32687 results about "Petroleum engineering" patented technology

A cable trough for installing cables alongside a railway line or other right of way is described. The cable trough is constructed using longitudinally oriented reinforcing fibers coated with polymeric resin that generally aligns the reinforcing fibers with the length of the cable trough. One or more connector clips may be used to secure respective portions of the cable trough to one another. The cable trough is provided with a cover that may be removably secured to an elongate channel to protect the cables housed within the cable trough. Elbows, corners, tees, and other connectors may be provided to run the cable trough in any desired direction. A method of installing cables in a cable trough is also described.

The invention relates to the field of shale oil and gas, and discloses a method for identifying a shale oil and gas reservoir dessert, which comprises the following steps: acquiring a core CT image, three-dimensional seismic data and production dynamic data, and carrying out cross-scale preprocessing; constructing a fractional-order non-local seepage field model to represent nano-to-kilometer-level flow characteristics; predicting seepage field parameters through a Lie group symmetry constrained neural network; establishing a cross-scale coupling model of the quantum adsorption effect and the macroscopic seepage law; dynamically updating model parameters based on real-time monitoring data; and executing multi-target collaborative optimization to generate a sweet spot three-dimensional distribution and development scheme. According to the method, a fractal dimension dynamic constraint cross-scale data fusion technology is adopted, the effect of accurate mapping of nanopore and macroscopic fracture network parameters is achieved, and the problem of misalignment of CT scanning and seismic inversion data space registration is solved through pore communication fractal analysis.

The invention belongs to the technical field of petroleum pipeline inner wall defect detection, and particularly relates to a petroleum pipeline inner wall defect detection system which comprises a pipe section division module, a wall thickness analysis module, a straight pipe section detection module and a bent pipe section detection module. Ultrasonic incident detection and eddy current scanning are synchronously carried out in areas with different wall thicknesses, eddy current and ultrasonic dual-mode detection are fused to generate a three-dimensional map containing defect boundary and depth information, a deposition risk area is divided on the basis of stress distribution of flow field simulation of a bent pipe section, an adaptive defect detection mode is adopted in different areas, and the defect detection accuracy of the bent pipe section is improved. Therefore, targeted detection of the defects of the inner wall of the petroleum pipeline is realized, missed identification is avoided to a great extent, and the completeness and reliability of defect detection can be greatly improved.

The invention relates to the technical field of gas pipeline safety assessment, in particular to a gas pipeline safety assessment early warning system and method based on data analysis. The method comprises the following steps: collecting gas pressure data of a gas pipeline at multiple points at the same time, carrying out time-space synchronization processing to obtain aligned gas pressure data so as to construct a continuous gas pressure field of the pipeline, based on the gas pressure field, identifying the pressure distribution difference of the pipeline, estimating the transient flow velocity of the gas, continuously recording the transient flow velocity of the gas, and deducing the change of the flow velocity. Judging the deformation condition of the inner wall of the pipeline in combination with air pressure field data, positioning a deformation area, reconstructing a pipeline frame, analyzing deformation response, identifying a deformation type, identifying a corrosion evolution trend, performing safety evaluation, judging the gas circulation degree and performing physical safety evaluation. According to the invention, dynamic monitoring of the gas pipeline is realized, a data-driven safety management mode is promoted, the early warning capability of potential risks is improved, and a more intelligent safety assessment and early warning mechanism is formed.

The invention relates to an oil bearing carrying capacity evaluation method based on virtual simulation, and the method comprises the steps: obtaining working condition data samples of an oil bearing in a plurality of typical operation states under a complex working condition of a composite load, and carrying out the marking of bearing structure partitions, so as to build a working condition partition mapping table; establishing a multi-physics field sensitive area identification model for each partition, and performing dynamic parameter adjustment on the global finite element model and the local high-precision infinitesimal sub-model by using a multi-physics field coupling calibration factor; and performing time sequence feature extraction on a multi-physical field joint simulation result after dynamic parameter adjustment to obtain a multi-dimensional parameter sequence related to the typical failure mechanism of the oil bearing.

