Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,i...Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,in certain regions,the installation of buried pipes for heat exchangers may be complicated,and these pipes may not always serve as efficient low-temperature heat sources for the heat pumps of the system.To address this issue,the current study explored the use of solar-energy-collecting equipment to supplement buried pipes.In this design,both solar energy and geothermal energy provide low-temperature heat to the heat pump.First,a simulation model of a solar‒ground source heat pump coupling system was established using TRNSYS.The accuracy of this model was validated through experiments and simulations on various system configurations,including varying numbers of buried pipes,different areas of solar collectors,and varying volumes of water tanks.The simulations examined the coupling characteristics of these components and their influence on system performance.The results revealed that the operating parameters of the system remained consistent across the following configurations:three buried pipes,burial depth of 20 m,collector area of 6 m^(2),and water tank volume of 0.5 m^(3);four buried pipes,burial depth of 20 m,collector area of 3 m^(2),and water tank volume of 0.5 m^(3);and five buried pipes with a burial depth of 20 m.Furthermore,the heat collection capacity of the solar collectors spanning an area of 3 m^(2)was found to be equivalent to that of one buried pipe.Moreover,the findings revealed that the solar‒ground source heat pump coupling system demonstrated a lower annual cumulative energy consumption compared to the ground source heat pump system,presenting a reduction of 5.31%compared to the energy consumption of the latter.展开更多
In this paper,we investigate the method of compensating LTS SQUID Gradiometer Systems data.By matching the attitude changes of the pod in fl ight to the anomalies of the magnetic measurement data,we find that the yaw ...In this paper,we investigate the method of compensating LTS SQUID Gradiometer Systems data.By matching the attitude changes of the pod in fl ight to the anomalies of the magnetic measurement data,we find that the yaw attitude changes most dramatically and corresponds best to the magnetic data anomaly interval.Based on this finding,we solved the compensation model using least squares fitting and Huber's parametric fitting.By comparison,we found that the Huber parametric fit not only eliminates the interference introduced by attitude changes but also retains richer anomaly source information and therefore obtains a higher signal-to-noise ratio.The experimental results show that the quality of the magnetometry data obtained by using the compensation method proposed in this paper has been significantly improved,and the mean value of its improvement ratio can reach 118.93.展开更多
The geological disasters such as collapse,mud bursting and water gushing often occur during tunnel construction.Thus,it is of great significance to detect the hidden geological disasters ahead of the tunnel face.The a...The geological disasters such as collapse,mud bursting and water gushing often occur during tunnel construction.Thus,it is of great significance to detect the hidden geological disasters ahead of the tunnel face.The audio magnetotelluric(AMT)was applied for the advanced detectionstudy during the boring process of the Tianheshan tunnel in the Taihang Mountains.Three AMT profiles were deployed above the tunnel,and the data obtained in the field were analysed in terms of electrical principal axes.From shallow to deep,the direction of the geoelectric strike angle changes,generally between 30°and 60°NE,which is consistent with similar to the direction of the Taihangshan Uplift,and the data show some 3D characteristics.Two-dimensional(2D)and three-dimensional(3D)inversion methods were adopted to jointly study the subsurface structural information,and the resistivity model was geophysically and geologically interpreted.Two sets of low resistance anomalies were found,and it was hypothesised that the near-erect low-resistivity anomalies in the east might be a fragmentation zone,while the low resistance anomalies in the west,which are inclined to the westward,might be a tectonic structure or fragmentation zone related to the regional major fault,and the results of the tunnelling confirmed the reliability of the inversion interpretation.The 3D inversion can fully reflect the development scale and morphological changes of the fracture zone,and the inversion model is more reliable.Finally,it is concluded that the audio magnetotelluric method,which adopts advanced acquisition,processing and inversion interpretation techniques,is an effective means of over-detection of tunnels.展开更多
Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detectio...Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detection accuracy.Using multiple methods to carry out a comprehensive evaluation can eff ectively improve the accuracy of advanced geological prediction results.In this study,geological information is combined with the detection results of geophysical methods,including transient electromagnetic,induced polarization,and tunnel seismic prediction,to establish a comprehensive analysis method of adverse geology.First,the possible main adverse geological problems are determined according to the geological information.Subsequently,various physical parameters of the rock mass in front of the tunnel face can then be derived on the basis of multisource geophysical data.Finally,based on the analysis results of geological information,the multisource data fusion algorithm is used to determine the type,location,and scale of adverse geology.The advanced geological prediction results that can provide eff ective guidance for tunnel construction can then be obtained.展开更多
In the 3D inversion modeling of gravity and magnetic potential field data,the model weighting function is often applied to overcome the skin eff ect of inversion results.However,divergence occurs at the the deep area,...In the 3D inversion modeling of gravity and magnetic potential field data,the model weighting function is often applied to overcome the skin eff ect of inversion results.However,divergence occurs at the the deep area,and artificial weak negative anomalies form around the positive anomalies in the horizontal direction,resulting in a reduction in the overall resolution.To fully utilize the model weighting function,this study constructs a combined model weighting function.First,a new depth weighting function is constructed by adding a regulator into the conventional depth weighting function to overcome the skin eff ect and inhibit the divergence at the deep area of the inversion results.A horizontal weighting function is then constructed by extracting information from the observation data;this function can suppress the formation of artificial weak anomalies and improve the horizontal resolution of the inversion results.Finally,these two functions are coupled to obtain the combined model weighting function,which can replace the conventional depth weighting function in 3D inversion.It improves the vertical and horizontal resolution of the inversion results without increasing the algorithm complexity and calculation amount,is easy to operate,and adapts to any 3D inversion method.Two model experiments are designed to verify the effectiveness,practicability,and anti-noise of the combined model weighting function.Then the function is applied to the 3D inversion of the measured aeromagnetic data in the Jinchuan area in China.The obtained inversion results are in good agreement with the known geological data.展开更多
Since April 2002,the Gravity Recovery and Climate Experiment Satellite(GRACE)has provided monthly total water storage anomalies(TWSAs)on a global scale.However,these TWSAs are discontinuous because some GRACE observat...Since April 2002,the Gravity Recovery and Climate Experiment Satellite(GRACE)has provided monthly total water storage anomalies(TWSAs)on a global scale.However,these TWSAs are discontinuous because some GRACE observation data are missing.This study presents a combined machine learning-based modeling algorithm without hydrological model data.The TWSA time-series data for 11 large regions worldwide were divided into training and test sets.Autoregressive integrated moving average(ARIMA),long short-term memory(LSTM),and an ARIMA-LSTM combined model were used.The model predictions were compared with GRACE observations,and the model accuracy was evaluated using fi ve metrics:the Nash-Sutcliff e effi ciency coeffi cient(NSE),Pearson correlation coeffi cient(CC),root mean square error(RMSE),normalized RMSE(NRMSE),and mean absolute percentage error.The results show that at the basin scale,the mean CC,NSE,and NRMSE for the ARIMA-LSTM model were 0.93,0.83,and 0.12,respectively.At the grid scale,this study compared the spatial distribution and cumulative distribution function curves of the metrics in the Amazon and Volga River basins.The ARIMA-LSTM model had mean CC and NSE values of 0.89 and 0.61 and 0.92 and 0.61 in the Amazon and Volga River basins,respectively,which are superior to those of the ARIMA model(0.86 and 0.48 and 0.88 and 0.46,respectively)and the LSTM model(0.80 and 0.41 and 0.89 and 0.31,respectively).In the ARIMA-LSTM model,the proportions of grid cells with NSE>0.50 for the two basins were 63.3%and 80.8%,while they were 54.3%and 51.3%in the ARIMA model and 53.7%and 43.2%in the LSTM model.The ARIMA-LSTM model significantly improved the NSE values of the predictions while guaranteeing high CC values in the GRACE data reconstruction at both scales,which can aid in fi lling in discontinuous data in temporal gravity fi eld models..展开更多
