96 results about "Subsurface geology" patented technology

The invention provides a pre-control and monitoring method for a whole process of actual grouting engineering based on digital geological model, comprising: extracting discontinuous fracture surfaces in a geologic body structure, to build a underground geologic body structure model; build a multi-source geologic body attribute model, optimizing and solving grouting simulations of a disaster high-risk region by using multiphase flow calculation method, and controlling grouting equipment by using optimized grouting parameters to carry out an actual grouting engineering; obtaining a multi-factor diffusion range of variable coefficients by adjusting physical values of the parameters in the grouting simulation and attribute data structure model by using a control variable method, learning and capturing complex mapping relationship between different parameters by using a neural network, optimizing the grouting parameters in the actual engineering in real-time, so as to realize the pre-controlling, monitoring and optimization of the whole process of the actual grouting engineering.

A system and method that may include receiving real-time downhole data from one or more sensors of a drillstring disposed in a borehole in a subsurface geologic region during a directional drilling operation. The system and method also include selecting a drillstring drilling mode from a plurality of drillstring drilling modes. The system and method may additionally include predicting, in real-time, characteristics of a hole bottom of the borehole using the drilling mode model and at least a portion of the real-time downhole data. The system and method may further include controlling the directional drilling operation using one or more of the characteristics.

The invention discloses ground penetrating radar equipment based on an all-wheel-drive unmanned aerial vehicle and an underground geological three-dimensional map construction method, and relates to the technical field of three-dimensional map construction. The invention aims to solve the problems of terrain information perception distortion, difficulty in constructing a three-dimensional geologic model which is fused with terrain information and has space authenticity and the like caused by vehicle bumping and inclination in the prior art of integrating a ground penetrating radar into an intelligent unmanned vehicle platform for underground detection. According to the integrated structure design of the all-wheel-drive unmanned aerial vehicle integrated ground penetrating radar, the attitude of the whole unmanned aerial vehicle is kept stable when the unmanned aerial vehicle carries the radar for flight operation, data loss and noise introduction caused by attitude jitter of the unmanned aerial vehicle in the radar acquisition process are reduced, and a data foundation is laid for subsequent accurate three-dimensional geological map construction. According to the multi-sensor fusion method, the absolute precision of RTK, the high resolution of laser ranging and the dynamic response characteristic of an accelerometer are fully utilized, and the centimeter-level absolute position of the unmanned aerial vehicle, the height of the unmanned aerial vehicle to the ground and the absolute altitude of the ground surface below a scanning point are obtained. According to the invention, decoupling control of six degrees of freedom corresponding to the full-drive unmanned aerial vehicle is realized, so that the unmanned aerial vehicle can fly close to the rugged topography, and automatic and full-coverage scanning path flight is carried out with a constant ground clearance and a stable attitude.

The invention discloses a gravity anomalous body inversion method based on a PMU-Net deep learning network, and belongs to the field of gravity inversion, and the method comprises the steps: increasing the number of observation equation sets through the joint inversion of two different types of gravity anomalous data, and comprehensively presenting an underground geologic structure. Data are processed by means of two independent channels, one channel uses a Mama module to capture dependency between observation points, and the other channel uses a spatial pre-training model to capture position association between the observation points and underground density. And the processed features are fused and input into the U-shaped neural network constructed by one-dimensional convolution, so that the calculation amount is reduced and the efficiency is improved. The system further comprises a simulation data generation module, and the problem of weak interpretability of deep learning in gravity inversion is solved by embedding priori knowledge. According to the invention, the accuracy and reliability of inversion under complex geological conditions are effectively improved, and an efficient and accurate new method is provided for geophysical exploration.

The invention is suitable for the field of geophysics, and provides a geologic structure edge detection method based on an enhanced gravity tensor eigenvalue, and the method comprises the steps: preparing data, and generating a gravity gradient tensor matrix; performing characteristic decomposition on the gravity gradient tensor matrix to obtain a gravity tensor characteristic value; performing deep decomposition on the gravity tensor characteristic value to extract amplitude information; constructing an enhanced edge detection filter F based on the amplitude information; according to the above steps, the structure edge detection calculation based on the enhanced gravity tensor characteristic value is realized, and the underground geologic structure edge is obtained. Compared with a common characteristic value detection technology, the geological structure (or target body) edge detection result obtained through the method technology can obtain a clearer and more continuous recognition effect, the positioning accuracy is high, the method can be well suitable for edge description of the geological structure (or target body) with multiple scales and different buried depth superposition, and the practicability is higher.