The invention discloses a coal and rock mass fracture instability multivariate signal fusion analysis method, and belongs to coal and rock mass analysis. The method comprises the following steps: carrying out time-frequency domain processing on an acoustic emission signal to obtain an accumulated ringing characteristic value # imgabs0 # and an accumulated b characteristic value # imgabs1 #; a main control frequency characteristic value # imgabs2 # and an amplitude characteristic value # imgabs3 # are accumulated; a spatial characteristic value # imgabs4 # of acoustic emission; fitting a fitting function # imgabs7 # from the characteristic value # imgabs5 # to the characteristic value # imgabs6 # respectively; according to the fitting function # imgabs8 #, calculating a correlation coefficient matrix R between the characteristic values # imgabs9 # to # imgabs10 #; according to the matrix R, determining a weight coefficient # imgabs11 # of each characteristic value; a first-order derivative function # imgabs13 # and a second-order derivative function # imgabs14 # of the fitting function # imgabs12 # are obtained, and according to the first-order derivative function # imgabs15 # and the second-order derivative function # imgabs16 #, a demarcation time point # imgabs17 # in the coal and rock mass damage process is determined; and the boundary time point # imgabs19 # is corrected by using the weight coefficient # imgabs18 #, and a corrected boundary time point # imgabs20 # is obtained. In order to solve the problems that an existing coal and rock mass fracture instability judgment index is single, and coal and rock mass fracture instability early warning is low in single index precision, the early warning precision is improved through multi-element signal fusion.

The invention provides a method for evaluating the grouting water control effect of an underground water-sealed cave depot project. The method comprises the steps that firstly, grouting and geological parameters and hydrological monitoring data of a project area are obtained; establishing a three-dimensional seepage-grouting coupling model, and simulating the dynamic state of a seepage field by using a finite element analysis algorithm; then calculating the equivalent permeability change rate of the grouting affected zone based on a simulation result; constructing an evaluation index system, and performing quantitative evaluation by using a fuzzy comprehensive evaluation algorithm; and finally, generating a grouting parameter dynamic adjustment scheme according to an evaluation result. According to the method, scientific and accurate evaluation and engineering optimization of the grouting water control effect can be achieved, and the safety and economical efficiency of engineering are improved.

The invention provides a water conservancy data acquisition supervision method and system based on big data analysis. The method comprises the following steps: firstly, obtaining dam body surface temperature field data, reservoir water level time sequence monitoring data and a dam body three-dimensional structure, and carrying out environmental radiation interference elimination processing on the temperature field data; secondly, extracting temperature fluctuation amplitude time sequence characteristics and water level change rate in the corrected temperature field data, and constructing a matrix reflecting correlation strength of the temperature fluctuation amplitude time sequence characteristics and the water level change rate through dynamic correlation analysis; and identifying temperature fluctuation abnormal points by using the matrix, and generating a seepage correlation map in combination with the water level change rate. And dividing seepage state categories according to the water level change rate, and generating a leakage risk probability distribution diagram by combining periodic trend prediction. And finally, fusing the graph with a dam body three-dimensional structure to generate positioning supervision information with a seepage abnormal identifier. The technical scheme provided by the invention can improve the efficiency and accuracy of water conservancy data acquisition supervision.

A method and device for optimizing comprehensive production of an oil reservoir. The method comprises: on the basis of historical production data, performing regional level recognition, single-well level recognition, and production optimization model recognition, and updating oil reservoir dynamic recognition; on the basis of the historical production data, using the following steps to perform cyclic historical fitting on model parameters of a plurality of production optimization models: performing historical fitting on the model parameters, and performing well-to-well communication relationship calibration on the plurality of production optimization models; determining, on the basis of the updated oil reservoir dynamic recognition, a constraint condition corresponding to each production optimization model, solving an objective function corresponding to each production optimization model, obtaining an optimal decision variable corresponding to each production optimization model, and obtaining a development regulation scheme corresponding to each production optimization model; obtaining a comprehensive development regulation scheme of an oil reservoir; and updating the oil reservoir dynamic recognition on the basis of a regulation effect obtained by real-time monitoring of a development operation.