Enhancing the mining speed of a working face has become the primary approach to achieve high production and efficiency in coal mines,thereby further improving the production capacity.However,the problem of rock bursts...Enhancing the mining speed of a working face has become the primary approach to achieve high production and efficiency in coal mines,thereby further improving the production capacity.However,the problem of rock bursts resulting from this approach has become increasingly serious.Therefore,to implement coal mine safety and efficient extraction,the impact of deformation pressure caused by different mining speeds should be considered,and a reasonable mining speed of the working face should be determined.The influence of mining speed on overlying rock breaking in the stope is analyzed by establishing a key layer block rotation and subsidence model.Results show that with the increasing mining speed,the compression amount of gangue in the goaf decreases,and the rotation and subsidence amount of rock block B above goaf decreases,forcing the rotation and subsidence amount of rock block A above roadway to increase.Consequently,the contact mode between rock block A and rock block B changes from line contact to point contact,and the horizontal thrust and shear force between blocks increase.The increase in rotation and subsidence of rock block A intensifies the compression degree of coal and rock mass below the key layer,thereby increasing the stress concentration degree of coal and rock mass as well as the total energy accumulation.In addition,due to the insufficient compression of gangue in the goaf,the bending and subsidence space of the far-field key layer are limited,the length of the suspended roof increases,and the influence range of mining stress and the energy accumulation range expand.Numerical test results and underground microseismic monitoring results verify the correlation between mining speed and stope energy,and high-energy events generally appear 1-2 d after the change in mining speed.On this basis,the statistical principle confirms that the maximum mining speed of the working face at 6 m/d is reasonable.展开更多
Absorption compensation is a process involving the exponential amplification of reflection amplitudes.This process amplifies the seismic signal and noise,thereby substantially reducing the signal-tonoise ratio of seis...Absorption compensation is a process involving the exponential amplification of reflection amplitudes.This process amplifies the seismic signal and noise,thereby substantially reducing the signal-tonoise ratio of seismic data.Therefore,this paper proposes a multichannel inversion absorption compensation method based on structure tensor regularization.First,the structure tensor is utilized to extract the spatial inclination of seismic signals,and the spatial prediction filter is designed along the inclination direction.The spatial prediction filter is then introduced into the regularization condition of multichannel inversion absorption compensation,and the absorption compensation is realized under the framework of multichannel inversion theory.The spatial predictability of seismic signals is also introduced into the objective function of absorption compensation inversion.Thus,the inversion system can effectively suppress the noise amplification effect during absorption compensation and improve the recovery accuracy of high-frequency signals.Synthetic and field data tests are conducted to demonstrate the accuracy and effectiveness of the proposed method.展开更多
Earthquakes not only release the long-term accumulated stress on the seismogenic fault but may also increase the stress on some surrounding faults or other segments of the seismogenic fault,thereby raising the seismic...Earthquakes not only release the long-term accumulated stress on the seismogenic fault but may also increase the stress on some surrounding faults or other segments of the seismogenic fault,thereby raising the seismic risk on these faults.This study investigates the impact of the April 2,2024,Mw 7.4 earthquake in Hualien,Taiwan,China,on the surrounding faults and aftershocks.We analyze stress-triggering effects by calculating Coulomb stress changes(ΔCFS)using rupture models and focal mechanism data.Historical focal mechanism nodal planes serve as receiver fault parameters forΔCFS calculations.Our findings indicate signifi cant Coulomb stress loading on the Longitudinal Valley fault and Central Range structure due to the mainshock,promoting their seismic activity.Loading effects vary by fault type,with thrust and strike-slip faults experiencing more stress loading than normal and odd faults.Conversely,the rupture’s coseismic slip concentration area shows predominant stress unloading,inhibiting seismic activity in the region.Aftershocks mainly experience increasedΔCFS,suggesting that the stress-triggering induced by the mainshock considerably influences the earthquake sequence evolution.These insights are crucial for understanding aftershock patterns and enhancing seismic hazard assessments.展开更多
The Tarim Basin has revealed numerous tight sandstone oil and gas reservoirs.The tidal fl at zone in the Shunbei area is currently in the detailed exploration stage,requiring a comprehensive description of the sand bo...The Tarim Basin has revealed numerous tight sandstone oil and gas reservoirs.The tidal fl at zone in the Shunbei area is currently in the detailed exploration stage,requiring a comprehensive description of the sand body distribution characteristics for rational exploration well deployment.However,using a single method for sand body prediction has yielded poor results.Seismic facies analysis can eff ectively predict the macro-development characteristics of sedimentary sand bodies but lacks the resolution to capture fine details.In contrast,single-well sedimentary facies analysis can describe detailed sand body development but struggles to reveal broader trends.Therefore,this study proposes a method that combines seismic facies analysis with single-well sedimentary microfacies analysis,using the lower section of the Kepingtage Formation in the Shunbei area as a case study.First,seismic facies were obtained through unsupervised vector quantization to control the macro-distribution characteristics of sand bodies,while principal component analysis(PCA)was applied to improve the depiction of fine sand body details from seismic attributes.Based on 3D seismic data,well-logging data,and geological interpretation results,a detailed structural interpretation was performed to establish a high-precision stratigraphic framework,thereby enhancing the accuracy of sand body prediction.Seismic facies analysis was then conducted to obtain the macro-distribution characteristics of the sand bodies.Subsequently,core data and logging curves from individual wells were used to clarify the vertical development characteristics of tidal channels and sandbars.Next,PCA was employed to select the seismic attributes most sensitive to sand bodies in diff erent sedimentary facies.Results indicate that RMS amplitude in the subtidal zone and instantaneous phase in the intertidal zone are the most sensitive to sand bodies.A comparative analysis of individual seismic attributes for sand body characterization revealed that facies-based delineation improved the accuracy of sand body identification,eff ectively capturing their contours and shapes.This method,which integrates seismic facies,single-well sedimentary microfacies,and machine learning techniques,enhances the precision of sand body characterization and off ers a novel approach to sand body prediction.展开更多
Disaster mitigation necessitates scientifi c and accurate aftershock forecasting during the critical 2 h after an earthquake. However, this action faces immense challenges due to the lack of early postearthquake data ...Disaster mitigation necessitates scientifi c and accurate aftershock forecasting during the critical 2 h after an earthquake. However, this action faces immense challenges due to the lack of early postearthquake data and the unreliability of forecasts. To obtain foundational data for sequence parameters of the land-sea adjacent zone and establish a reliable and operational aftershock forecasting framework, we combined the initial sequence parameters extracted from envelope functions and incorporated small-earthquake information into our model to construct a Bayesian algorithm for the early postearthquake stage. We performed parameter fitting and early postearthquake aftershock occurrence rate forecasting and effectiveness evaluation for 36 earthquake sequences with M ≥ 4.0 in the Bohai Rim region since 2010. According to the results, during the early stage after the mainshock, earthquake sequence parameters exhibited relatively drastic fl uctuations with signifi cant errors. The integration of prior information can mitigate the intensity of these changes and reduce errors. The initial and stable sequence parameters generally display advantageous distribution characteristics, with each parameter’s distribution being relatively concentrated and showing good symmetry and remarkable consistency. The sequence parameter p-values were relatively small, which indicates the comparatively slow attenuation of signifi cant earthquake events in the Bohai Rim region. A certain positive correlation was observed between earthquake sequence parameters b and p. However, sequence parameters are unrelated to the mainshock magnitude, which implies that their statistical characteristics and trends are universal. The Bayesian algorithm revealed a good forecasting capability for aftershocks in the early postearthquake period (2 h) in the Bohai Rim region, with an overall forecasting effi cacy rate of 76.39%. The proportion of “too low” failures exceeded that of “too high” failures, and the number of forecasting failures for the next three days was greater than that for the next day.展开更多
