture and rupture characteristics; analyzing microseismic results of the crack zone in real time by using acoustic emission and microseismic full waveform analysis methods and full waveform microseismic analysis methods to obtain microseismic characteristic parameters of the crack zone; and inputting the microseismic characteristic parameters into the correlation model to obtain spatial distribution of rock fracture mechanics parameters of the crack zone; wherein the correlation model comprises a fracture model suitable for rock, a physical model of fracture crack propagation, a time-dependent rock subcritical crack propagation model, a unit damage mechanics model, and a spatial material point mechanics characteristic determination model.

[0034] In one example, the method of constructing a correlation model of microseismic characteristic parameters and rock fracture and rupture characteristics comprises:

[0035] c1. The fracture model suitable for rock is used to obtain the constitutive relationship and fracture model parameters: three-point bending fracture tests are carried out in the laboratory, and various macroscopic corresponding data such as loading force, displacement, deformation, and crack opening are recorded. Various monitoring methods such as acoustic emission (indoor microseismic), digital image, and optical fiber grating are used to determine the constitutive relationship and model parameters of the fracture model suitable for rock. Typical parameters include (but are not limited to): the correlation between the softening function of the cohesive force-crack opening of the cohesive fracture model and the spatial distribution of acoustic emission and microseismic characteristic parameters; and the correlation between the spatial distribution of the cumulative amount of acoustic emission energy, events, and frequency, wave speed, and different types of rupture proportion and the elastic, viscous, strength, and fracture parameters of rock.

[0036] c2. The physical model of fracture crack propagation: based on the correlation between the acoustic emission and microseismic energy distribution characteristics monitored in the fracture experiment and the phase field model, the distribution characteristics of dissipation energy, fracture mechanism, displacement field, strain field, crack opening, stress field, and other parameters in the cross-sectional crack propagation direction in the fracture test are described by using acoustic and optical joint monitoring methods, which are used to construct the phase field model and obtain the physical model of fracture crack propagation.

[0037] c3. The time-dependent rock subcritical crack propagation model: based on the correlation between the size of microcrack zone and acoustic emission and microseismic energy and event density characteristics: the spatial evolution of microcrack zone is described by using acoustic emission and microseismic energy and event density, and the energy dissipation in the microcrack zone is determined, and then the local stress response is inferred to construct the time-dependent rock subcritical crack propagation model, which is especially suitable for liquid and supercritical carbon dioxide fracturing and well killing and fracture creating technology.

[0038] C4 unit damage mechanics model: adopts the "microseismic parameter evolution-macro-micro crack generation" method to distinguish the correlation between microseismic characteristic parameters and fracturing cracks. By capturing the evolution characteristics of microseismic characteristic parameters such as wave velocity attenuation, energy accumulation, and frequency increase, the initiation and development of macro- and micro-cracks are judged, and the above mechanism is finally used to determine the parameters of the unit damage mechanics model.

[0039] c5 Spatial material point mechanical characteristics determination model: The initial polarity method and moment tensor analysis method (including but not limited to) are used to identify and determine the fracture mechanism (tension, shear, compression) of microcracks (acoustic emission sources), and further integrated into the discrete element model to characterize the microscopic failure mode between particles in the discrete element model. In addition, based on the spatial distribution characteristics of characteristic parameters including but not limited to dissipated energy, displacement field, strain field, crack opening, stress field, etc., the material point method is integrated to obtain the spatial material point mechanical characteristics based on the material point method.

[0040] In step 104, the rock fracture mechanics parameters are substituted into the simulation calculation model to predict the expansion of the fracturing crack. Specifically, it includes using the acoustic emission and microseismic full waveform analysis method and the full waveform microseismic analysis method to analyze the microseismic results obtained by real-time monitoring, and obtain the macro crack trajectory and morphology of the fracturing crack, as well as the range and distribution morphology of the secondary cracks around the cracks, and convert the microseismic characteristic parameters of the secondary microcrack area into physical and mechanical parameters. According to the engineering geological conditions, the finite element method, discrete element method, boundary element method, material point method and other numerical simulation calculation methods are comprehensively used to dynamically update the physical and mechanical parameters and engineering conditions in the numerical simulation, perform numerical calculations, and predict the next expansion trajectory and macro and microscopic morphology of the fracturing crack under the current fracturing process engineering parameters. The specific mutual feedback diagram is as follows: Figure 3 As shown, the physical and mechanical parameters are obtained by monitoring the hydraulic fractures, and the engineering parameters are output by the numerical simulation model updated by the physical and mechanical parameters to control the fracture expansion of the hydraulic fractures.

[0041] In step 105, it is determined whether the simulation result of the predicted value of the fracturing crack extension meets the fracturing design requirements; if it does not meet the fracturing design requirements, the engineering condition parameters are adjusted until the simulation result of the predicted value of the fracturing crack extension meets the fracturing design requirements.

[0042] Specifically, it is judged whether the dynamic updated fracturing fracture propagation numerical simulation result meets the fracturing design requirement, and when it does not meet the fracturing design requirement, a deep learning method is used to train different processes corresponding to engineering conditions including but not limited to displacement, viscosity, fracturing fluid type, liquid volume, proppant scale type, elastic parameters, plasticity, strength, viscosity, fracture, and other solid mechanics parameters, and physical parameters related to fluid seepage flow such as permeability, porosity, and filtration property, etc. to obtain engineering conditions that are beneficial to meet the fracturing fracture propagation design requirement, and further use the current physical and mechanical parameter dynamic updated numerical simulation model to calculate the fracturing fracture propagation law under multiple sets of engineering conditions, select the engineering conditions corresponding to the optimal result, and dynamically, real-time and intelligently adjust.