The invention discloses a digital basin construction method and device in multi-resource exploration and development and a medium, and relates to the technical field of geologic model construction, and the method comprises the steps: carrying out the collection of regional surface images, and obtaining a regional surface image set; constructing an initial three-dimensional earth surface digital model; carrying out fracture identification on the initial three-dimensional earth surface digital model; obtaining a large-scale fracture model; carrying out distribution constraint mining analysis; and carrying out medium and small-scale fracture model construction to obtain medium and small scales, and obtaining a target digital basin. The technical problems that in the prior art, a large basin cannot be integrally constructed, the characterization accuracy of a large-medium-small multi-scale basic geologic model and an energy resource model is poor, and the comprehensiveness of underground geology and energy resource analysis is insufficient are solved, high-precision construction of the digital basin is achieved, and the construction efficiency is improved. And the characterization accuracy of the multi-scale basic geologic model and the energy resource model in the geologic model and the analysis comprehensiveness of underground geology and energy resources are improved.

A method of removing hydrogen sulfide from a subterranean geological formation includes mixing a zinc-imidazolate material, ZIF-8, in an amount of 0.1 to 2.5 percent by weight with an organic liquid containing one or more unsaturated oils to form a drilling fluid suspension with a pH of 10 or more. The method includes injecting the drilling fluid suspension in the subterranean geological formation, circulating the drilling fluid suspension in the subterranean geological formation to form an oil-based mud, and scavenging hydrogen sulfide from the subterranean geological formation.

A method can include performing a simulation to generate synthetic seismic data using a wavelet and a velocity model of a subsurface geologic region, where the velocity model includes representations of subsurface structural features and associated geophysical parameters; generating a velocity gradient conditioner for the velocity model based at least in part on the synthetic seismic data; performing an iterative inversion process using acquired seismic data for the subsurface geologic region, the velocity model, and the velocity gradient conditioner; and outputting a final velocity model of the subsurface geologic region as a result of the iterative inversion process.

A method can include accessing data for a number of reservoir sites, where the data include at least property data for reservoir properties; performing a determination, using the property data for the reservoir sites, as to whether the reservoir properties for the reservoir sites are independent; responsive to the determination, implementing a Sobol' indices technique or a Kucherenko indices technique to generate global sensitivity analysis results that include property indices for the reservoir properties; generating confidence intervals for the property indices; and generating a graphical user interface for rendering the property indices with the confidence intervals for a number of the reservoir properties.

A subsurface pumped hydropower storage system is provided and includes an upper reservoir, and a lower reservoir within a subsurface formation. The system includes a completed well extending into the subsurface geological strata to reach the lower reservoir, the completed well has a wellhead at the surface, a casing, a tubing string extending within the casing, the tubing being adapted to establish fluid communication between the upper reservoir and the lower reservoir. An electric submersible pump (ESP) operable in a turbine configuration and a pumping configuration is coupled to the tubing string, where, when in the turbine configuration, electricity is generated and transmitted to the surface via a power cable connected to the ESP, and, when in the pumping configuration, electricity is consumed to pump the working fluid from the lower reservoir into the upper reservoir.

A method of removing hydrogen sulfide from a subterranean geological formation includes mixing a zinc-imidazolate material, ZIF-8, in an amount of 0.1 to 2.5 percent by weight with an organic liquid containing one or more unsaturated oils to form a drilling fluid suspension with a pH of 10 or more. The method includes injecting the drilling fluid suspension in the subterranean geological formation, circulating the drilling fluid suspension in the subterranean geological formation to form an oil-based mud, and scavenging hydrogen sulfide from the subterranean geological formation.