The investigation of the tectonic deformation characteristics at the front margin of the Xu-Su arc tectonic belt provides important reference points for identifying and analyzing its genetic mechanism,tectonic evoluti...The investigation of the tectonic deformation characteristics at the front margin of the Xu-Su arc tectonic belt provides important reference points for identifying and analyzing its genetic mechanism,tectonic evolution process,and the latest evidence of tectonic deformation.In this study,two reflection seismic exploration profiles across the front margin of the Xu-Su arc tectonic belt are utilized to reveal that the Qinglongshan fault is the thrust fault of its front margin boundary.The kinematic properties and tectonic deformation characteristics of the internal faults in the front margin basin are also obtained.Using the Qinglongshan fault as the boundary,the middle and posterior margins of the Xu-Su arc tectonic belt are composed of numerous thrust faults,which suggest strong ancient tectonic movement.However,a large number of normal faults are developed within the front margin basin,with some faults exhibiting strike-slip and growth properties,which indicate strong neotectonic movement.Results reveal that the Xu-Su arc tectonic belt is a large-scale thrust-nappe structure that has undergone structural inversion.The Xu-Su arc tectonic belt experienced strong tectonic activity during the Middle Pleistocene,and the most recent tectonic deformation has extended into the front margin basin interior.展开更多
The stratum lithology and geological structure of the highway tunnel in the mountainous areas of western China are complex,and the engineering geological conditions are complicated.When the highway tunnel passes throu...The stratum lithology and geological structure of the highway tunnel in the mountainous areas of western China are complex,and the engineering geological conditions are complicated.When the highway tunnel passes through different lithological strata,its structural design and construction technology are completely diff erent.Therefore,in order to support the tunnel design and construction,the tunnel survey Among them,the identification of the contact boundary between magmatic rock and metamorphic rock and the grade of surrounding rock is very important.Through magnetotelluric survey of the Mupi tunnel of Jiuzhaigou-Mianyang highway on G8513 line,2D forward numerical simulation,1D,2D,3D inversion,and engineering geological analysis,it is revealed that the electrical characteristics of each layer,focusing on the identification of the contact boundary between magmatic rock and metamorphic rock.This study provides the electrical characteristics of the magmatic rock and metamorphic rock contact boundary of the Mupi Tunnel.It is speculated that the boundary is revealed by the tunnel construction excavation,which verifies the correctness of the geophysical inversion model and provides a more detailed design basis for the tunnel design.I believe that taking the Mupi Tunnel survey as an example,through this research,it can provide detailed geophysical evidence for highway tunnels to distinguish between magmatic rock and metamorphic rock.展开更多
The increasing risk of ground pressure disasters resulting from deep well mining highlights the urgent need for advanced monitoring and early warning systems.Ground pressure monitoring,supported by microseismic techno...The increasing risk of ground pressure disasters resulting from deep well mining highlights the urgent need for advanced monitoring and early warning systems.Ground pressure monitoring,supported by microseismic technology,plays a pivotal role in ensuring mine safety by enabling real-time identifi cation and accurate classification of vibration signals such as microseismic signals,blasting signals,and noise.These classifications are critical for improving the efficacy of ground pressure monitoring systems,conducting stability analyses of deep rock masses,and implementing timely and precise roadway support measures.Such eff orts are essential for mitigating ground pressure disasters and ensuring safe mining operations.This study proposes an artificial intelligence-based automatic classification network model for mine vibration signals.Based on conventional convolutional neural networks,the proposed model further incorporates long short-term memory(LSTM)networks and attention mechanisms.The LSTM component eff ectively captures temporal correlations in time-series mining vibration data,while the attention mechanism enhances the models’ability to focus on critical features within the data.To validate the eff ectiveness of our proposed model,a dataset comprising 480,526 waveform records collected in 2022 by the microseismic monitoring system at Guangxi Shanhu Tungsten Mine was used for training,validation,and testing purposes.Results demonstrate that the proposed artifi cial intelligence-based classifi cation method achieves a higher recognition accuracy of 92.21%,significantly outperforming traditional manual classification methods.The proposed model represents a signifi cant advancement in ground pressure monitoring and disaster mitigation.展开更多
Geomagnetic data hold significant value in fields such as earthquake monitoring and deep earth exploration.However,the increasing severity of anthropogenic noise contamination in existing geomagnetic observatory data ...Geomagnetic data hold significant value in fields such as earthquake monitoring and deep earth exploration.However,the increasing severity of anthropogenic noise contamination in existing geomagnetic observatory data poses substantial challenges to high-precision computational analysis of geomagnetic data.To overcome this problem,we propose a denoising method for geomagnetic data based on the Residual Shrinkage Network(RSN).We construct a sample library of simulated and measured geomagnetic data develop and train the RSN denoising network.Through its unique soft thresholding module,RSN adaptively learns and removes noise from the data,effectively improving data quality.In experiments with noise-added measured data,RSN enhances the quality of the noisy data by approximately 12 dB on average.The proposed method is further validated through denoising analysis on measured data by comparing results of time-domain sequences,multiple square coherence and geomagnetic transfer functions.展开更多
Machine learning(ML)efficiently and accurately processes dense seismic array data,improving earthquake catalog creation,which is crucial for understanding earthquake sequences and fault systems;analyzing its reliabili...Machine learning(ML)efficiently and accurately processes dense seismic array data,improving earthquake catalog creation,which is crucial for understanding earthquake sequences and fault systems;analyzing its reliability is also essential.An M5.8 earthquake struck Alxa Left Banner,Inner Mongolia,China on April 15,2015,a region with limited CENC monitoring capabilities,making analysis challenging.However,abundant data from ChinArray provided valuable observations for assessing the event.This study leveraged ChinArray data from the 2015 Alxa Left Banner earthquake sequence,employing machine learning(specifically PhaseNet,a deep learning method,and GaMMA,a Bayesian approach)for automated seismic phase picking,association,and location analysis.Our generated catalog,comprising 10,432 phases from 708 events,is roughly ten times larger than the CENC catalog,encompassing all CENC events with strong consistency.A slight magnitude overestimation is observed only at lower magnitudes.Furthermore,the catalog adheres to the Gutenberg-Richter and Omori laws spatially,temporally,and in magnitude distribution,demonstrating its high reliability.Double-difference tomography refined locations for 366 events,yielding a more compact spatial distribution with horizontal errors within 100m,vertical errors within 300m,and travel-time residuals within 0.05s.Depths predominantly range from 10-30km.Aftershocks align primarily NEE,with the mainshock east of the aftershock zone.The near-vertical main fault plane dips northwestward,exhibiting a Y-shaped branching structure,converging at depth and expanding towards the surface.FOCMEC analysis,using first motion and amplitude ratios,yielded focal mechanism solutions for 10 events,including the mainshock.These solutions consistently indicate a strike-slip mechanism with a minor extensional component.Integrating the earthquake sequence's spatial distribution and focal mechanisms suggests the seismogenic structure is a negative flower structure,consistent with the Dengkou-Benjing fault.Comparing the CENC and ML-generated catalogs using the maximum curvature(MAXC)method reveals a 0.6 decrease in completeness magnitude(M_(C)).However,magnitude-frequency distribution discrepancies above the MAXC-estimated M_(C)suggest MAXC may underestimate both M_(C)and the b-value.This study analyzes the 2015 Alxa Left Banner M5.8 earthquake using a reliable,MLgenerated earthquake catalog,revealing detailed information about the sequence,faulting structure,aftershock distribution,and stress characteristics.展开更多