The invention discloses a multi-source collaborative advanced geological exploration method based on TBM construction, and belongs to the technical field of tunnel engineering geological exploration. A three-dimensional geological model is constructed through multi-scale collaborative operation of directional long exploration drilling, branch short exploration drilling and in-hole transient electromagnetic detection; the directional long exploration adopts a secondary drilling structure and a screw motor directional drilling technology to realize accurate control of a deep stratum, the branch short exploration realizes dynamic and rapid verification through a TBM integrated drilling machine, meanwhile, in-hole transient electromagnetic exploration adopts three-component measurement and an intelligent inversion algorithm to fill the blank of geological information between drill holes, and by means of mutual data correction of the three methods, the detection accuracy is improved. A three-in-one detection system of drilling, geophysical prospecting and intelligent analysis is formed, and then accurate advanced prediction is achieved, so that the problems that a traditional single detection technology is low in precision and insufficient in coverage range are effectively solved, the water inrush risk is remarkably reduced, construction safety is guaranteed, and the method is effectively suitable for deep tunnel TBM safety construction.

The invention relates to the technical field of coal mine safety monitoring, in particular to an underground coal mine dust concentration monitoring method and system based on multi-modal data fusion, and the method comprises the steps: synchronously collecting dust concentration time sequence data, dust image data, sound wave signal data and environmental parameters through a multi-modal sensor array deployed in an underground coal mine; carrying out preprocessing and feature extraction on the collected data; predicting the decomposed high-frequency and low-frequency component signals by adopting a long short-term memory neural network and a grey Markov model; when the environment humidity is greater than 80%, carrying out light scattering compensation on the predicted value; inputting various predicted values into an improved D-S evidence theory fusion device, and outputting a fusion dust concentration monitoring value; and when the threshold value is exceeded or the temperature and humidity composite condition is reached, an acousto-optic alarm is triggered and a spraying dust-settling device is started. According to the method, the problems of low precision of a single sensor, multi-source data conflict, high-humidity environment measurement deviation and insufficient time sequence and fusion precision in underground coal mine dust concentration monitoring can be solved.

The invention provides a while-drilling formation pressure early warning method and device based on model prediction, equipment and a medium, and relates to the technical field of low-carbon mining, and the method comprises the steps: in a pre-drilling stage, based on seismic data, adjacent well historical data and design data, analyzing and generating prediction risk data of a target monitoring well; in the drilling process, actual formation pressure data are calculated in real time by using drilling data collected for a target monitoring well in real time, and the actual formation pressure data are compared with the predicted risk data; in the drilling stage, a pressure safety window is depicted based on the predicted risk data, the cycle equivalent density of the target monitoring well calculated in real time is compared with the safety window, and the drilling safety risk is recognized and analyzed; and after drilling is finished, summarizing the predicted risk data, the actual formation pressure data and the drilling safety risk, and updating and iterating the model algorithm through the summarized data. The method has the effect of improving the accuracy of formation pressure early warning while drilling in the petroleum drilling process.

A fuzzy cloud-based risk assessment method for reservoir operation schemes, including: collecting basic data of target reservoirs; constructing optimal operation model of conventional reservoirs to obtain model calculation results; acquiring change process of operation characteristics during whole operating period according to model calculation results, and constructing multi-level reservoir multi-dimensional risk assessment index system; dividing different risk level intervals according to multi-level reservoir multi-dimensional risk assessment index system; obtaining large number of sample data xij of reservoir risk index under corresponding working conditions by multiple parallel calculations to conduct risk assessment; calculating cloud digital features of different indexes by inverse cloud generator; and weighting indexes in index layer and criterion layer by Analytic Hierarchy Process to obtain multi-dimensional risk assessment results. In order to promote sustainable development and utilization of water resources and enhance level of reservoir risk management, scientific evaluation of reservoir risk is conducted by comprehensively considering various uncertainties.

