188 results about "Microearthquake" patented technology

The invention relates to the technical field of hydraulic fracturing, in particular to a method for evaluating effectiveness of fracture parameters of artificial fracturing of a horizontal well. The method comprises the following steps that information collection based on ground process parameters and underground dynamic parameters is conducted on the horizontal well artificial fracturing construction process, and fracturing working condition data are obtained; according to the fracturing working condition data, the fracture expansion of the horizontal well is monitored in real time, digital conversion processing is conducted, and real-time fracture monitoring data is generated; performing micro-seismic signal analysis on the real-time crack monitoring data, and performing crack network space distribution calculation to generate crack network distribution data; performing reservoir stress field dynamic evolution analysis according to the fracture network distribution data to generate stress field distribution data; and carrying out propping agent migration trajectory tracking according to the stress field distribution data to generate propping agent distribution data. According to the method, the reservoir stress field dynamic evolution analysis and the proppant migration mechanical model are combined, and the effectiveness of the fracture parameters can be evaluated more accurately.

The invention relates to the technical field of petroleum and natural gas engineering, and discloses an oil and gas reservoir optimized mining method based on multi-modal data, which comprises the following steps: constructing an oil and gas reservoir multi-modal data acquisition system, seismic wave field data, logging interpretation data, production dynamic data, micro-seismic monitoring data, underground temperature and pressure time sequence data and shaft structure parameter data are obtained through the acquisition system; and performing space-time alignment processing on the acquired multi-modal data, establishing a unified geological coordinate system and a time reference, and eliminating data isomerism caused by different acquisition frequencies and spatial resolutions. A six-dimensional heterogeneous data acquisition system covering a seismic wave field, well logging interpretation, production dynamics, micro-seismic monitoring, an underground temperature and pressure time sequence and shaft structure parameters is constructed, so that the depiction precision of a reservoir porosity field, a permeability field, a saturation field and a pressure field is essentially improved.

The invention relates to the technical field of geological disaster forecasting, in particular to a karst tunnel collapse disaster microearthquake precursor information identification method. According to the technical scheme, the method comprises the steps of constructing a micro-seismic monitoring system fusing multi-source data, carrying out processing and analysis based on machine learning, establishing a multi-factor coupling analysis and early warning model, and carrying out real-time early warning and dynamic feedback. According to the method, noise can be accurately removed through wavelet transformation, key features of the micro-seismic signals can be reserved, the data quality is improved, multi-dimensional features including frequency, amplitude, phase and the like are extracted from the micro-seismic signals, multi-dimensional feature extraction is achieved, and therefore the accuracy of capturing precursor information related to collapse disasters is improved; in addition, comprehensive classification and judgment are carried out by utilizing a machine learning algorithm and combining multiple factors such as geological conditions and construction progress, so that the recognition result is more in line with the actual situation, misjudgment caused by a single factor is avoided, and the recognition accuracy and efficiency are improved.

The invention provides a karst collapse early warning method and device, electronic equipment and a storage medium. The method provided by the invention comprises the steps of determining a first time sequence feature of surface displacement data, a second time sequence feature of groundwater dynamic data, a spatial feature of geological radar image data and a vibration feature of microseismic signal data, and generating a multi-modal fusion feature vector according to the first time sequence feature, the second time sequence feature, the spatial feature and the vibration feature; according to the multi-modal fusion feature vector and an early warning model, an early warning signal is obtained, and the early warning model is obtained by updating an early warning threshold value through a historical multi-modal fusion feature vector and a Transform-LSTM hybrid network by using a time sequence difference learning strategy; and performing validity judgment on the early warning signal according to the surface displacement data, the groundwater dynamic data and the micro-seismic signal data, and determining whether to perform early warning according to a judgment result. According to the method, the accuracy of karst collapse early warning can be improved.