Detection technology to monitor a flare stack during drilling operations and determine information based on the imaging. Various actions may be taken based on the determined information. For example, subterranean geology may be mapped. This may include mapping formation properties, fractures, faults or reservoir zones. Additionally, drilling operational parameters may be adjusted. This may include adjusting rate of direction, penetration, weight on bit, rotary speed, mud flow rate, mud weight, actuating a valve, or changing the pump speed.

A method for underbalanced drilling includes drilling into a subterranean geological formation to form a wellbore therein, injecting a foaming agent into the wellbore during drilling at a wellbore pressure that is below a pore pressure of the subterranean geological formation, and transporting drill cuttings formed by the drilling away from the drilling surface in the foam. The foaming agent forms a foam in the wellbore at a drilling surface at a bottom of the wellbore. The foaming agent is an aqueous solution including an ammonium alcohol ether sulfate surfactant.

Providing mobile electric power comprising a power generation transport configured to convert hydrocarbon fuel to electricity and an inlet and exhaust transport configured to: couple to at least one side of the power generation transport such that the inlet and exhaust transport is not connected to a top side of the power generation transport, provide ventilation air and combustion air to the power generation transport, collect exhaust air from the power generation transport, and filter the exhaust air.

The invention belongs to the technical field of geophysical exploration, particularly relates to a background noise seismic frequency imaging method and system based on autocorrelation, and aims to solve the problem that an existing background noise exploration method is insufficient in resolution. The method comprises the following steps: acquiring background noise data of a plurality of acquisition points in a target area and segmenting the background noise data to obtain horizontal component signals in different directions; performing self-correlation calculation on each horizontal component signal to obtain a plurality of sections of self-correlation sequences, performing frequency domain conversion, and performing superposition according to directions to obtain a north component characteristic frequency spectrum and an east component characteristic frequency spectrum; and combining the east characteristic frequency spectrum and the north characteristic frequency spectrum, mapping the combined frequency spectrum into the depth of the underground anomalous body, and generating a frequency imaging result. According to the method, after self-correlation processing, the passive source body wave signals are transmitted in a frequency domain and reflected on the ground surface through an underground geological interface to interfere and perform imaging, the exploration cost is low, the applicability is high, and the imaging resolution of low-speed anomalous bodies such as karst is high.

A method of modeling subsurface geology includes receiving interpreted data including fault data indicating at least one fault within the interpreted data, and geological feature data including a plurality of horizon picks indicating a subsurface geological feature. The method includes, based on the fault data, creating a dynamic kernel mask. The method includes generating a geological model using a horizon-fault machine learning (ML) model that is generated to process input geological feature data to predict continuous geological features across subsurface discontinuities based on applying the dynamic kernel mask to isolate continuous zones in the input geological feature data. The method also includes providing the geological model for simulating one or more properties of a geological feature indicated in the geological feature data.

The invention discloses a power transmission tower footing site selection method, system and equipment, and relates to the technical field of power transmission line engineering. The method comprises the following steps: carrying out physical detection on a target area, obtaining geological data through geophysical detection, laying verification drill holes, and constructing a multi-source geological data set; based on the multi-source geological data set, constructing a three-dimensional geologic body model capable of representing underground structure spatial distribution; and according to the three-dimensional geologic body model. According to the method, the high-precision three-dimensional model is constructed by fusing the multi-source geological data, so that the detection precision and reliability of the underground geological structure are remarkably improved; geological information is deeply combined with a multi-objective optimization algorithm, so that scientific site selection of comprehensively optimizing cost, path and construction difficulty while avoiding risks is realized; and finally, by means of reinforcement learning and a risk assessment mechanism, the engineering is endowed with dynamic adjustment and prospective management capabilities, so that the safety, economical efficiency and decision scientificity of the power transmission tower footing engineering are improved.

Systems and processes for stimulating subterranean geologic formations to create an artificial stress barrier. An injector well extends from surface to a subterranean geologic formation. After cementing and perforating, the injector well utilizes single-path injection through a coiled tubing and a pump. The coiled tubing is inserted into the injector well to a first stimulation zone. A first stimulation fluid is pumped through the coiled tubing at rate R1 into the first stimulation zone, spaced apart from a target stimulation zone in the formation. The coiled tubing is then inserted into the injector well to the target stimulation zone, then main stimulation treatment fluid at rate R2 is pumped through the coiled tubing at the target stimulation zone, where R2>R1. A sub-system is included that measures blocking effect on the main stimulation fluid in the target stimulation zone by the first stimulation fluid in the first stimulation zone.