The present invention relates to a coal mine intelligent directional drill and its drilling method, belonging to the technical field of coal mine drills. It comprises a moving platform, machine frame, clamper, main manipulator, power head, drill pipe storage system, control system, and hydraulic system. The power head structure is improved by adding an angle adjuster with accurate angle adjustment, locking, and anti-rotation functions. The angle adjuster is positioned on the gearbox side opposite the main motor, connected via a driving shaft. The control system includes a toolface azimuth detection and initialization system that works with the angle adjuster. This solves prior issues such as the absence of specialized toolface azimuth adjustment devices, low precision, low track adjustment efficiency, and challenges in achieving automatic directional drilling in the prior art. The invention enhances precision and efficiency, enabling automated, intelligent directional drilling.

The invention discloses a high-precision drilling control method and system for a multi-layer PCB, and relates to the technical field of intelligent control. The method comprises the following steps: scanning and analyzing to obtain layered material characteristics and structural size information of a multi-layer PCB, and carrying out clamping fixation and positioning hole processing on the multi-layer PCB to obtain a PCB positioning hole; a drilling machining three-dimensional coordinate axis is constructed; a PCB drilling strategy space is constructed, the PCB drilling strategy space is adopted to conduct drilling analysis on the layered material characteristics and the structure size information in sequence according to the PCB drilling machining requirement, and layered drilling strategy parameters are obtained; and the layered drilling strategy parameters are mapped to a drilling processing three-dimensional coordinate axis for space route fusion, layered drilling processing parameters are determined, and high-precision drilling and quality detection closed-loop control are executed on the multi-layer PCB. The technical problem that in the prior art, the positioning precision is low in the drilling process of the multi-layer PCB is solved, and the technical effect of improving the drilling machining precision of the multi-layer PCB is achieved.

The invention provides an underground water source water supply safety assessment method and system, and relates to the technical field of water supply safety assessment. The method comprises the steps of obtaining a permeability distribution diagram, dividing grids and analyzing direction changes, constructing an edge set to extract a closed form to generate a partition layer, setting measuring points to collect water level data, evaluating a change consistency screening path, matching a boundary to judge a crossing condition, marking a sudden change position, recording an interference path and establishing a recognition list. According to the method, by comparing the consistency of the water level direction in unit time and the response fluctuation, the path line segment with the hydraulic coherence characteristic is identified, the depicting ability of the actual underground water flowing path in the non-uniform supply environment is improved, the path trend sudden change and boundary overlapping position is analyzed, the response identification of the structure interference action area is enhanced, and the accuracy of the structure interference action area is improved. A key section with water supply interruption or supply abnormity is positioned, and the response capability of actual hydrological and geological changes and the spatial fineness of evaluation and judgment are improved.

The invention relates to the technical field of geothermal drilling monitoring management, in particular to a construction monitoring system and method for geothermal drilling. The method comprises the following steps: constructing a state variable set, quantifying structural disturbance intensity by adopting a disturbance derivative method, normalizing the structural disturbance intensity, and defining a state transition tensor mapping behavior influence coefficient; in combination with the high-order derivative of the disturbance trend function and the behavior collaborative change matrix, an offset risk factor is generated through fusion for early warning; dividing a well drilling area into three-dimensional grids, calculating local stress potential energy, adjusting weight through a dynamic sensitive belt, and generating a risk distribution diagram through smooth filtering; performing closed-loop dynamic regulation and control by using risk potential energy centroid coordinates and gradient field inversion intervention vectors for medium and high risk areas; and through multi-period risk potential energy tensor analysis, calculating the matching degree of a self-healing index and a stable cone region, evaluating the self-healing capability of the system and feeding back a regulation and control strategy. According to the invention, a closed-loop monitoring and active control system for nonlinear risks of geothermal drilling is formed.

