197 results about "Rock types" patented technology

The invention provides a rock image classification method based on edge enhancement and multi-scale feature fusion. By combining the edge enhancement and multi-scale feature fusion technology, the accuracy of mineral classification in the rock slice image is remarkably improved. According to the method, rock slice image interference is eliminated through filtering and denoising, and mineral particle edges are enhanced by fusing morphological top-hat transformation and a Laplace operator; and performing multi-scale pyramid decomposition on the enhanced image to extract high-frequency information, performing multi-direction response enhancement to generate a direction feature map, and performing channel-level fusion on the original image, the edge enhanced image and the direction feature map. And finally, inputting the fused image into a convolutional neural network to complete rock type classification. According to the method, mineral boundary expression is effectively enhanced, the classification accuracy is improved, and a reliable technical scheme is provided for geological analysis and lithology identification.

The invention discloses a borehole pressure monitoring system based on multi-modal information fusion, and particularly relates to the technical field of multi-modal information fusion. Comprising a drilling pressure monitoring area division module, a multi-modal information data acquisition module, a multi-modal information data analysis module, a drilling pressure multi-modal information fusion module, a drilling pressure monitoring and early warning module and a drilling pressure monitoring man-machine interaction module. The drilling pressure monitoring area division module is used for taking drilling operation as a target area and dividing the target area into a plurality of monitoring sub-areas according to equal time periods; according to the method, the pressure-rock type parameter is analyzed to obtain an index to evaluate the influence degree of the rock type on the drilling pressure, and in the multi-modal information fusion process, the fusion algorithm and parameters can be adjusted according to different rock types, so that the method can better adapt to the mechanical properties and drilling pressure response characteristics of different rocks, and the method has good application prospects. And the accuracy and the reliability of drilling pressure monitoring are further improved.

The invention discloses a mineralization center determination method and device based on multi-source remote sensing data, relates to the technical field of remote sensing image recognition, and aims to solve the problem that existing mineralization center determination is low in accuracy. Comprising the following steps: acquiring hyperspectral data of a target area and an actually measured rock and mine spectrum set; carrying out spectrum characteristic analysis according to the actually measured rock-mine spectrum set, and determining an absorption intensity abnormal region and an altered rock type corresponding to the absorption intensity abnormal region; according to the hyperspectral data and the alteration rock wave spectrum, alteration information is extracted by adopting a maximum noise ratio method and a hybrid modulation matched filtering method, and target alteration information is obtained; and determining a mineralization center of the target area based on the absorption intensity abnormal area, the altered rock type and the target alteration information. The method for determining the mineralization center based on the multi-source remote sensing data is used for improving the accuracy of alteration information in a mode of combining the actually measured rock and mine spectrum and the hyperspectral data, so that the determined mineralization center is more accurate.

The invention provides a pore-scale underground natural hydrogen migration and accumulation behavior prediction method, and belongs to the field of underground natural hydrogen exploration and exploitation. Comprising the following steps: reconstructing an underground porous medium according to a real geological structure image; establishing an empirical formula of fluid attributes such as wettability, interfacial tension and viscosity of the hydrogen-water-rock system and temperature, pressure, salinity and rock type; establishing a flow equation of the hydrogen-water two-phase system in the porous medium; after initial conditions and boundary conditions are determined, the initial distribution, migration and aggregation process of natural hydrogen in the porous medium is simulated; and after the flow is stable, a migration and accumulation image of the hydrogen-water-rock system and a hydrogen recovery rate change curve are obtained. The hydrogen-water two-phase migration-accumulation model constructed by the method is suitable for the characteristics of high density ratio and high viscosity ratio of hydrogen and water, and is good at treating a porous medium complex structure and identifying a hydrogen-water interface; and the method is oriented to a real underground reservoir, and is suitable for predicting the hydrogen-water-rock migration and accumulation process under no environmental factors.