The invention discloses a mine microseismic event self-positioning method and a mine microseismic event self-positioning system without a prior velocity structure, which realize integration of underground velocity structure inversion and seismic source positioning by jointly utilizing microseismic signals and surface wave interference noise generated in a mining process. Comprising the following steps: arranging an earth surface detector array to collect micro-motion and micro-seismic mixed signals; extracting a surface wave dispersion curve to invert a stratum S-wave velocity model, and further constructing a P-wave velocity model when the stratum Poisson's ratio in the geological data is known; carrying out seismic phase pickup after carrying out noise reduction on the microseismic signal, and obtaining first arrival time of a P wave and an S wave; and constructing a target function taking the first arrival time, the seismic source position, the seismic moment and the velocity model as parameters, and optimizing the target function to realize accurate positioning. According to the method, early-stage field acoustic logging construction of a mine is avoided, surface wave interference noise is fully utilized, the utilization rate of monitoring data is improved, and mine microseism event positioning without a prior speed structure is achieved.

The invention provides a hard roof area fracturing multi-source monitoring method and device, and relates to the technical field of geological prospecting, and the method comprises the steps: determining the position of a seismic source according to a micro-seismic waveform record collected by a ground three-component detector; carrying out two-dimensional positioning on a microseismic event waveform acquired by the distributed optical fiber in a seismic source direction to obtain a seismic plane distance and depth; jointly determining the three-dimensional space position of the seismic source according to the three parameters of the seismic source orientation, the seismic plane distance and the depth; and analyzing the diffusion range of the fracturing fluid according to the three-dimensional space position through an electromagnetic method to obtain the diffusion range of the fracturing fluid. And finally, accurate monitoring and evaluation of the diffusion and transformation range of the fracturing fluid during the hydraulic fracturing operation of the hard roof are realized through microseism, distributed optical fiber sensing and electromagnetic method multi-source monitoring.

The invention belongs to the technical field of intelligent sensing, and relates to a micro-seismic monitoring method for a ground moving target in a sensitive area, which comprises the following steps: collecting five types of moving target seismic signals, and constructing a data set; preprocessing the data; constructing an interpretable convolution kernel based on a scalar wave field equation, and realizing adaptive extraction of key physical parameters and nonlinear dimensionality reduction of a high-dimensional feature space by embedding a partial differential operator to form compact feature representation with physical traceability; forward diffusion is adopted to carry out progressive Gaussian noise enhancement on the noisy features; designing a Transform architecture with a multi-head self-attention mechanism and position coding, capturing time-space correlation characteristics of vibration signals through context modeling, and realizing end-to-end mapping from physical characteristics to classification decision in combination with a multi-layer perceptron; and carrying out training and event decision making on the model, and outputting a decision classification result. According to the method, the identification accuracy of the seismic oscillation signal of the moving target can reach 95.2%, and the robustness is remarkably improved.

A method and device for accurately locating and surveying hidden active faults. First, through regional geological analysis and geomorphological judgment, potential hidden active faults and geomorphological features are identified using geological data and remote sensing images. Then, shallow exploration trenches are laid in the preliminary judgment area, and the activity and shallow location of hidden active faults are determined by combining chronological analysis and shallow seismic reflection method. Then, magnetotelluric sounding, microseismic monitoring and seismic wave CT imaging are used to detect deep hidden active faults. After that, a three-dimensional geological model is established by integrating multi-source data to intuitively display the information of hidden active faults. Finally, the activity of hidden active faults is evaluated based on the model, the impact of the project is analyzed, and optimization suggestions such as structural reinforcement and avoidance schemes are proposed. The problem that the traditional geological exploration technology is prone to splashing rocks, threatening personnel safety, increasing the difficulty of collection and affecting the exploration accuracy when locating hidden active faults, especially shallow exploration trenches, is solved due to the excavation equipment and sampling methods.