A method for inhibiting the formation of scale in a subterranean geological includes injecting a scale-inhibiting composition into a subterranean geological formation comprising a target zone. The scale inhibiting composition includes water and an amphiphilic polymer selected from the group consisting of S1, S2, and combinations thereof, where the structure of S1 is:the structure of S2 is:where x is in a range from 4 to 20, and n is in a range from 3 to 15, and where the amphiphilic polymer is dissolved in the scale inhibiting composition in an amount such that the concentration of the amphiphilic polymer at the target zone is equal to or greater than 500 ppm.

The invention discloses a three-dimensional geophysical prospecting detection method for a shallow corrosion groove, and belongs to the technical field of geological investigation, and the method comprises the following steps: S1, basic geological data collection and multi-geophysical prospecting method validity verification; s2, screening an optimal geophysical prospecting method combination and setting parameters based on test data; s3, on-site detection network layout and equipment deployment based on optimal parameters; s4, collecting on-site geophysical prospecting data and preliminarily identifying a target body; and S5, multi-source geophysical prospecting data fusion and underground geologic structure three-dimensional modeling are carried out. According to the three-dimensional geophysical prospecting detection method for the shallow corrosion groove, the cross-hole seismic wave CT and the transient electromagnetic method are combined, the karst cave recognition accuracy and the resolution ratio of the shallow corrosion groove can be improved, full-depth detection within the range of 0-50 m can be achieved, the three-dimensional model can visually present underground information, and accurate basis is provided for construction.

A first fracturing pump is selectively engaged or disengaged a from an electric prime mover based on operation of a first lever by a user. The first lever, the electric prime mover, and the first fracturing pump are mounted on a mobile transport. A second fracturing pump is selectively engaged or disengaged a from the electric prime mover based on operation of a second lever by the user. The second lever is also mounted on the mobile transport. The electric prime mover is operable to drive one of the first and second fracturing pumps that is engaged with the electric prime mover while not driving the other of the first and second fracturing pumps that is disengaged from the electric prime mover by operation of a corresponding one of the first and second levers.

The application relates to the technical field of seismic data acquisition and processing, and discloses a three-dimensional variable-speed mapping method, device, equipment, storage medium and computer program, which comprises the following steps: obtaining underground geological data, performing model construction on the underground geological data to obtain a velocity model; obtaining seismic data, adjusting model parameters of the velocity model according to the seismic data to obtain a mixed velocity model; obtaining a migration time structure map, converting the time structure map into a depth domain structure map by using the mixed velocity model; and correcting the depth domain structure map according to the seismic data to obtain a mixed velocity model structure map. The application can improve the three-dimensional velocity modeling precision and the structure mapping precision, and especially can improve the micro-amplitude structure mapping precision.

The present application provides a metal mining area earthquake frequency resonance interference processing method and system based on deep learning, relating to the technical field of signal data processing, the method comprising: arranging an observation array in a metal mining area, collecting earthquake frequency resonance original data containing environmental vibration interference; preprocessing the earthquake frequency resonance original data by standardization and format conversion, extracting time domain sequences containing three-axis acceleration information; inputting the time domain sequences into a pre-trained deep learning model, identifying and preliminarily separating the environmental vibration interference signals; performing time-frequency analysis on the preliminarily separated environmental vibration interference signals, dynamically determining at least three characteristic positioning points in the time-frequency characteristic space, the characteristic positioning points being selected from specific frequency amplitude peak points, time-frequency energy ridge intersection points and phase mutation points. The present application realizes accurate identification and directional rejection of non-steady-state and strongly coupled environmental vibration interference in the mining area, and maximally retains effective resonance signals reflecting underground geological structures.