Systems and methods include obtaining well log data and core sample data of a subsurface formation; generating, based on the well log data and the core sample data, an unconfined compressive strength log for the subsurface formation; using an unsupervised machine learning model to form rock type clusters based on the unconfined compressive strength log and the well log data; forming a training dataset including the well log data, the training dataset labeled based on the rock type clusters; training a supervised machine learning model using the training dataset. While drilling a well in the subsurface formation, logging-while-drilling data is obtained from drilling equipment used to drill the well; and rock types in the subsurface formation are determined using the supervised machine learning model and the logging-while-drilling data.

The invention belongs to the technical field of geological prospecting, and particularly discloses an exploration method for constructing an altered rock type gold mine in a shallow coverage area, which comprises the following steps of: firstly, optimizing a working area by using regional geochemical prospecting abnormity, and gradually reducing a prospecting target area by using 1: 25,000 geochemical measurement, 1: 10,000 soil profile measurement and 1: 10,000 geological grass survey; identifying a linear negative topographic development section by using an unmanned aerial vehicle, quickly positioning a gold-bearing structure alteration zone by using a manner of stripping soil and adopting a detection sample, and performing ground surface control by using a groove exploration project; and a target position is predicted by combining the ore body grade, the ore body thickness and the product contour map of the ore body grade thickness by utilizing a structure superposition halo method, drilling engineering deep verification is carried out, and finally the topography and the landform are recovered to find out the shape, the occurrence, the scale and the resource potential condition of the gold mineralized body. The method is simple and convenient, small in environmental disturbance, low in cost investment and good in coverage area effect, the purpose of rapid prospecting is achieved, and an excellent gold ore prospecting effect is achieved in the Heidong region of the Qieemun Tagean, the cliff and the Qieemun Tagean.

Disclosed is a mapping method of landslide threat range based on equivalent friction coefficient and trend analysis, which includes the following steps: obtaining physical parameters of a landslide, and obtaining a volume of the landslide according to an area in the physical parameters; selecting relevant parameters based on a rock type in the physical parameters, and obtaining the equivalent friction coefficient according to the relevant parameters and the volume; obtaining a landslide runout distance according to the equivalent friction coefficient, determining coordinate points of a hyperbola and a front edge boundary range according to the landslide runout distance, and performing a hyperbolic fitting on two side boundaries of the landslide according to the coordinate points to obtain a side boundary range; generating the landslide threat range based on the front edge boundary range and the side boundary range.

The invention provides a potential safety hazard analysis method and system based on underground cavern three-dimensional geological intelligent modeling, and the method comprises the steps: firstly, based on underground cavern three-dimensional model data, cutting the underground cavern three-dimensional model data into a plurality of sub-models according to a geological condition segmentation rule, and enabling the geological condition segmentation rule to dynamically adjust the cutting spacing according to the gradient change characteristics of a rock stratum; performing gradient analysis on the longitudinal and axial rock stratum attributes of each sub-model to generate rock stratum transition characteristic data containing the adjacent rock stratum attribute change rate and the transition area space distribution, and dynamically identifying the surrounding rock type of the sub-model according to the rock stratum transition characteristic data; and mapping and matching the surrounding rock identification result with a preset protected object space coordinate, collecting a sub-model geological parameter set in real time, finally triggering a safety early warning signal according to a geological parameter set numerical value interval, and generating an emergency disposal scheme set associated with the safety early warning signal, so that the potential safety hazard of the underground cavern can be effectively analyzed.

The invention relates to an alkaline miscellaneous rock type niobium ore prospecting method, which belongs to the technical field of geological prospecting, and comprises the following steps: systematically carding regional geological structure evolution and stratum lithology distribution, and mastering the distribution range, rock type and geological age of alkaline miscellaneous rocks; a gravimeter is adopted for measurement, and gravity abnormal data are obtained; the method comprises the following steps: collecting sediment samples in a water system in a target area, analyzing the content of niobium in the sediment, collecting surface and deep soil samples in a niobium element enrichment area, analyzing the content of the niobium element, collecting remote sensing image data in the target area, highlighting geological information related to alkaline miscellaneous rocks, and calculating the content of the niobium element in the target area. Comprehensively analyzing the remote sensing image, and delineating a possible mineralization alteration area; establishing a comprehensive database, and delineating a target region with the highest prospecting potential; sampling is conducted in the delineated target area, and the ore body position, scale and grade of the alkaline miscellaneous rock type niobium ore are determined. By comprehensively applying various technical means, the prospecting accuracy and efficiency are improved.