The invention relates to the technical field of microseism monitoring, in particular to a shale oil and gas well fracturing microseism monitoring and analyzing device and method.The shale oil and gas well fracturing microseism monitoring and analyzing device comprises a three-component microseism sensor and further comprises a discharging and taking assembly, and the discharging and taking assembly comprises an upper base, a lower base and a lower base; a first spring is fixedly connected between the upper seat and the top of the lower seat; the top of the lower seat is uniformly in threaded connection with guide column casings, the surface of the lower seat is uniformly in sliding connection with elastic supporting sliding blocks, the inner bottom wall of the lower seat is uniformly in threaded connection with positioning clamping cylinders, the driving rods are vertically and slidably connected to the inner walls of the guide column casings and the positioning clamping cylinders respectively, and the top ends of the driving rods are in threaded connection with the bottom of the upper seat. Therefore, the device is reasonable in structure, the three-component microseismic sensor can be stably installed in a test well, meanwhile, the device has excellent recoverability and can be stably taken out of the test well after use is finished, secondary utilization of the device is greatly promoted, the production cost is effectively reduced, and the working efficiency is remarkably improved.

The invention provides a coal mine earthquake prediction method and system based on Bayesian reasoning, and the method comprises the steps: obtaining observed micro-earthquake event data in a coal mine region; a microseism prediction model is constructed, an optimal solution of model parameters of the microseism prediction model is obtained based on the microseism event data in the historical time period, and the model parameters comprise event triggering parameters and event occurrence parameters; the optimal solution of the model parameters is used as prior information, and posteriori distribution is obtained based on Bayesian reasoning for observed micro-seismic event data; and extracting posterior probabilities in a set probability range from the posterior distribution, obtaining the maximum magnitude corresponding to the prediction time period based on the model parameters corresponding to each posterior probability, and calculating the occurrence probability of the maximum magnitude event based on the maximum magnitudes corresponding to all the posterior probabilities in the set probability range and a given magnitude threshold.

The invention discloses an all-terrain ad hoc network high-speed data transmission method and system for microseism acquisition, and relates to the technical field of data transmission, and the method comprises the steps: constructing a layered network architecture, a first-layer central backbone network is provided with a Mesh chain communication structure, and a second-layer star acquisition network is provided with a star connection architecture; after being powered on, the seismic acquisition terminal acquires seismic signal data and accesses the seismic signal data to the target relay node; and the target relay node selects an optimal Mesh routing path according to a built-in path evaluation processor, forwards the seismic signal data to a preset master control node hop by hop, and uploads the seismic signal data to a seismic data processing server through a local communication module after receiving the seismic signal data, thereby completing centralized data processing. According to the invention, the technical problem of poor seismic signal data transmission stability due to dependence on fixed communication infrastructures in a complex field environment in the prior art is solved, and the technical effects of improving data transmission reliability, reducing network failure rate and overcoming unsmooth communication under a complex field surface condition are achieved.

The invention discloses a coal bed gas crossing fracturing demonstration and optimization method, which comprises the following steps: acquiring an underground rock core, carrying out mechanical and physical property parameter tests on a coal bed and an interlayer, and constructing a longitudinal multi-thin interbed geologic model based on a full-three-dimensional structured grid, including mechanical characteristics and stress characteristics of each thin layer; the positions of perforation points are changed, a segmented clustering scheme is completed, and the longitudinal layer penetrating effect of cracks is simulated; the fracturing construction parameters are optimized with the longitudinal crossing effect as a target, and the fracturing construction parameters comprise the displacement, the sand adding amount, the number of single-cluster holes, the gap distance and the number of intra-segment clusters; simulating the overall fracture form and fracture parameters through a full-three-dimensional fracture propagation simulation platform; micro-seismic testing is carried out to monitor the fracture crossing effect, and the effectiveness of fracture crossing fracturing construction parameters is demonstrated. According to the embodiment of the invention, aiming at a thin interbed type coal bed gas reservoir, horizontal well crack longitudinal crossing fracturing construction parameters are optimized, the coal bed gas yield is improved, and higher economic benefits are obtained.