[0043] In one embodiment, in the n+1th prediction, the crack zone screened out in the nth time is taken as an encryption trial calculation zone and a fine partition of the initial value of the source positioning in the n+1th time, where n is an integer greater than or equal to 1. The accuracy of the source inversion and the richness of the microseismic characteristic parameters can be improved. In addition, in the whole process of fracturing crack propagation, the minimum analysis step of the dynamic propagation of the fracturing crack is determined based on the minimum number of sources required to obtain the correlation between the microseismic characteristic parameters and the geomechanical parameters, and the above steps 101-104 are repeated until the reservoir fracturing reconstruction is completed according to the engineering requirements in step 105, which can realize more accurate prediction and monitoring. Specifically, the negative feedback link in the embodiment is as shown in Figure 4 Figure 4 The judgment process and the two negative feedback substitution processes can clearly reflect the process of dynamic, real-time and intelligent adjustment.

[0044] The embodiments of the application are described in detail above in combination with the drawings, but the application is not limited thereto, and various changes can be made within the knowledge of those skilled in the art without departing from the purpose of the application, which are all within the protection scope of the claims of the application.

[0045] Obviously, those skilled in the art can make various modifications and variations to the application without departing from the spirit and scope of the application. Thus, if these modifications and variations of the application fall within the scope of the claims of the application and their equivalent technologies, the application also intends to include these modifications and variations.​

Claims

1. A dynamic monitoring and control method for fracturing crack expansion based on mutual feedback of microseismic and numerical simulation, characterized in that: include: Construct a simulation calculation model for fracturing crack expansion; Monitor microseismic and acoustic emission waveforms, obtain the spatial distribution of earthquake sources and microseismic characteristic parameters based on the microseismic waveforms, and generate distribution patterns. The method of obtaining the spatial distribution of the earthquake source and microseismic characteristic parameters and generating a distribution law based on the microseismic and acoustic emission waveforms includes: Locating the earthquake source using acoustic emission and microseismic location methods based on full waveform analysis; Based on the spatial coordinates of the location point of the earthquake source, the waveform and event evolution characteristics of the acoustic emission and the waveform and event evolution characteristics of the microseismic are analyzed and calculated to obtain microseismic characteristic parameters that characterize the characteristics of the acoustic emission and microseismic, wherein the microseismic characteristic parameters include the earthquake source event density and the earthquake source energy; Identifying areas where the density of earthquake source events and the density of earthquake source energy distribution in space are greater than a preset threshold, and obtaining the distribution pattern based on the areas; The identifying of an area where the density of earthquake source events and the density of earthquake source energy distribution in space are greater than a preset threshold, and obtaining the distribution law based on the area, includes: Constructing a spatial unit in the microseismic space; The accumulated amount of earthquake source energy and accumulated amount of earthquake source events in each unit are counted in turn; The peak point of the sum of the accumulated source energy and the accumulated source events is taken as the central source point, and the source energy and source events are counted around the microseismic space. Compare the sum of the accumulated energy of the earthquake source and the accumulated event of the earthquake source in each unit with the preset threshold, and select the area where the unit with a value greater than the preset threshold is located; Obtaining the distribution pattern of earthquake source energy and earthquake source events according to the region; Based on the distribution law of the above-mentioned source energy and source events, the spatial distribution law of the characteristic parameters is determined; The fracture area is screened out based on the distribution law of earthquake source energy and earthquake source events and the spatial distribution law of characteristic parameters; According to the correlation model between the microseismic characteristic parameters of the fracture zone and the nonlinear fracture characteristics of the rock, the spatial distribution of the rock fracture mechanics parameters in the fracture zone is determined; The rock fracture mechanics parameters are substituted into the simulation calculation model to predict the expansion of the fracturing crack.

2. The dynamic monitoring and control method for fracturing crack expansion based on mutual feedback of microseismic and numerical simulation according to claim 1 is characterized in that: The simulation calculation model includes engineering conditions, physical and mechanical parameters and a calculation function; the calculation function calculates the physical and mechanical parameters according to the engineering conditions.

3. The dynamic monitoring and control method for fracturing crack expansion based on mutual feedback of microseismic and numerical simulation according to claim 1 is characterized in that: The method of determining the spatial distribution of rock fracture mechanics parameters in the fracture zone according to a correlation model between the microseismic characteristic parameters of the fracture zone and the nonlinear fracture characteristics of the rock comprises: Construct a correlation model between microseismic characteristic parameters in the fracture zone and rock fracture and rupture characteristics; Utilizing acoustic emission and microseismic full waveform analysis methods to analyze and monitor microseismic results of the fracture zone in real time, and obtaining microseismic characteristic parameters of the fracture zone; Inputting the microseismic characteristic parameters into the correlation model to obtain the spatial distribution of rock fracture mechanics parameters in the fracture zone; Among them, the correlation model includes a rock fracture model, a fracturing crack extension physical model, a time-related rock subcritical crack extension model, a unit damage mechanics model, and a spatial material point mechanical characteristics determination model.

4. The method for dynamic monitoring and control of fracturing crack expansion with mutual feedback of microseismic and numerical simulation according to claim 1 is characterized in that: After the prediction of the hydraulic fracture expansion, the method further includes: Determining whether the simulation result of the predicted numerical value of the fracturing crack extension meets the requirements of the fracturing design; When the fracturing design requirements are not met, the engineering condition parameters are adjusted until the simulation result of the predicted numerical value of the fracturing crack extension meets the fracturing design requirements.

5. The method for dynamic monitoring and control of fracturing crack expansion with mutual feedback of microseismic and numerical simulation according to claim 1 is characterized in that: Also includes: In the n+1 prediction, the crack area selected in the nth time is used as the earthquake source location in the n+1th time. early The encryption trial area and fine partition of the value, where n is an integer ≥ 1.

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