The invention relates to the technical field of geological rock type identification, and discloses a deep carbonate rock lithology identification method based on gamma-ray spectrum logging, and the method comprises the steps: S1, collecting a large number of rock cores, slices and the like as verification data; s2, performing statistics on slice identification results of 4, 6, 7 and 8 well carbonate rock coring layer sections of the ancient city in the research area, and dividing the carbonate rock in the research area into five types, namely grit limestone, mud crystal, bright crystal grit limestone, mud crystal limestone, cloud limestone and dolomite; and S3, calibrating on a single well histogram, and counting gamma-ray energy spectrum (U, K, TH, PE) values corresponding to the slice samples. According to the method provided by the invention, the lithology of the carbonate rocks in the fourth, sixth, seventh and eighth wells of the ancient city is identified with relatively high accuracy, fine lithology changes are further identified in the originally explained large set of limestone, the accuracy is far higher than that of logging and debris logging through rock core inspection, and the accuracy of identifying the lithology of the carbonate rocks is greatly improved.

The invention provides a method for predicting vertical evolution of compacted diagenetic fractures of glutenite reservoirs. Main rock types and rock components of the glutenite reservoirs in an actual work area are obtained through rock core observation and slice identification; the method comprises the following steps: preparing artificial rock samples which have the same rock components as those of an actual work area and are in different burying and compacting stages by compacting physical diagenesis simulation experiment equipment; measuring fracture parameters of an artificial rock sample in a simulation experiment and fracture parameters of a rock sample in an actual work area, respectively calculating the surface fracture ratios of the artificial rock sample and the rock sample and the brittleness index of each rock sample in the actual work area, and establishing a prediction model for quantitatively evaluating the vertical evolution of the glutenite reservoir compaction diagenesis fracture. The method is used for predicting the development conditions of the compacted diagenetic fractures of glutenite reservoirs with different depths in the actual work area. According to the method, the established prediction model can well predict the development condition of the compacted diagenesis fracture of the glutenite reservoir, especially the development degree of the compacted diagenesis fracture in a BZ19-6 region can be well predicted, and reference is provided for exploration of oil and gas reservoirs.

The method for automatically generating the tunnel support model comprises the steps that a support template data set and a tunnel center line data set are transmitted to a BIM service platform, data extraction is carried out, and the data are structurally stored in a graph database; the surrounding rock section information is transmitted to a BIM service platform, tunnel position data and surrounding rock types in the construction process are collected, and the surrounding rock section information is updated based on the tunnel position data and the surrounding rock types; based on the surrounding rock section information, matching is conducted in the graph database, tunnel center line data, the positions of all construction sections on the tunnel center line and corresponding support template data are obtained, and a three-dimensional support model is constructed. The method has the advantages that the three-dimensional support model is automatically generated, business hooking with each business system of the BIM business platform can be automatically carried out, the operation threshold is reduced, the workload is greatly reduced, the BIM model change processing link is removed, and the updating efficiency of the three-dimensional support model is improved under the condition that the accuracy of the support model is ensured.

The invention relates to the technical field of geological survey, and mainly relates to a surrounding rock type determination method and device, a control system, equipment and a medium, and the method comprises the steps: obtaining surrounding rock multi-modal data of a target position collected at present, the surrounding rock multi-modal data comprising image data, point cloud data and sound wave data; extracting feature information according to the image data, the point cloud data and the sound wave data; inputting the feature information into a target knowledge graph; the target knowledge graph is a surrounding rock type knowledge graph constructed according to expert knowledge and historical data of surrounding rock types; and determining the surrounding rock type of the target position according to the feature information through the target knowledge graph. According to the technical scheme, the image data, the point cloud data and the sound wave data are applied, the type of the surrounding rock is accurately and efficiently judged based on the knowledge graph, and powerful reference data can be provided for geological survey, underground construction and other scenes.