The invention relates to the technical field of directional drilling track control, and discloses a coal mining underground directional drilling track control method and system, and the method comprises the steps: carrying out the fusion track analysis of a drilling machine based on sensor data, drilling parameters and pre-obtained geological hardness parameters, and obtaining a reference track of the drilling machine, a sensor, an azimuth angle sensor and a bit pressure sensor are used for synchronously collecting drill bit attitude data of a drilling machine to generate a real-time track of the drilling machine, then track offset calculation is carried out to obtain inclination angle deviation and azimuth angle deviation, and dynamic gain adjustment analysis is carried out on the drilling machine to obtain adjustment parameters of the drilling machine. And finally, the drill bit posture of the drilling machine is adjusted based on the adjusting parameters. According to the method, the directional control accuracy of the underground drilling track can be improved.

The invention provides an intelligent speed regulation control method and system for hydroelectric generating set multi-source data fusion, and relates to the technical field of hydropower station automation control, and the method comprises the steps: S1, collecting multi-source heterogeneous data, including mechanical quantity, hydraulic parameters and electrical quantity, in the operation process of a hydroelectric generating set; s2, performing standardized preprocessing on the multi-source heterogeneous data to obtain preprocessed data; s3, on the basis of the preprocessed data, global deep state feature information and operation trend prediction information of the hydroelectric generating set are extracted through a multi-layer data fusion algorithm, and a fused speed regulation decision basis is obtained; s4, generating a speed regulation control instruction for regulating the rotating speed of the hydroelectric generating set based on the fused speed regulation decision basis; and S5, performing speed regulation control on the hydroelectric generating set according to the speed regulation control instruction. Through multi-layer data fusion and a dynamic self-adaptive control strategy, comprehensive perception and accurate regulation and control of the operation state of the hydroelectric generating set are realized.

The invention discloses a deep water-rich weak-impact coal seam surrounding rock control method based on rapid tunneling, and relates to the technical field of surrounding rock control. The method comprises the steps that S1, a high-risk area is identified through address detection, a waterproof curtain is constructed, and the tunneling disturbance risk is reduced; s2, rapid tunneling and instant supporting are conducted, the surrounding rock exposure time is shortened, tunneling and supporting are completed synchronously, and deformation development is restrained; s3, sensing a surrounding rock-support response in real time, optimizing parameters and early warning risks, and realizing dynamic monitoring and feedback regulation and control; s4, later-stage continuous reinforcement maintenance is conducted, so that the roadway adapts to the rheological characteristics of deep surrounding rock, and the service cycle of the roadway is prolonged; according to the method, a high-risk area is identified through various detection technologies, and instant supporting is achieved through cutting process optimization and digging and supporting collaborative operation; real-time monitoring and dynamic feedback are achieved, and automatic optimization of supporting parameters is achieved; and later reinforcement and periodic maintenance are adopted to ensure that the surrounding rock supporting system can adapt to the rheological characteristics of deep surrounding rock for a long time.

The invention discloses a multi-factor prospecting prediction method suitable for tin polymetallic ore, and relates to the technical field of geological science. The prospecting prediction method comprises the following steps: collecting data; fusing multi-source data; extracting and analyzing mineralization information; constructing a comprehensive prediction model; and predicting mineralization. According to the method, a potential tin polymetallic ore deposit area is preliminarily selected by comprehensively considering multi-source information such as geology, geophysics, geochemistry and remote sensing, drilling data and profile data are collected in the area, the drilling data and the profile data are utilized to construct a comprehensive prediction model, and the model is combined with advanced algorithms such as geostatistics and machine learning, so that the prediction accuracy of the tin polymetallic ore deposit area is improved. The multi-source data is efficiently integrated, and a three-dimensional visualization result is provided, so that the position and the scale of a potential ore body can be more accurately predicted, and the success rate of prospecting is improved.