The study area is rich in shale gas resources and has reached the stage of comprehensive development. Shale gas extraction poses risks such as induced seismicity and well closure, compounded by the limited availabilit...The study area is rich in shale gas resources and has reached the stage of comprehensive development. Shale gas extraction poses risks such as induced seismicity and well closure, compounded by the limited availability of fi xed seismic monitoring stations nearby. To address these challenges, a dense observation array was developed within the study area to monitor and analyze microseismic activity during hydraulic fracturing. Microseismic events generated by hydraulic fracturing typically exhibit low amplitude and signal-to-noise ratio, rendering traditional manual analysis methods impractical. To overcome these limitations, an innovative artifi cial intelligence method combining picking-association-location (PAL) and match-expand- shift-stack (MESS) techniques (PALM) has been utilized for automated seismic detection. Numerous factors influence the accuracy of microseismic detection and localization. To evaluate these factors, the effects of various velocity structure models, instrument types, and station distributions on seismic location were analyzed and compared. The results indicate that the PALM method significantly mitigates the influence of velocity structure models on seismic location accuracy. Additionally, the use of broadband seismic instruments and a uniform station distribution enhances the precision of seismic location results. Furthermore, by integrating data from diff erent types of observation instruments, a comprehensive seismic catalog for the study area was established. These fi ndings not only enhance seismic location accuracy but also provide valuable guidance for optimizing regional seismic monitoring network design and improving seismic risk assessment.展开更多
This article introduces a cable-free real-time telemetry seismic acquisition system(hereinafter referred to as the cable-free real-time telemetry system)that utilizes 4G/5G technology.This system facilitates the real-...This article introduces a cable-free real-time telemetry seismic acquisition system(hereinafter referred to as the cable-free real-time telemetry system)that utilizes 4G/5G technology.This system facilitates the real-time acquisition and quality control of seismic data,the real-time monitoring of equipment location and health status,the synchronous transmission of collected data between the cloud and client,and the real-time issuance of operational instructions.It addresses the critical limitation of existing seismic node equipment,which is often restricted to mining and blind storage due to the absence of a wired or wireless communication link between the acquisition node device and the central control unit.This limitation necessitates local data storage and rendering real-time quality control unfeasible.Typically,quality control is conducted post-task completion,requiring the overall retrieval and downloading of data.If data issues are identifi ed,it becomes necessary to eliminate faulty tracks and determine the need for supplementary acquisition,which can lead to delays in the acquisition process.The implementation of real-time monitoring and early warning systems for equipment health status aims to mitigate the risk of poor data quality resulting from equipment anomalies.Furthermore,the real-time synchronous transmission between the cloud and server addresses the bottleneck of slow download speeds associated with the centralized retrieval of data from multiple node devices during blind acquisition and storage.A real-time microseismic data acquisition test and verifi cation were conducted at a fracturing site in an eastern oil and gas fi eld.Analysis of the test data indicates that the overall performance indicators of the system are comparable to those of existing mainstream system equipment,demonstrating stability and reliability.The performance parameters fully satisfy the technical requirements for oilfield fracturing monitoring scenarios,suggesting promising prospects for further promotion and application.展开更多
Taking the Qihe area as an example,this paper compared various geophysical exploration methods in view of the problems of urban construction,deep thermal reservoir burial,and vast overlying low-resistance shield layer...Taking the Qihe area as an example,this paper compared various geophysical exploration methods in view of the problems of urban construction,deep thermal reservoir burial,and vast overlying low-resistance shield layer in deep karst geothermal exploration.A Controlledsource audio magnetotelluric(CSAMT)method was taken to overcome the problems and detect deep stratigraphic structures in the study area.The acquisition parameters of CSAMT were optimized to take into account the exploration depth and signal-to-noise ratio.The distortion of data in the near and transition zone was eliminated by the inversion of equivalent whole-region apparent resistivity,so as to achieve the purpose of deep sounding.Based on the resistivity profile resulting from the proposed CSAMT method,three faults were inferred and one low-resistance anomaly zone in the area was traced.The results of the profile interpretation were verified by drilling.The inferred stratigraphic boundaries and low-resistance anomaly zone were basically in agreement with the drilling results,thereby proving the eff ectiveness of the CSAMT method for deep geothermal exploration in low-resistance coverage areas.This method could provide technical support for deep geothermal exploration in similar areas.展开更多
Medium-low temperature geothermal resources are abundant in the Guanxian fault depression.An essential foundation for the effective development and use of geothermal resources is the study of the genetic model and res...Medium-low temperature geothermal resources are abundant in the Guanxian fault depression.An essential foundation for the effective development and use of geothermal resources is the study of the genetic model and resource assessment of the geothermal system.This study examines the geothermal geological circumstances,hydrochemical features,and geothermal field characteristics based on the regional geological structure and prior research findings.The appraisal of geothermal resources is done,and a conceptual model of the geothermal system in the research area is built.The findings indicate that the Guan xian fault depression's geothermal resources are primarily Guantao Formation sandstone heat reservoirs.The geothermal water at the wellhead has a temperature between 54℃and 60℃,and its primary chemistry is Cl·SO_(4)-Na.Deep thermal conduction heats the geothermal water,which is then laterally supplied to the reservoir after being largely restored by air precipitation from the western Taihang Mountains.With an annual exploitable geothermal resource of 6,782×10^(12)J,or 23.14×10^(4)tons of standard coal,the Guantao Formation sandstone reservoir in the Guanxian depression has a geothermal resource of about 620.10×10^(16)J.An area of 18 million m^(2)can be heated by geothermal extraction per year,demonstrating the potential for geothermal resources and their high development and use value.展开更多
基金supported by 2024 Central Guidance Local Science and Technology Development Fund Project"Study on the mechanism and evaluation method of thermal pollution in water bodies,as well as research on thermal carrying capacity".(Grant 246Z4506G)Key Research and Development Project in Hebei Province:"Key Technologies and Equipment Research and Demonstration of Multiple Energy Complementary(Electricity,Heat,Cold System)for Solar Energy,Geothermal Energy,Phase Change Energy"(Grant 236Z4310G)the Hebei Academy of Sciences Key Research and Development Program"Research on Heat Transfer Mechanisms and Efficient Applications of Intermediate and Deep Geothermal Energy"(22702)。
文摘Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,in certain regions,the installation of buried pipes for heat exchangers may be complicated,and these pipes may not always serve as efficient low-temperature heat sources for the heat pumps of the system.To address this issue,the current study explored the use of solar-energy-collecting equipment to supplement buried pipes.In this design,both solar energy and geothermal energy provide low-temperature heat to the heat pump.First,a simulation model of a solar‒ground source heat pump coupling system was established using TRNSYS.The accuracy of this model was validated through experiments and simulations on various system configurations,including varying numbers of buried pipes,different areas of solar collectors,and varying volumes of water tanks.The simulations examined the coupling characteristics of these components and their influence on system performance.The results revealed that the operating parameters of the system remained consistent across the following configurations:three buried pipes,burial depth of 20 m,collector area of 6 m^(2),and water tank volume of 0.5 m^(3);four buried pipes,burial depth of 20 m,collector area of 3 m^(2),and water tank volume of 0.5 m^(3);and five buried pipes with a burial depth of 20 m.Furthermore,the heat collection capacity of the solar collectors spanning an area of 3 m^(2)was found to be equivalent to that of one buried pipe.Moreover,the findings revealed that the solar‒ground source heat pump coupling system demonstrated a lower annual cumulative energy consumption compared to the ground source heat pump system,presenting a reduction of 5.31%compared to the energy consumption of the latter.