The invention discloses an anchor rod or anchor cable mounting device and method for inhibiting failure of an anchoring interface, and relates to the technical field of roadway supporting. The device comprises an annular body, a conical protrusion structure, a pulse press-in device, a fluid flushing system and a guide stabilizer, and is suitable for various hole diameters and different surrounding rock types. The construction method using the device comprises the following steps: drilling a hole by a drilling machine to mount an anchor rod or an anchor cable, evaluating the drilling hole, determining a test environment and boundary conditions, performing a drilling hole compression test to simulate confining pressure to obtain a stress deformation response curve, and determining the bonding performance and the shear strength through a pull-out test. The size of the conical protrusion is determined by combining lithology and crustal stress characteristics, the device is installed to a drilling target section, the pulse pressing-in device is started, the conical protrusion structure is pressed into the hole wall of a drilling hole to form a continuous groove, and when a fluid washing system is started to remove dust and chippings, a guiding stabilizer is connected, so that the drilling target section is formed. It is ensured that the device retreats from a drill hole at a constant speed, cleaning operation in the hole is completed, and finally the prefabricated anchor rod is inserted to form a high-adhesion and high-shear-resistance complete anchoring structure.

The invention provides a blasting control construction method for a quarry based on rock mass lumpiness partition and prediction, and belongs to the technical field of blasting control construction. The method comprises the following steps: surveying and setting out, arranging steps and roads, partitioning blasting lumpiness, carrying out blasting design, predicting blasting grading, evaluating safety, drilling holes, cleaning and checking blast holes, loading explosives and detonators and blocking blast hole openings, connecting a detonating network, cleaning a site and warning all around, detonating and checking after blasting. Checking and eliminating unexploded shots; processing and analyzing muck pile images; clearing dangerous stones on the slope; clearing and transporting rock ballast and cleaning the bottom. Reasonable partitioning is carried out according to six indexes including rock types, rock hardness, average crack spacing, explosive unit consumption, blasting funnel volume and blasting lumpiness distribution indexes in a quarry, the qualified rate of specification stones is effectively increased, the resource utilization rate is increased, and a mathematical model Kuz-Ram model for quarry blasting lumpiness distribution forecasting has the advantages of being simple in structure and convenient to use. And predicting and forecasting the grading of the muck pile before blasting, and verifying the muck pile after blasting.

The invention belongs to the technical field of deep hole blasting parameter optimization, and discloses a hole site parameter optimization analysis method based on open-air deep hole blasting. According to the method, the rock type is judged through multi-index cooperation, and a dynamic threshold adjustment mechanism is combined, so that the rock classification accuracy is improved, and accurate matching of hole site parameters and geological conditions is ensured. According to the method, through geological parameter-rock type-mapping relation three-level correlation determination, limitation of an empirical formula is avoided, and the parameter range better fits actual geological features. And meanwhile, a historical blasting data set is introduced for similar case matching, a potential risk parameter set is removed through experience screening, the deviation between theoretical simulation and actual engineering is reduced, and the parameter reliability is improved. According to the method, the multi-objective optimization model is adopted, the crushing quality, the safety control and the economical efficiency are synchronously considered, the parameter set for balancing all the objectives is output through the Pareto optimal algorithm, and high-quality, low-risk and low-cost collaborative optimization is achieved.

The present invention discloses a method for in-situ collaborative development of coal-rock-sandstone type uranium deposits. Uranium resources in coal-rock and sandstone type uranium deposits are mined by combining underground coal gasification with in-situ neutral (CO2+O2) in-situ leaching. This method can achieve clean utilization of coal resources through gasification and collaborative development of sandstone and coal-rock type uranium resources. The method has the advantages of low energy consumption, high resource recovery rate, simple process, and low environmental impact. It conforms to the concept of green mining and is of great significance for addressing my country's demand for strategic key metallic uranium resources and protecting the environment.