A system and method may include receiving real-time downhole data from one or more sensors of a drill string disposed in a borehole in a subterranean geological region during a directional drilling operation. The system and method also include selecting a drill string drilling mode from a plurality of drill string drilling modes. The systems and methods may additionally include predicting, in real-time, characteristics of the bottom hole of the borehole using the drilling pattern model and at least a portion of the real-time downhole data. The system and method may also include using one or more characteristics to control directional drilling operations.

The embodiment of the invention relates to the field of electric or magnetic exploration or detection, in particular to a method and system for determining the extension form of a fracture deep part of a granite type uranium mine. According to the method and the system, the relation between the electrical difference and the underground geologic structure can be quantified by determining the relation between the electrical resistivity of the fracture area and the electrical resistivity of the peripheral area of the fracture area; an underground resistivity inversion cross-section diagram is determined according to the frequency-apparent resistivity of each measuring point, and the deep extension form of the fracture can be visually judged; according to the method, the frequency-apparent resistivity at the measuring point is determined only by using the electric field signal, so that the calculation result is more accurate; and in combination with an underground resistivity inversion section diagram of a detection section, the deduction of the deep extension form of the fracture can be more accurate.

The application belongs to the technical field of geophysical exploration, and particularly relates to a background noise seismic frequency imaging method and system based on autocorrelation, aiming to solve the problem of insufficient resolution of the existing background noise exploration method. The method comprises the following steps: obtaining background noise data of multiple acquisition points in a target area and segmenting, to obtain horizontal component signals in different directions; performing autocorrelation calculation on each horizontal component signal, respectively, to obtain multiple autocorrelation sequences, then performing frequency domain conversion, respectively, and stacking according to the direction, to obtain a north component characteristic frequency spectrum and an east component characteristic frequency spectrum; merging the east component characteristic frequency spectrum and the north component characteristic frequency spectrum, to map the underground abnormal body depth, to generate a frequency imaging result. After autocorrelation processing, the passive source body wave signal propagation is used in the frequency domain to reflect on the ground interference for imaging through the underground geological interface, the exploration cost is low, the applicability is strong, and the imaging resolution of karst and other low-velocity abnormal bodies is high.

The present invention discloses a dynamic monitoring and early warning system for safety risks in non-coal mines based on point-surface fusion technology, which relates to the technical field of mine safety monitoring. The system uses the four-dimensional spatiotemporal coordinate data of surface monitoring points to construct a dynamic surface model; adopts a deep learning large model (DSIM) to dynamically invert a probabilistic three-dimensional underground geomechanical model from the surface and quantify the uncertainty; adaptively evolves the DSIM model online by comparing the difference between predictions and actual observations; integrates a causal inference engine to deeply trace the risk driving factors; and finally generates an intelligent early warning with clear causal attribution. The present invention realizes underground state perspective, risk cause tracing and model self-evolution, significantly improving the accuracy, reliability and intelligent decision-making support level of monitoring and early warning.

Method and apparatus for constructing seismic velocity models of the underground geologic formation using full waveform inversion are provided. The method evaluates velocity model accuracy by measuring local traveltime differences between recorded seismic data and synthetic data. The travetime misfit may be calculated with a hybrid L1 / L2 norm that relatively lowers down the influence of large traveltime difference in each iteration and ensures the inversion stability. The method tolerates poor quality initial model and generates high resolution models.

The application discloses a water level prediction method and device for water conservancy projects. The method comprises the following steps: reading water level time series data of a reservoir at a preset interval; obtaining external influence data of the water level of the reservoir and performing feature extraction to obtain external influence features and store the external influence features to a block chain; performing correlation analysis on the external influence features and the water level of the reservoir, and assigning weights to the external influence features according to the analysis result; inputting the water level time series data and the external influence features carrying the weights into a pre-trained water level prediction model to obtain an initial predicted water level; calculating first internal influence data of the water level of the reservoir through the inflow of the reservoir according to water quality information and geological information of inflow rivers of the reservoir; measuring underground water level data and underground geological data of the reservoir to determine second internal influence data of the water level of the reservoir; and correcting the initial predicted water level through a water level correction model based on the first internal influence data and the second internal influence data to obtain a final predicted water level.