The invention discloses a risk management and control method, system and equipment based on a water conservancy project, and relates to the technical field of risk management and control. A sensor data drift abnormal index is calculated by obtaining multi-source monitoring data of a target water conservancy project after an earthquake, and an engineering structure change abnormal index is calculated based on a preset structure health model and epicenter parameters; and calculating an earthquake propagation influence index by combining the seismic source distance, calculating an earthquake influence coefficient by combining the three factors, and judging whether an original risk early warning evaluation system needs to be updated according to the earthquake influence coefficient. According to the method, after a natural disaster event (such as a slight earthquake) is encountered, whether the risk early warning evaluation system needs to be updated or not can be judged according to the actual disaster degree; it is ensured that early warning is not delayed or invalid, and the possibility of causing larger potential safety hazards is reduced; meanwhile, whether the risk early warning evaluation system is updated or not can be reasonably judged according to the influence of the actual earthquake on the construction of the hydraulic engineering project, and unnecessary waste of computing resources is reduced.

The invention discloses a shale reservoir fracturing casing deformation calculation method, and relates to the technical field of shale oil and gas development. The method comprises the following steps: fusing microseism, logging, rock core and drilling and logging data, and constructing a fracture network-geomechanics coupling model; calculating a direction cosine matrix according to the fracture three-dimensional stress and the inclination angle, evaluating an activation risk, and screening out high-risk fractures; the triangular mesh boundary element solves the slippage as a displacement boundary, and an eight-node hexahedron elastic-plastic casing mesh is utilized to iteratively calculate a casing variable and draw a cloud picture; and a micro-seismic data real-time iteration model is newly added along with construction, and the perforation cluster distance, the fracturing scale, the displacement and the well spacing are dynamically optimized. According to the method, a large amount of on-site microseismic data is fully utilized, reservoir fracture fine description and slippage risk analysis are achieved, shaft multi-point casing variable prediction is completed, and key technical support is provided for deep shale gas development fracturing scheme decision and risk avoidance.

The present invention discloses an integrated online safety monitoring system for salt cavern storage areas, comprising: a data acquisition unit for collecting and converging online monitoring data of the safety of salt cavern storage areas, the monitoring data including safety production risk factor data, micro-earthquakes, wellbore leakage, ground subsidence and natural gas leakage; a data analysis unit for comprehensively analyzing the acquired monitoring data based on a gas storage reservoir risk assessment model to obtain analysis results; a monitoring unit for generating risk warning information in real time based on the analysis results, monitoring the dynamic risk status of the gas storage reservoir, and automatically displaying the generated risk warning information, the risk warning information including a safety risk spatial distribution map. Through the timely generation and monitoring of risk warning information, corresponding measures can be taken to prevent potential safety risks and ensure the safe operation of the gas storage reservoir.

The invention belongs to the field of microseism signal identification and positioning, and discloses a microseism identification method based on a neural network and a computer readable storage medium, and the method comprises the steps: enabling original seismic data to be used for initial seismic phase identification; opening a time window for the arrival time of the seismic phase identified for the first time on the seismic trace data, and calculating an amplitude value in the time window; when the amplitude value in the time window is abnormal, inputting the corresponding original seismic trace data into a validity judgment neural network, and identifying whether the original seismic trace data belongs to noise data or valid data; if the original seismic trace data is noise data, eliminating the original seismic trace data from the original seismic data to obtain noise-reduced original data, and using the noise-reduced original data for secondary seismic phase identification; and if the original seismic trace data are valid data, the original seismic trace data are reserved in the original seismic data, and the original seismic data are used for secondary seismic phase identification. According to the method, strong energy noise events are eliminated, the workload of processing personnel is greatly reduced, the labor cost is reduced, and cost reduction and efficiency improvement of microseism observation are realized.

The invention relates to the field of oil and gas development, in particular to a sandstone reservoir fracturing performance evaluation method which comprises the following steps: step 1, determining a plurality of fracturing performance evaluation indexes of a sandstone reservoir; 2, analyzing the influence rule of each factor on the fracture form; 3, obtaining a weight coefficient of the fracturing performance evaluation index; 4, defining a sandstone fracturing index, and determining a comprehensive fracturing coefficient of the sandstone reservoir; and 5, calculating a fracturing index and guiding fracturing well selection and layer selection. According to the method, a plurality of fracturing performance evaluation indexes of the sandstone reservoir are determined by utilizing a rock broken sample of the sandstone reservoir, different fracture forms are obtained by changing parameters such as rock elasticity modulus, fracture energy and minimum horizontal ground stress, and the fracturing performance of the sandstone reservoir is evaluated through micro-earthquake and volume fracturing data regression of a fractured well. The weight coefficients of the multiple fracturing performance evaluation indexes of the compact sandstone reservoir are obtained, so that the brittle interlayer is accurately judged, and the position of the fracturing perforation cluster is optimized conveniently.