The invention relates to a fractured sedimentary reservoir overpressure prediction method and device and computer equipment. The method comprises the following steps: obtaining basic physical property parameters of a to-be-predicted sedimentary reservoir; calculating a rock matrix bulk modulus and a fluid bulk modulus; acquiring a crack angle average value and a preliminary crack aspect ratio of the crack; setting a random crack pore aspect ratio; obtaining the bulk modulus of the rock skeleton; calculating rock longitudinal wave velocity; when the ratio of the difference value of the longitudinal wave speed and the actual logging longitudinal wave speed to the actual longitudinal wave speed is smaller than a threshold value, the real skeleton bulk modulus of the rock is obtained; calculating to obtain a combination item; introducing a correction coefficient to obtain an improved sedimentary reservoir pore pressure prediction model based on a porous elastic mechanics theory, and obtaining a correction coefficient gamma; and predicting pore pressure of other typical wells in the same region. The method is a general method for predicting the overpressure of the sedimentary reservoir, which is really suitable for various rock types and takes the fracture anisotropy into consideration.

A method for recognizing a dominant carbonate rock reservoir in a complex facies zone, comprising: determining a lithologic type and lithologic physical properties of a study section (S100); carving out a development pattern configuration of a special geologic body in the lithologic type (S200); on the basis of the development pattern configuration, using an iterative modeling method to construct an inversion low-frequency model under a phase controlled constraint (S300); using the inversion low-frequency model to perform multi-parameter pre-stack inversion of the study section to obtain an inversion parameter data volume of the study section (S400); and using a multi-parameter intersection method to predict a dominant reservoir distribution in the inversion parameter data volume (S500). Also provided are an apparatus for recognizing a dominant carbonate rock reservoir in a complex facies zone, and an electronic device. By means of the phase controlled constraint, a configuration attribute representing geomorphic facies and lithologic inversion representing lithologic facies are comprehensively considered, and the attribute lateral resolution and the inversion longitudinal resolution are combined, thereby achieving high-precision recognition of a dominant carbonate rock reservoir in a complex facies zone.

The invention discloses a coal-bearing target stratum lithology and macroscopic coal rock type identification method based on element logging, and relates to the technical field of unconventional natural gas exploration and development, and the method comprises the following steps: s1, constructing a coal rock boundary, and dividing a coal rock and a non-coal rock; s2, calculating the content of each component in the coal rock and the non-coal rock; and s3, constructing a non-coal rock lithology identification method and a macroscopic coal rock type identification method in the coal rock. According to the method, division of the coal rock and the non-coal rock can be realized only based on element logging data and a small amount of experimental data, calculation of the content of each component in the rock of the coal-containing target layer is realized, and efficient and accurate identification of the lithology of the non-coal rock and the macroscopic coal rock type can be completed by further innovatively combining with the sulfur element; important technical reference can be provided for geological evaluation and target layer selection of a coal-bearing target layer.

The invention belongs to the technical field of information, and discloses a cloud-English rock type ore body construction method and system based on drilling data, and the method comprises the steps: carrying out the boundary recognition processing according to the gradient change characteristics in an alteration intensity space distribution model, and if the alteration intensity gradient change rate of adjacent space points exceeds a preset boundary threshold value, carrying out the boundary recognition processing; if yes, determining that the position is an ore body boundary point, forming an ore body boundary surface by connecting all boundary points, and judging geometric morphology characteristics of the ore body; a three-dimensional reconstruction algorithm is adopted to carry out internal structure analysis on a space area inside the boundary surface of the ore body, mineral combination difference degrees of different positions inside are calculated through a heterogeneity analysis method, internal structure layers are divided according to difference degree distribution characteristics, and occurrence characteristics and spatial distribution rules inside the ore body are determined. According to the method, full-process automation from data preprocessing to three-dimensional space modeling is achieved, the depicting precision of the ore body space distribution characteristics is remarkably improved, and efficient and accurate technical support is provided for geological exploration and resource evaluation.