The invention provides a high-negative-pressure gas extraction drill hole full-life-cycle efficiency evaluation method, and belongs to the technical field of mineral exploitation. A ground stress distribution model is established through microseism monitoring to determine drill hole arrangement parameters; a distributed optical fiber sensing system and a multi-parameter gas flow meter are used for monitoring the stress change around a drill hole and gas extraction data in real time, the coal fracture development degree is obtained in combination with sound wave testing, and all the data are input into a physical numerical value coupling model to calculate a permeability dynamic evolution curve. Establishing a permeability influence coefficient matrix and determining a key parameter weight, constructing an evaluation index system including the extraction amount, the permeability change rate, the drilling life and the coverage range, and performing multi-objective optimization configuration by applying a Pareto optimal solution theory. The technical problem that full-life-cycle dynamic monitoring and comprehensive efficiency evaluation of the high-negative-pressure gas extraction drill hole are lacked at present is solved.

The invention provides a shield adaptability adjusting method based on a stratum structure, which comprises the following steps: acquiring geological parameters of a construction area of a shield tunneling machine through drilling and geophysical prospecting, and arranging sensors at key positions of the shield tunneling machine to acquire construction parameters of the shield tunneling machine in real time; a convolutional neural network CNN is adopted to analyze the geological parameters to identify stratum features, and a geological model is constructed based on the identified stratum features; constructing a disaster risk index system, and predicting a disaster risk based on the geological model and the construction parameters by adopting Logistic regression and a random forest algorithm; according to the predicted disaster risk, the cutterhead configuration of the shield tunneling machine is dynamically adjusted, and tunneling parameters are optimized or a muck improvement scheme is adopted; by monitoring geological parameters, construction parameters and environmental changes in real time, a multistage early warning mechanism is adopted to trigger emergency response measures, and construction safety is guaranteed. According to the method, the safety and efficiency of shield construction can be improved, the geological disaster risk is reduced, and reliable technical guarantee is provided for underground space development.

The invention relates to the technical field of drilling parameter control, in particular to an exploration drilling parameter control method and system.The method comprises the following steps that a drilling target and a target priority corresponding to the drilling target are set, and the target priority indicates the importance of the drilling target; acquiring various measurement data in the drilling process, and processing the various measurement data; according to the processed multiple measurement data, the current stratum characteristics and the current drilling tool operation state are recognized; according to geological information in the drilling process, the drilling target and the target priority are adjusted; according to real-time geological information and a drilling state, a drilling target and a parameter control strategy are dynamically adjusted, so that the method has the advantages of better adapting to complex stratum changes, optimizing tradeoff among multiple targets and improving drilling self-adaptability and control precision.

The invention relates to the technical field of unconventional oil-gas exploration, and discloses a well-seismic integrated horizontal well geosteering risk evaluation method, which comprises the following steps: S1, acquiring three-dimensional seismic data, measurement while drilling data and geological logging data through a well-seismic integrated data acquisition platform; s2, constructing a horizontal well geosteering dynamic model based on multi-source heterogeneous data, and integrating a seismic inversion result and real-time drilling parameters; by establishing a well-seismic data dynamic fusion mechanism and a multi-source risk quantification model, the problem of space-time dislocation of seismic inversion and measurement-while-drilling data is solved, the recognition precision of a fault boundary, a lithologic interface and a pressure abnormal zone is ensured to be matched with drilling position changes in real time, risk misjudgment caused by model updating lag in a traditional method is eliminated, and the accuracy of the method is improved. The accuracy and timeliness of geosteering decision making of the complex structure area are improved; by monitoring well track deviation and geological model prediction deviation in real time, the risks of well wall instability and target deviation are avoided, and the operation safety of the horizontal well in the full life cycle is guaranteed.

The invention discloses a low-carbon stability conjoint analysis method and system for underground engineering, and particularly relates to the technical field of engineering modeling optimization, and the method comprises the steps: obtaining rock-soil mechanical parameters, construction parameters and full-life-cycle carbon emission factor data of a target area; dividing a collaborative optimization region based on parameter fusion and identifying a conflict section; constructing a mechanical stability numerical model and a carbon emission quantitative model, outputting double indexes, and generating a double-target optimization decision space through dynamic weight distribution; traversing and screening candidate schemes meeting a safety threshold and carbon emission constraints, and extracting an anti-interference Pareto solution set in combination with geological sensitivity simulation; a low-carbon-stability balance scheme is generated through reverse coupling verification, and full-life-cycle low-carbon stability optimization support is provided for complex geological engineering.