The invention discloses a method and a device for predicting cracks based on micro-seismic data. The method comprises the following steps: determining a micro-seismic event B value according to the micro-seismic data of each fractured section; determining a natural seismic crack according to the microseismic event B value; determining a main fracture trend surface of a natural seismic fracture of each fracturing section through an earthquake magnitude weighted fitting algorithm, and determining fracture occurrence information of each fracturing section; and according to the fracture density of each fracturing section and the occurrence information, correcting fracture information predicted by adopting seismic data, and determining the fracture density and the fracture direction.

The invention provides a micro-seismic event identification method and device based on distributed optical fibers. The micro-seismic event identification method based on the distributed optical fibers comprises the following steps: acquiring energy channel data of distributed optical fiber sound wave data according to the channel number of the distributed optical fiber sound wave data of a target reservoir; determining a microseism event identification threshold according to the energy channel data; and recognizing the micro-seismic event of the target reservoir according to the energy channel data and the micro-seismic event recognition threshold. According to the micro-seismic event identification method based on the distributed optical fibers, the micro-seismic event identification curve can be obtained without channel-by-channel calculation, the micro-seismic event identification efficiency is improved, the storage amount of the acoustic wave data of the distributed optical fibers is reduced, and therefore the requirement for field real-time monitoring during fracturing is met, and the application prospect is wide. Moreover, the calculation process is simple and efficient, and technical support can be provided for microseism monitoring event identification and subsequent positioning during distributed optical fiber fracturing monitoring.

The invention discloses a fracturing crack fine characterization method and system based on microseism monitoring data, and relates to the technical field of oil and gas field development, and the method comprises the steps: obtaining basic parameters of a target well; according to the well completion data of the target well, the micro-seismic event points of all the fracturing sections of the target well are preprocessed, and the preprocessed micro-seismic event points of all the fracturing sections are obtained; noise reduction processing is carried out on the preprocessed micro-seismic event points of all the fracturing sections, and the micro-seismic event points of all the fracturing sections after noise reduction are obtained; clustering the microseismic event points after noise reduction according to the number of perforation clusters of the fracturing section, and determining effective microseismic event points of each perforation cluster; on the basis of the effective microseismic event points of each perforation cluster, through a crack surface fitting method, respectively obtaining characterization parameters of each perforation cluster crack; and according to the characterization parameter of each perforation cluster crack in the target well, obtaining a fracturing crack fine characterization result of the target well. According to the invention, fine characterization of the fractured crack can be realized.

The invention belongs to the technical field of underground ore body monitoring, and particularly relates to an underground mine cross-border mining dynamic monitoring method and system. The method comprises the following steps: (1) constructing a mine digital twinborn base map; (2) arranging a seismic source monitoring network on the basis of the mine digital twinborn base map, and carrying out micro-seismic monitoring and three-dimensional micro-motion exploration; and (3) a multi-dimensional intelligent dynamic monitoring and early warning platform is built through the mine digital twinborn base map and the data acquired by the seismic source monitoring network, and the multi-dimensional intelligent dynamic monitoring and early warning platform is used for realizing real-time pushing and three-dimensional visual display of the monitoring data and synthesizing a data analysis result to carry out border-crossing analysis research and judgment. And early warning information is sent in time for the suspected border-crossing mining event.