A while-drilling multi-source logging data fusion overlying strata type rock burst risk assessment method comprises the steps that drilling is conducted in a roadway at the interval of 5-50 m, and drilling parameters such as torque, thrust, drilling speed and rotating speed and natural gamma, resistivity and sound wave velocity curves are obtained while drilling; the impact danger levels near different drilling positions are judged in combination with monitoring data such as microseism, stress and support resistance, and the corresponding relation between multi-source logging characteristic parameters and the impact danger levels is established through continuously accumulated drilling multi-source logging information and data of the impact danger levels near the corresponding positions. According to the method, the rock burst risk level near the drilling position in the next construction step is predicted, so that while-drilling real-time identification of the overlying strata type rock burst risk is realized, the hysteresis quality and low efficiency of risk assessment after traditional coring testing are avoided, and the disaster prevention and control timeliness is remarkably improved.

The invention belongs to the technical field of hard rock efficient crushing, and provides a vehicle-mounted high-energy laser rock cracking control system and method. The vehicle-mounted high-energy laser rock cracking control system comprises the steps that surrounding environment information of an electric flat car in the moving process is obtained through a second image obtaining and analyzing unit; the electric flat carriage control unit generates a first control instruction according to the stored electric flat carriage motion path and the surrounding environment information; the electric flat carriage controls the electric flat carriage to move to a rock breaking designated position; the type of the rock to be broken is obtained through a first image obtaining and analyzing unit, and real-time condition information of the laser cracking rock is obtained after a laser emitting unit is started; the laser control unit obtains laser emission parameters corresponding to the type of the current to-be-broken rock, adjusts the laser emission parameters after receiving the real-time condition information of the laser cracking rock obtained by the first image obtaining and analyzing unit, and generates a second control instruction according to the laser emission parameters; and the laser emitting unit is controlled to start emitting laser to break rocks.

The invention provides an intelligent geological condition sensing system of a cantilever tunneling machine based on dual-band sound wave analysis, which can solve the problem that the geological condition encountered by the cantilever tunneling machine during construction is unclear, and realizes safe, efficient, intelligent and refined construction of the cantilever tunneling machine. The system is composed of a dual-band high-sensitivity sound pickup, a data wireless transmission antenna and an integrated industrial personal computer, and can collect sound wave data of a cutting head, a tunnel face and surrounding rock in the construction process of the cantilever tunneling machine in real time, and the sound wave data of the cutting head, the tunnel face and the surrounding rock can be obtained through processing methods such as wavelet denoising and Fourier transform on collected audio signals. The system can effectively remove noise signals, analyzes and identifies surrounding rock types in real time in combination with a machine learning algorithm, and can provide a scientific basis for selection of construction parameters of the cantilever tunneling machine, so that parameter setting in the construction process is optimized, the construction safety is improved, reliable support is provided for intelligent construction of tunnel engineering, and the construction efficiency is improved. And special requirements of construction of the cantilever heading machine are met.

A computer-implemented method for augmented inversion and uncertainty quantification for characterizing geophysical bodies is disclosed. The method includes machine-learning-augmented inversion that also facilitates the characterization of uncertainties in geophysical bodies. The method may further estimate wavelets without a well-log calibration, thereby enabling a pre-discovery exploration phase when well log data is unavailable. The machine learning component incorporates a priori knowledge about the subsurface and physics, such as distributions of expected rock types and rock properties, geological structures, and wavelets, through learning from examples. The methodology also allows for conditioning the characterization with the information extracted a priori about the geobodies, such as probabilities of rock types, using other analysis tools. Thus, the conditioning strategy may make the inversion more robust even when a priori distributions are not well balanced. Using the method, a scenario testing workflow may evaluate different candidate subsurface models, facilitating the management of uncertainty in decision-making processes.

The invention discloses a device and method for inverting lunar rock types through annihilation radiation, and belongs to the technical field of lunar geologic structure detection.The method comprises the steps that a proton accelerator is used for obtaining high-current proton bombardment typical lunar rock component samples, meanwhile, a detector is used for measuring induced gamma-ray energy spectrum information generated by the samples, proton flow bombardment is conducted on the samples to be detected, and the samples to be detected are obtained; the method comprises the following steps: acquiring the counting rate of annihilation radiation of different samples to be detected in a 511keV energy window and the counting rate of the annihilation radiation in a 969-1133 keV characteristic peak region, calculating the ratio of the two counting rates, and accurately distinguishing different types of lunar rocks according to different ratios; according to the invention, through successful excitation of typical rock annihilation radiation, accurate distinguishing of lunar rock types is realized by adopting a direct ground calibration method.