基金Earth Observation and Navigation Special,Research on Low Temperature Superconducting Aeromagnetic Vector Gradient Observation Technology(2021YFB3900201)projectState Key Laboratory of Remote Sensing Science project.
文摘In this paper,we investigate the method of compensating LTS SQUID Gradiometer Systems data.By matching the attitude changes of the pod in fl ight to the anomalies of the magnetic measurement data,we find that the yaw attitude changes most dramatically and corresponds best to the magnetic data anomaly interval.Based on this finding,we solved the compensation model using least squares fitting and Huber's parametric fitting.By comparison,we found that the Huber parametric fit not only eliminates the interference introduced by attitude changes but also retains richer anomaly source information and therefore obtains a higher signal-to-noise ratio.The experimental results show that the quality of the magnetometry data obtained by using the compensation method proposed in this paper has been significantly improved,and the mean value of its improvement ratio can reach 118.93.
基金projects of China Railway Beijing Group Company Limited.(No.2016CG23)for funding this research。
文摘The geological disasters such as collapse,mud bursting and water gushing often occur during tunnel construction.Thus,it is of great significance to detect the hidden geological disasters ahead of the tunnel face.The audio magnetotelluric(AMT)was applied for the advanced detectionstudy during the boring process of the Tianheshan tunnel in the Taihang Mountains.Three AMT profiles were deployed above the tunnel,and the data obtained in the field were analysed in terms of electrical principal axes.From shallow to deep,the direction of the geoelectric strike angle changes,generally between 30°and 60°NE,which is consistent with similar to the direction of the Taihangshan Uplift,and the data show some 3D characteristics.Two-dimensional(2D)and three-dimensional(3D)inversion methods were adopted to jointly study the subsurface structural information,and the resistivity model was geophysically and geologically interpreted.Two sets of low resistance anomalies were found,and it was hypothesised that the near-erect low-resistivity anomalies in the east might be a fragmentation zone,while the low resistance anomalies in the west,which are inclined to the westward,might be a tectonic structure or fragmentation zone related to the regional major fault,and the results of the tunnelling confirmed the reliability of the inversion interpretation.The 3D inversion can fully reflect the development scale and morphological changes of the fracture zone,and the inversion model is more reliable.Finally,it is concluded that the audio magnetotelluric method,which adopts advanced acquisition,processing and inversion interpretation techniques,is an effective means of over-detection of tunnels.
基金National Natural Science Foundation of China(grant numbers 42293351,41877239,51422904 and 51379112).
文摘Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detection accuracy.Using multiple methods to carry out a comprehensive evaluation can eff ectively improve the accuracy of advanced geological prediction results.In this study,geological information is combined with the detection results of geophysical methods,including transient electromagnetic,induced polarization,and tunnel seismic prediction,to establish a comprehensive analysis method of adverse geology.First,the possible main adverse geological problems are determined according to the geological information.Subsequently,various physical parameters of the rock mass in front of the tunnel face can then be derived on the basis of multisource geophysical data.Finally,based on the analysis results of geological information,the multisource data fusion algorithm is used to determine the type,location,and scale of adverse geology.The advanced geological prediction results that can provide eff ective guidance for tunnel construction can then be obtained.
基金jointly funded by the National Natural Science Foundation of China(No.U2244220,No.42004125)the China Geological Survey Projects(No.DD20240119,No.DD20243245,No.DD20230114,No.DD20243244)the China Postdoctoral Science Foundation(No.2020M670601)。
文摘In the 3D inversion modeling of gravity and magnetic potential field data,the model weighting function is often applied to overcome the skin eff ect of inversion results.However,divergence occurs at the the deep area,and artificial weak negative anomalies form around the positive anomalies in the horizontal direction,resulting in a reduction in the overall resolution.To fully utilize the model weighting function,this study constructs a combined model weighting function.First,a new depth weighting function is constructed by adding a regulator into the conventional depth weighting function to overcome the skin eff ect and inhibit the divergence at the deep area of the inversion results.A horizontal weighting function is then constructed by extracting information from the observation data;this function can suppress the formation of artificial weak anomalies and improve the horizontal resolution of the inversion results.Finally,these two functions are coupled to obtain the combined model weighting function,which can replace the conventional depth weighting function in 3D inversion.It improves the vertical and horizontal resolution of the inversion results without increasing the algorithm complexity and calculation amount,is easy to operate,and adapts to any 3D inversion method.Two model experiments are designed to verify the effectiveness,practicability,and anti-noise of the combined model weighting function.Then the function is applied to the 3D inversion of the measured aeromagnetic data in the Jinchuan area in China.The obtained inversion results are in good agreement with the known geological data.
基金financially supported by The National Natural Science Foundation of China (42374004)the Open Fund of Hubei Luojia Laboratory (220100045)the Natural Science Foundation of Sichuan Province (2022NSFSC1047)。
文摘Since April 2002,the Gravity Recovery and Climate Experiment Satellite(GRACE)has provided monthly total water storage anomalies(TWSAs)on a global scale.However,these TWSAs are discontinuous because some GRACE observation data are missing.This study presents a combined machine learning-based modeling algorithm without hydrological model data.The TWSA time-series data for 11 large regions worldwide were divided into training and test sets.Autoregressive integrated moving average(ARIMA),long short-term memory(LSTM),and an ARIMA-LSTM combined model were used.The model predictions were compared with GRACE observations,and the model accuracy was evaluated using fi ve metrics:the Nash-Sutcliff e effi ciency coeffi cient(NSE),Pearson correlation coeffi cient(CC),root mean square error(RMSE),normalized RMSE(NRMSE),and mean absolute percentage error.The results show that at the basin scale,the mean CC,NSE,and NRMSE for the ARIMA-LSTM model were 0.93,0.83,and 0.12,respectively.At the grid scale,this study compared the spatial distribution and cumulative distribution function curves of the metrics in the Amazon and Volga River basins.The ARIMA-LSTM model had mean CC and NSE values of 0.89 and 0.61 and 0.92 and 0.61 in the Amazon and Volga River basins,respectively,which are superior to those of the ARIMA model(0.86 and 0.48 and 0.88 and 0.46,respectively)and the LSTM model(0.80 and 0.41 and 0.89 and 0.31,respectively).In the ARIMA-LSTM model,the proportions of grid cells with NSE>0.50 for the two basins were 63.3%and 80.8%,while they were 54.3%and 51.3%in the ARIMA model and 53.7%and 43.2%in the LSTM model.The ARIMA-LSTM model significantly improved the NSE values of the predictions while guaranteeing high CC values in the GRACE data reconstruction at both scales,which can aid in fi lling in discontinuous data in temporal gravity fi eld models..