The invention provides a hot dry rock reservoir fracturing induced earthquake management and control system, which belongs to the field of hot dry rock development and supervision and comprises a fracturing construction monitoring subsystem, a microearthquake monitoring subsystem and a traffic light decision subsystem. The fracturing construction monitoring subsystem is used for monitoring fracturing construction data in the fracturing construction process and transmitting main construction parameters to the traffic light decision subsystem; the microseism monitoring subsystem is used for acquiring microseism waveform information, interpreting the microseism waveform information into microseism event data and transmitting the microseism event data to the traffic light decision subsystem; and the traffic light decision subsystem is used for comparing information parameters transmitted by the fracturing construction monitoring subsystem and the micro-earthquake monitoring subsystem with a plurality of set decision discrimination factors, judging and predicting the risk of inducing an earthquake event, carrying out graded early warning prompt on the earthquake risk through an indicator light, guiding the fracturing construction process in real time, and carrying out early warning on the earthquake risk. And the earthquake inducing risk is reduced.

The present invention discloses a real-time dynamic monitoring system for microseismic events based on 5G mobile communications, comprising a data acquisition module for acquiring microseismic signals; a sensor setting module for acquiring an optimal distribution scheme for wireless sensors; a signal conversion module for converting microseismic signals into 5G digital signals; a 5G base station for acquiring the arrival time of the 5G digital signal and transmitting it to an earthquake monitoring station; an earthquake monitoring station for monitoring the location of the earthquake source according to the arrival time; and an early warning module for issuing an early warning when a microseismic event is detected or when a wireless signal sensor fails. The present invention converts traditional microseismic signals into 5G digital signals through 5G communication technology and data signal processing technology, thereby realizing the acquisition of wireless data at the arrival time, speeding up data transmission while saving costs, achieving detection range coverage by planning sensor settings, and realizing identification and early warning of sensor failures.

The invention provides a micro-seismic event P-wave first arrival pickup method and device, and the method comprises the steps: obtaining micro-seismic monitoring data, and selecting a time window containing a wave crest in a P-wave first arrival preset range; establishing an initial Gaussian model; and inputting the selected time window data into the initial Gaussian model, performing iterative fitting, obtaining a final Gaussian model curve when iteration meets a preset condition, and determining the P-wave first arrival time according to the final Gaussian model curve. The invention provides a high-precision micro-seismic event P-wave first arrival pickup scheme based on Gaussian curve iterative fitting, realizes automatic and accurate pickup of P-wave first arrival time in micro-seismic signals, has relatively strong anti-noise capability, and is suitable for analysis of complex waveform data.

The embodiment of the invention relates to the field of earthquake detection, in particular to a micro-earthquake monitoring system. The system is suitable for monitoring a high-level waste disposal underground laboratory, and comprises a plurality of ground surface monitors arranged on the ground surface of the underground laboratory and used for monitoring micro-earthquakes of an underground shallow layer; a plurality of in-well monitors disposed in a peripheral well of the underground laboratory and disposed to monitor microseisms in the underground deep layer; the processor is arranged to receive data from the ground surface monitor and the in-well monitor respectively and determine the stability of the surrounding stratum of the underground laboratory based on the data, and the ground surface monitor and the in-well monitor are arranged at preset positions respectively so that the data provided by the ground surface monitor and the in-well monitor can improve the accuracy of determining the stability. A plurality of micro-seismic monitors are arranged on the earth surface and in a well at the same time, micro-seismic fluctuation of an underground shallow layer and a deep rock stratum is accurately recorded, the stability of the stratum is comprehensively monitored, and micro-seismic monitoring in a three-dimensional space is achieved.

The invention provides a multidirectional shallow well microseism monitoring seismic source positioning method. The multidirectional shallow well microseism monitoring seismic source positioning method comprises the following steps: step 1, arranging a multidirectional shallow well observation system to continuously collect fracturing microseism monitoring records; step 2, event identification and seismic phase first arrival pickup are carried out on the continuous micro-seismic monitoring records; step 3, carrying out polarization analysis on the microseism event, calibrating the orientation of the detector, and calculating signal-to-noise ratio information of the seismic phase of each stage of detector; and 4, setting a focus position search range, performing focus optimization on the events one by one, and taking the minimum value of the target function as an optimization target to obtain focus positioning results of all the events. According to the multidirectional shallow well microseism monitoring seismic source positioning method, mass weights recorded by different detectors are considered to construct an inversion positioning objective function to realize seismic source positioning, so that the positioning error of a microseism event can be reduced, and the reliability of fracture explanation is further improved.