The invention discloses a hot dry rock type geothermal resource prediction method and device, a medium and a program product, and the method comprises the steps: firstly carrying out the gravity inversion through the gravity measurement data of a to-be-researched region, and constructing a three-dimensional density model of a hot dry rock body; constructing a hot dry rock volume model according to the geothermal geological data; gridding the hot dry rock volume model to obtain a hot dry rock space grid model; performing geological attribute assignment on each cell in the hot dry rock space grid model according to the geological attribute of the to-be-studied area to obtain a hot dry rock attribute model; performing temperature numerical simulation on each thermal reservoir in the hot dry rock space grid model by using temperature data of the to-be-researched area to obtain a hot dry rock temperature model; and on the basis of the hot dry rock space grid model, the attribute model and the temperature model, the hot dry rock geothermal resource quantity is predicted, and a hot dry rock type geothermal resource quantity prediction result is obtained. According to the embodiment of the invention, the prediction accuracy of the hot dry rock type geothermal resources can be effectively improved.

The present application proposes a method and system for identifying anomalies in mine blasting monitoring images, wherein the method includes: obtaining the rock moisture distribution topology and rock temperature distribution topology of the mine, combining the rock type distribution topology to perform hardness zoning to obtain the rock hardness distribution topology; using the rock type distribution topology, rock fracture distribution topology, and rock hardness distribution topology as constraints, collecting blasting samples from the blasting location list and blasting series list to obtain a blasting sample set, performing high-frequency blast pile morphology mining, and obtaining a blast pile baseline morphology; when the blast pile monitoring morphology is inconsistent with the blast pile baseline morphology, the blast pile monitoring morphology is marked as uncontrollable and sent to the user end. The present application solves the technical problem in the prior art that it is difficult to accurately identify anomalies in mine blasting monitoring images, and achieves the technical effect of accurately identifying anomalies in mine blasting monitoring images and issuing timely warnings.

The embodiment of the present application provides a rock type identification method and device for ultra-deep sea downhole oil and gas exploration, the method comprising: respectively obtaining deuranium gamma logging data and density logging data of a target layer segment located in an ultra-deep sea downhole area; determining the quadrant area where the target layer segment is located in a target plane intersection diagram according to the numerical values ​​corresponding to the deuranium gamma logging data and the density logging data, respectively, the target plane intersection diagram is a plane intersection diagram between deuranium gamma and density, and is provided with a plurality of quadrant areas pre-divided according to a first division threshold corresponding to the deuranium gamma logging data and a second division threshold corresponding to the density logging data; based on a preset identification rule, determining the corresponding rock type according to the quadrant area where the target layer segment is located. The present application can effectively identify the rock type in the ultra-deep sea downhole oil and gas exploration process, can effectively improve the efficiency and reliability of the identification process, and effectively improve the accuracy of the rock identification results.

The invention discloses a comprehensive evaluation method for a deep coal bed gas reservoir, and the method comprises the following specific steps: S100, classifying gas wells according to the effects of produced wells in a research area, and dividing the gas wells into three types of gas wells I, II and III; s200, in combination with gas well classification standards, carrying out classification evaluation on three types of gas wells I, II and III, including coal rock type, coal rank, coal body structure, coal seam thickness, coal seam physical property, coal seam gas-bearing property, coal seam roof and floor research and the like; and S300, establishing a coal rock reservoir comprehensive evaluation classification standard table according to classification evaluation, evaluating the reservoir quality of the undeveloped target area of the research area, and guiding coal bed gas development. By establishing the comprehensive evaluation method for the deep coal-bed gas reservoir, the method has good guiding significance for efficient development of the deep coal-bed gas, the actual reservoir characteristics of the deep coal-bed gas can be reflected, the requirement for the quality of the geological comprehensive evaluation reservoir is met, a favorable area is preferably selected for comprehensive evaluation of the deep coal-bed gas reservoir, and efficient development is achieved.