基金supported by Technology Innovation Fund of China Coal Research Institute(2022CX-I-04)Science and Technology Innovation Venture Capital Project of China Coal Technology Engineering Group(2020-2-TD-CXY005)。
文摘Enhancing the mining speed of a working face has become the primary approach to achieve high production and efficiency in coal mines,thereby further improving the production capacity.However,the problem of rock bursts resulting from this approach has become increasingly serious.Therefore,to implement coal mine safety and efficient extraction,the impact of deformation pressure caused by different mining speeds should be considered,and a reasonable mining speed of the working face should be determined.The influence of mining speed on overlying rock breaking in the stope is analyzed by establishing a key layer block rotation and subsidence model.Results show that with the increasing mining speed,the compression amount of gangue in the goaf decreases,and the rotation and subsidence amount of rock block B above goaf decreases,forcing the rotation and subsidence amount of rock block A above roadway to increase.Consequently,the contact mode between rock block A and rock block B changes from line contact to point contact,and the horizontal thrust and shear force between blocks increase.The increase in rotation and subsidence of rock block A intensifies the compression degree of coal and rock mass below the key layer,thereby increasing the stress concentration degree of coal and rock mass as well as the total energy accumulation.In addition,due to the insufficient compression of gangue in the goaf,the bending and subsidence space of the far-field key layer are limited,the length of the suspended roof increases,and the influence range of mining stress and the energy accumulation range expand.Numerical test results and underground microseismic monitoring results verify the correlation between mining speed and stope energy,and high-energy events generally appear 1-2 d after the change in mining speed.On this basis,the statistical principle confirms that the maximum mining speed of the working face at 6 m/d is reasonable.
基金funded by the National Key R&D Program of China(Grant no.2018YFA0702504)the Sinopec research project(P22162).
文摘Absorption compensation is a process involving the exponential amplification of reflection amplitudes.This process amplifies the seismic signal and noise,thereby substantially reducing the signal-tonoise ratio of seismic data.Therefore,this paper proposes a multichannel inversion absorption compensation method based on structure tensor regularization.First,the structure tensor is utilized to extract the spatial inclination of seismic signals,and the spatial prediction filter is designed along the inclination direction.The spatial prediction filter is then introduced into the regularization condition of multichannel inversion absorption compensation,and the absorption compensation is realized under the framework of multichannel inversion theory.The spatial predictability of seismic signals is also introduced into the objective function of absorption compensation inversion.Thus,the inversion system can effectively suppress the noise amplification effect during absorption compensation and improve the recovery accuracy of high-frequency signals.Synthetic and field data tests are conducted to demonstrate the accuracy and effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(42364005,42174074,42064008 and 41704053)Science&Technology Fundamental Resources Investigation Program(Grant No.2023FY201500)+1 种基金Science and Technology Plan Project of Jiangxi Province(20212BCJ23002,20232ACB213013)the East China University of Technology Research Foundation for Advanced Talents(ECUT)(DHBK2019084)。
文摘Earthquakes not only release the long-term accumulated stress on the seismogenic fault but may also increase the stress on some surrounding faults or other segments of the seismogenic fault,thereby raising the seismic risk on these faults.This study investigates the impact of the April 2,2024,Mw 7.4 earthquake in Hualien,Taiwan,China,on the surrounding faults and aftershocks.We analyze stress-triggering effects by calculating Coulomb stress changes(ΔCFS)using rupture models and focal mechanism data.Historical focal mechanism nodal planes serve as receiver fault parameters forΔCFS calculations.Our findings indicate signifi cant Coulomb stress loading on the Longitudinal Valley fault and Central Range structure due to the mainshock,promoting their seismic activity.Loading effects vary by fault type,with thrust and strike-slip faults experiencing more stress loading than normal and odd faults.Conversely,the rupture’s coseismic slip concentration area shows predominant stress unloading,inhibiting seismic activity in the region.Aftershocks mainly experience increasedΔCFS,suggesting that the stress-triggering induced by the mainshock considerably influences the earthquake sequence evolution.These insights are crucial for understanding aftershock patterns and enhancing seismic hazard assessments.
基金Collaborative Project Grant from the Exploration and Development Research Institute of SINOPEC Northwest Oilfi eld Company(Grant No.KY2021-S-104).
文摘The Tarim Basin has revealed numerous tight sandstone oil and gas reservoirs.The tidal fl at zone in the Shunbei area is currently in the detailed exploration stage,requiring a comprehensive description of the sand body distribution characteristics for rational exploration well deployment.However,using a single method for sand body prediction has yielded poor results.Seismic facies analysis can eff ectively predict the macro-development characteristics of sedimentary sand bodies but lacks the resolution to capture fine details.In contrast,single-well sedimentary facies analysis can describe detailed sand body development but struggles to reveal broader trends.Therefore,this study proposes a method that combines seismic facies analysis with single-well sedimentary microfacies analysis,using the lower section of the Kepingtage Formation in the Shunbei area as a case study.First,seismic facies were obtained through unsupervised vector quantization to control the macro-distribution characteristics of sand bodies,while principal component analysis(PCA)was applied to improve the depiction of fine sand body details from seismic attributes.Based on 3D seismic data,well-logging data,and geological interpretation results,a detailed structural interpretation was performed to establish a high-precision stratigraphic framework,thereby enhancing the accuracy of sand body prediction.Seismic facies analysis was then conducted to obtain the macro-distribution characteristics of the sand bodies.Subsequently,core data and logging curves from individual wells were used to clarify the vertical development characteristics of tidal channels and sandbars.Next,PCA was employed to select the seismic attributes most sensitive to sand bodies in diff erent sedimentary facies.Results indicate that RMS amplitude in the subtidal zone and instantaneous phase in the intertidal zone are the most sensitive to sand bodies.A comparative analysis of individual seismic attributes for sand body characterization revealed that facies-based delineation improved the accuracy of sand body identification,eff ectively capturing their contours and shapes.This method,which integrates seismic facies,single-well sedimentary microfacies,and machine learning techniques,enhances the precision of sand body characterization and off ers a novel approach to sand body prediction.