The invention provides a micro-seismic monitoring P-wave energy compensation method and system, and belongs to the field of micro-seismic signal processing. The method comprises the steps of firstly constructing a P-wave first arrival pickup function, performing P-wave energy pickup, then constructing a P-wave energy linear compensation function by taking a transmission angle of a detector as an independent variable, and finally performing micro-seismic P-wave energy compensation by using the P-wave energy linear compensation function. In the prior art, a compensation method for energy attenuation caused by stratum absorption in a P wave propagation process is mainly used, but in the invention, the stratum influence is not considered, and an energy consistency correction technology is developed only aiming at large difference of P wave energy received by detectors at different monitoring distances of a same-level seismic source of a horizontal well. The P-wave energy of microseism P-wave signals excited by the same level of seismic sources at different monitoring distances at the detector terminal is equivalent or as close as possible.

The invention relates to the technical field of underground microseism monitoring, in particular to a method for correcting three-dimensional parameter values of an underground microseism monitoring fracturing horizontal fracture network, which comprises the following steps of: constraining the height of a fracture network by using the thickness of a single sand body of a target stratum; a single sand body constraint fracture height is obtained, an interval with the width being a constrained fracture network height value is selected in the horizontal axis direction of the fracture monitoring microseismic event height normal distribution diagram, the number of effective microseismic events with invalid noise points removed is obtained, and the number of the effective microseismic events with the invalid noise points removed and the effective ringing area fracture length are obtained; correcting the height of the post-fracturing fracture network and the length of the post-fracturing fracture network; according to the method, the seam height is restrained through the thickness of the single sand body of the target layer, the seam length and the seam width are determined in combination with the number of effective microseism events, the difference between a microseism monitoring crack result and a fracturing effective crack is determined, and the precision of three-dimensional parameters of a microseism monitoring crack network is remarkably improved.

The invention discloses a tight oil and gas reservoir horizontal well volume fracturing fracture network wave and volume prediction method, which comprises the following steps of: based on geological engineering parameters of a fractured horizontal well and microseism monitoring fracture volume data, calculating weight factors of each geological and engineering parameter by establishing a multi-factor evaluation model; aiming at a to-be-predicted fracturing section, combining the solved weight factor and the geological parameters of the perforation positions of the fracturing clusters in the fracturing section, and calculating a fracturing crack-making efficiency coefficient representing the distribution uniformity of fracturing fluid; multiplying the original micro-seismic monitoring fracture volume of the fractured section by the calculated fracture forming efficiency coefficient to obtain a corrected effective fracture network wave and volume; according to the method, the fracture forming efficiency coefficient is introduced to correct the original microseismic monitoring volume, the problem that prediction results of an existing method are generally large is solved, accurate quantitative prediction of the effective fracture network waves and the volume is achieved, and a scientific basis is provided for fracturing effect evaluation and scheme optimization.

The invention discloses a micro-seismic signal classification method based on genetic algorithm optimization. The method comprises the following steps: data acquisition: acquiring waveform data containing multiple types of micro-seismic event forms; preprocessing: carrying out mean value removal and band-pass filtering preprocessing on the obtained waveform data, and removing baseline drift and high-frequency noise interference; envelope calculation: respectively calculating a time domain envelope and a frequency spectrum envelope for the preprocessed microseismic signal; feature extraction: extracting a plurality of statistics and time frequency parameters from the time domain envelope and the frequency spectrum envelope to form a feature complete set; feature selection and classifier optimization: utilizing a genetic algorithm to perform joint search optimization on structure parameters and feature subsets of the multi-layer perceptron; and training and verification: training the multilayer perceptron by using the optimized feature subset and the network structure, and evaluating the classification accuracy on a verification set. The method can realize high-precision classification, has robustness to noise, and can be widely applied to the fields of microseism monitoring, blasting event monitoring, other vibration source identification and the like.