The invention discloses a deep coal mine disaster early warning method and system based on a geological radar, and relates to the technical field of disaster early warning, and the method comprises the steps: carrying out the monitoring coverage analysis of a target monitoring region, laying geological radar equipment according to a result, and constructing a geological radar array; scanning a mine underground structure through an array to obtain a rock stratum data array; performing spatial hierarchical feature recognition on the rock stratum data array to obtain rock stratum risk feature distribution; calling historical data to obtain a plurality of historical risk feature distributions; and performing risk trend prediction on the rock stratum risk feature distribution according to the historical distribution, and outputting a predicted disaster critical working condition. The technical problem that the real-time performance and the accuracy of disaster risk identification are insufficient due to the fact that a traditional coal mine disaster early warning method depends on low-frequency and single-dimension monitoring data is solved, and the technical effect of improving the accuracy and the real-time performance of coal mine disaster early warning is achieved.

The invention discloses a coal fire area fracture active enhancement detection test system and method, and belongs to the technical field of mine safety and geophysical exploration, and the system comprises a fracture generation module which is used for simulating a heat-force-gas coupling condition of an underground coal fire area, and inducing a coal rock mass test piece to generate a fracture; the fracture detection module is used for synchronously acquiring multi-physics field data of the coal and rock mass test piece in real time; the fracture intervention module is used for injecting a natural medium simulant and an enhanced medium foam gel material into the fracture so as to simulate a real environment and enhance a detection signal; and the intelligent feedback and data fusion module is used for controlling operation parameters of each module, synchronously acquiring detection data, and performing fusion processing, intelligent inversion and four-dimensional visualization on the detection data to realize whole-process monitoring detection of fracture evolution. The invention provides a scientific method for precise delineation and targeted plugging treatment of hidden fractures in a coal fire area, and solves the problems of multiplicity of solution in traditional fracture detection and easy reburning in coal fire treatment.

The invention discloses a coal mine rock burst risk assessment system which comprises a data acquisition module, an energy accumulation rate calculation module, a roadway network modeling module, a risk assessment module and an early warning regulation and control module. The method comprises the following steps of: firstly, calculating an energy accumulation rate of a roadway, then constructing a roadway network diagram, identifying a high stress conduction path, calculating a dynamic risk index and delimiting a risk area by integrating factors such as a historical impact event and an energy index, and automatically triggering corresponding early warning and regulation measures by a system according to a risk level so as to realize accurate early warning and dynamic regulation. And mine operation decision making and accident prevention are assisted.

The invention belongs to the technical field of tunnel and underground engineering intelligent construction and geotechnical engineering informatization, and discloses a high-energy geological environment surrounding rock classification and decision-making method based on digital twinning and multi-source feedback. The problems caused by difficulty in realizing surrounding rock state dynamic sensing, multi-source data fusion classification and construction decision closed-loop linkage in the prior art in a high-energy geological environment are solved. The method comprises the following steps: firstly, constructing a tunnel three-dimensional geology-structure digital twinborn body based on initial survey data; in the construction process, multi-source data such as geology, construction disturbance and surrounding rock response are collected in real time through the Internet of Things technology and mapped to the digital twinborn body, and virtual-real synchronous updating is achieved. And then, constructing a deep learning-parameter inversion hybrid model on the basis of the multi-source fusion data, outputting a dynamic surrounding rock classification index DRCI and key mechanical parameters, inputting the DRCI and the key mechanical parameters into a multi-objective optimization module, and giving a self-adaptive drilling and blasting scheme. And finally, reversely correcting the model through a construction feedback result to realize closed-loop self-learning.