基金supported by the Natural Science Foundation of Tianjin (No. 22JCQNJC01070)the National Natural Science Foundation of China (No. 42404079)the Key Project of Tianjin Earthquake Agency (No. Zd202402)。
文摘Disaster mitigation necessitates scientifi c and accurate aftershock forecasting during the critical 2 h after an earthquake. However, this action faces immense challenges due to the lack of early postearthquake data and the unreliability of forecasts. To obtain foundational data for sequence parameters of the land-sea adjacent zone and establish a reliable and operational aftershock forecasting framework, we combined the initial sequence parameters extracted from envelope functions and incorporated small-earthquake information into our model to construct a Bayesian algorithm for the early postearthquake stage. We performed parameter fitting and early postearthquake aftershock occurrence rate forecasting and effectiveness evaluation for 36 earthquake sequences with M ≥ 4.0 in the Bohai Rim region since 2010. According to the results, during the early stage after the mainshock, earthquake sequence parameters exhibited relatively drastic fl uctuations with signifi cant errors. The integration of prior information can mitigate the intensity of these changes and reduce errors. The initial and stable sequence parameters generally display advantageous distribution characteristics, with each parameter’s distribution being relatively concentrated and showing good symmetry and remarkable consistency. The sequence parameter p-values were relatively small, which indicates the comparatively slow attenuation of signifi cant earthquake events in the Bohai Rim region. A certain positive correlation was observed between earthquake sequence parameters b and p. However, sequence parameters are unrelated to the mainshock magnitude, which implies that their statistical characteristics and trends are universal. The Bayesian algorithm revealed a good forecasting capability for aftershocks in the early postearthquake period (2 h) in the Bohai Rim region, with an overall forecasting effi cacy rate of 76.39%. The proportion of “too low” failures exceeded that of “too high” failures, and the number of forecasting failures for the next three days was greater than that for the next day.
基金The active fault exploration and seismic risk assessment project of Huaibei and the research and development project of Beijing Disaster Prevention Technology Co.,Ltd.(FZKJYF202201)jointly funded this work。
文摘The investigation of the tectonic deformation characteristics at the front margin of the Xu-Su arc tectonic belt provides important reference points for identifying and analyzing its genetic mechanism,tectonic evolution process,and the latest evidence of tectonic deformation.In this study,two reflection seismic exploration profiles across the front margin of the Xu-Su arc tectonic belt are utilized to reveal that the Qinglongshan fault is the thrust fault of its front margin boundary.The kinematic properties and tectonic deformation characteristics of the internal faults in the front margin basin are also obtained.Using the Qinglongshan fault as the boundary,the middle and posterior margins of the Xu-Su arc tectonic belt are composed of numerous thrust faults,which suggest strong ancient tectonic movement.However,a large number of normal faults are developed within the front margin basin,with some faults exhibiting strike-slip and growth properties,which indicate strong neotectonic movement.Results reveal that the Xu-Su arc tectonic belt is a large-scale thrust-nappe structure that has undergone structural inversion.The Xu-Su arc tectonic belt experienced strong tectonic activity during the Middle Pleistocene,and the most recent tectonic deformation has extended into the front margin basin interior.
基金National Natural Science Foundation of China(41630640)National Science Foundation of Innovation Research Group(41521002)+1 种基金National Natural Science Foundation of China(41790445)Construction S&T Project of Department of Transportation of Sichuan Province(Grant No.2020A01).
文摘The stratum lithology and geological structure of the highway tunnel in the mountainous areas of western China are complex,and the engineering geological conditions are complicated.When the highway tunnel passes through different lithological strata,its structural design and construction technology are completely diff erent.Therefore,in order to support the tunnel design and construction,the tunnel survey Among them,the identification of the contact boundary between magmatic rock and metamorphic rock and the grade of surrounding rock is very important.Through magnetotelluric survey of the Mupi tunnel of Jiuzhaigou-Mianyang highway on G8513 line,2D forward numerical simulation,1D,2D,3D inversion,and engineering geological analysis,it is revealed that the electrical characteristics of each layer,focusing on the identification of the contact boundary between magmatic rock and metamorphic rock.This study provides the electrical characteristics of the magmatic rock and metamorphic rock contact boundary of the Mupi Tunnel.It is speculated that the boundary is revealed by the tunnel construction excavation,which verifies the correctness of the geophysical inversion model and provides a more detailed design basis for the tunnel design.I believe that taking the Mupi Tunnel survey as an example,through this research,it can provide detailed geophysical evidence for highway tunnels to distinguish between magmatic rock and metamorphic rock.
基金supported in part by the National Science Fund for Distinguished Young Scholars under Grant (42025403)the National Key Research and Development Plan of China (2021YFA0716800)the National Key Research and Development Plan of China (2022YFC2903804)。
文摘The increasing risk of ground pressure disasters resulting from deep well mining highlights the urgent need for advanced monitoring and early warning systems.Ground pressure monitoring,supported by microseismic technology,plays a pivotal role in ensuring mine safety by enabling real-time identifi cation and accurate classification of vibration signals such as microseismic signals,blasting signals,and noise.These classifications are critical for improving the efficacy of ground pressure monitoring systems,conducting stability analyses of deep rock masses,and implementing timely and precise roadway support measures.Such eff orts are essential for mitigating ground pressure disasters and ensuring safe mining operations.This study proposes an artificial intelligence-based automatic classification network model for mine vibration signals.Based on conventional convolutional neural networks,the proposed model further incorporates long short-term memory(LSTM)networks and attention mechanisms.The LSTM component eff ectively captures temporal correlations in time-series mining vibration data,while the attention mechanism enhances the models’ability to focus on critical features within the data.To validate the eff ectiveness of our proposed model,a dataset comprising 480,526 waveform records collected in 2022 by the microseismic monitoring system at Guangxi Shanhu Tungsten Mine was used for training,validation,and testing purposes.Results demonstrate that the proposed artifi cial intelligence-based classifi cation method achieves a higher recognition accuracy of 92.21%,significantly outperforming traditional manual classification methods.The proposed model represents a signifi cant advancement in ground pressure monitoring and disaster mitigation.
基金Deep Earth Probe and Mineral Resources ExplorationNational Science and Technology Major Project(2024ZD1000208)SinoProbe Laboratory Fund of Chinese Academy of Geological Sciences(SL202401)+3 种基金Project of the Nuclear Technology Application Engineering Research Center of the Ministry of Education(HJSJYB2021-3)2022 Fuzhou Science and Technology Plan Project(Research on High Voltage Electrostatic Atomization New Air Sterilization and Purification Technology and Equipment)Jiangxi Province Major Science and Technology Special Project(20233AAE02008)Fuzhou Unveiling and Leading Project(Jiangxi Gandian)-Online Diagnosis and Intelligent Cloud Platform for the Health Status of Transformer and Distribution Equipment。
文摘Geomagnetic data hold significant value in fields such as earthquake monitoring and deep earth exploration.However,the increasing severity of anthropogenic noise contamination in existing geomagnetic observatory data poses substantial challenges to high-precision computational analysis of geomagnetic data.To overcome this problem,we propose a denoising method for geomagnetic data based on the Residual Shrinkage Network(RSN).We construct a sample library of simulated and measured geomagnetic data develop and train the RSN denoising network.Through its unique soft thresholding module,RSN adaptively learns and removes noise from the data,effectively improving data quality.In experiments with noise-added measured data,RSN enhances the quality of the noisy data by approximately 12 dB on average.The proposed method is further validated through denoising analysis on measured data by comparing results of time-domain sequences,multiple square coherence and geomagnetic transfer functions.
基金funded by the Inner Mongolia Natural Science Foundation(No.2024MS04021)the Science and Technology Plan of Inner Mongolia Autonomous Region(No.2023YFSH0004)the Director Fund of the Inner Mongolia Autonomous Region Seismological Bureau(No.2023GG01,No.2023GG02,No.2023MS05,No.2023QN13)。
文摘Machine learning(ML)efficiently and accurately processes dense seismic array data,improving earthquake catalog creation,which is crucial for understanding earthquake sequences and fault systems;analyzing its reliability is also essential.An M5.8 earthquake struck Alxa Left Banner,Inner Mongolia,China on April 15,2015,a region with limited CENC monitoring capabilities,making analysis challenging.However,abundant data from ChinArray provided valuable observations for assessing the event.This study leveraged ChinArray data from the 2015 Alxa Left Banner earthquake sequence,employing machine learning(specifically PhaseNet,a deep learning method,and GaMMA,a Bayesian approach)for automated seismic phase picking,association,and location analysis.Our generated catalog,comprising 10,432 phases from 708 events,is roughly ten times larger than the CENC catalog,encompassing all CENC events with strong consistency.A slight magnitude overestimation is observed only at lower magnitudes.Furthermore,the catalog adheres to the Gutenberg-Richter and Omori laws spatially,temporally,and in magnitude distribution,demonstrating its high reliability.Double-difference tomography refined locations for 366 events,yielding a more compact spatial distribution with horizontal errors within 100m,vertical errors within 300m,and travel-time residuals within 0.05s.Depths predominantly range from 10-30km.Aftershocks align primarily NEE,with the mainshock east of the aftershock zone.The near-vertical main fault plane dips northwestward,exhibiting a Y-shaped branching structure,converging at depth and expanding towards the surface.FOCMEC analysis,using first motion and amplitude ratios,yielded focal mechanism solutions for 10 events,including the mainshock.These solutions consistently indicate a strike-slip mechanism with a minor extensional component.Integrating the earthquake sequence's spatial distribution and focal mechanisms suggests the seismogenic structure is a negative flower structure,consistent with the Dengkou-Benjing fault.Comparing the CENC and ML-generated catalogs using the maximum curvature(MAXC)method reveals a 0.6 decrease in completeness magnitude(M_(C)).However,magnitude-frequency distribution discrepancies above the MAXC-estimated M_(C)suggest MAXC may underestimate both M_(C)and the b-value.This study analyzes the 2015 Alxa Left Banner M5.8 earthquake using a reliable,MLgenerated earthquake catalog,revealing detailed information about the sequence,faulting structure,aftershock distribution,and stress characteristics.
基金the support of the China Three Gorges Corporation Science and Technology Fund, with the numbers 0799275the support of the National Natural Science Foundation of China, with the numbers 42174177 and 62106239。
文摘The study area is rich in shale gas resources and has reached the stage of comprehensive development. Shale gas extraction poses risks such as induced seismicity and well closure, compounded by the limited availability of fi xed seismic monitoring stations nearby. To address these challenges, a dense observation array was developed within the study area to monitor and analyze microseismic activity during hydraulic fracturing. Microseismic events generated by hydraulic fracturing typically exhibit low amplitude and signal-to-noise ratio, rendering traditional manual analysis methods impractical. To overcome these limitations, an innovative artifi cial intelligence method combining picking-association-location (PAL) and match-expand- shift-stack (MESS) techniques (PALM) has been utilized for automated seismic detection. Numerous factors influence the accuracy of microseismic detection and localization. To evaluate these factors, the effects of various velocity structure models, instrument types, and station distributions on seismic location were analyzed and compared. The results indicate that the PALM method significantly mitigates the influence of velocity structure models on seismic location accuracy. Additionally, the use of broadband seismic instruments and a uniform station distribution enhances the precision of seismic location results. Furthermore, by integrating data from diff erent types of observation instruments, a comprehensive seismic catalog for the study area was established. These fi ndings not only enhance seismic location accuracy but also provide valuable guidance for optimizing regional seismic monitoring network design and improving seismic risk assessment.
基金funded by the National Natural Science Foundation of China (42074127)the Key Program of National Natural Science Foundation of China (41930425)Research on Key Technologies for the Production, Exploration, and Development of Continental Shale Oil (2023ZZ15YJ02)。
文摘This article introduces a cable-free real-time telemetry seismic acquisition system(hereinafter referred to as the cable-free real-time telemetry system)that utilizes 4G/5G technology.This system facilitates the real-time acquisition and quality control of seismic data,the real-time monitoring of equipment location and health status,the synchronous transmission of collected data between the cloud and client,and the real-time issuance of operational instructions.It addresses the critical limitation of existing seismic node equipment,which is often restricted to mining and blind storage due to the absence of a wired or wireless communication link between the acquisition node device and the central control unit.This limitation necessitates local data storage and rendering real-time quality control unfeasible.Typically,quality control is conducted post-task completion,requiring the overall retrieval and downloading of data.If data issues are identifi ed,it becomes necessary to eliminate faulty tracks and determine the need for supplementary acquisition,which can lead to delays in the acquisition process.The implementation of real-time monitoring and early warning systems for equipment health status aims to mitigate the risk of poor data quality resulting from equipment anomalies.Furthermore,the real-time synchronous transmission between the cloud and server addresses the bottleneck of slow download speeds associated with the centralized retrieval of data from multiple node devices during blind acquisition and storage.A real-time microseismic data acquisition test and verifi cation were conducted at a fracturing site in an eastern oil and gas fi eld.Analysis of the test data indicates that the overall performance indicators of the system are comparable to those of existing mainstream system equipment,demonstrating stability and reliability.The performance parameters fully satisfy the technical requirements for oilfield fracturing monitoring scenarios,suggesting promising prospects for further promotion and application.
基金National Natural Science Foundation of China(No 52174048).
文摘Taking the Qihe area as an example,this paper compared various geophysical exploration methods in view of the problems of urban construction,deep thermal reservoir burial,and vast overlying low-resistance shield layer in deep karst geothermal exploration.A Controlledsource audio magnetotelluric(CSAMT)method was taken to overcome the problems and detect deep stratigraphic structures in the study area.The acquisition parameters of CSAMT were optimized to take into account the exploration depth and signal-to-noise ratio.The distortion of data in the near and transition zone was eliminated by the inversion of equivalent whole-region apparent resistivity,so as to achieve the purpose of deep sounding.Based on the resistivity profile resulting from the proposed CSAMT method,three faults were inferred and one low-resistance anomaly zone in the area was traced.The results of the profile interpretation were verified by drilling.The inferred stratigraphic boundaries and low-resistance anomaly zone were basically in agreement with the drilling results,thereby proving the eff ectiveness of the CSAMT method for deep geothermal exploration in low-resistance coverage areas.This method could provide technical support for deep geothermal exploration in similar areas.
基金funded by the Hebei Province Natural Resources Science and Technology Project(13000024P00F2D410443X).
文摘Medium-low temperature geothermal resources are abundant in the Guanxian fault depression.An essential foundation for the effective development and use of geothermal resources is the study of the genetic model and resource assessment of the geothermal system.This study examines the geothermal geological circumstances,hydrochemical features,and geothermal field characteristics based on the regional geological structure and prior research findings.The appraisal of geothermal resources is done,and a conceptual model of the geothermal system in the research area is built.The findings indicate that the Guan xian fault depression's geothermal resources are primarily Guantao Formation sandstone heat reservoirs.The geothermal water at the wellhead has a temperature between 54℃and 60℃,and its primary chemistry is Cl·SO_(4)-Na.Deep thermal conduction heats the geothermal water,which is then laterally supplied to the reservoir after being largely restored by air precipitation from the western Taihang Mountains.With an annual exploitable geothermal resource of 6,782×10^(12)J,or 23.14×10^(4)tons of standard coal,the Guantao Formation sandstone reservoir in the Guanxian depression has a geothermal resource of about 620.10×10^(16)J.An area of 18 million m^(2)can be heated by geothermal extraction per year,demonstrating the potential for geothermal resources and their high development and use value.
