Journal of Applied Geophysics最新文献

{"title":"Recognition and classification of microseismic event waveforms based on histogram of oriented gradients and shallow machine learning approach","authors":"Hongmei Shu ,&nbsp;Ahmad Yahya Dawod ,&nbsp;Longjun Dong","doi":"10.1016/j.jappgeo.2024.105551","DOIUrl":"10.1016/j.jappgeo.2024.105551","url":null,"abstract":"<div><div>Accurate identification of microseismic events is vital for understanding underground rock deformation, rupture behavior, and mechanical properties. This study proposes a method that combines the Histogram of Orientation Gradient (HOG) and shallow machine learning techniques for microseismic waveform recognition. HOG features are extracted from event waveform images, and five classifiers including Linear classifier (LC), Fisher Discriminant (FD), Decision Tree (DT), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM) are compared. Experimental results show good accuracy and efficiency, with the SVM classifier and FD classifier achieving the best performance at 97.1 % and 96.9 % accuracy, respectively. Compared to previous studies, this method offers simplicity, ease of use, and low computational resource requirements, making it valuable for real-time monitoring and disaster prediction applications. It provides a foundation for evaluating mine geological structure stability.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105551"},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospection of faults on the Southern Erftscholle (Germany) with individually and jointly inverted refraction seismics and electrical resistivity tomography","authors":"Nino Menzel ,&nbsp;Norbert Klitzsch ,&nbsp;Michael Altenbockum ,&nbsp;Lisa Müller ,&nbsp;Florian M. Wagner","doi":"10.1016/j.jappgeo.2024.105549","DOIUrl":"10.1016/j.jappgeo.2024.105549","url":null,"abstract":"<div><div>As part of the Lower Rhein Embayment (LRE), the Southern Erft block is characterized by a complex tectonic setting that influences hydrological and geological conditions on a local as well as regional level. The study area is located in the south of North Rhine-Westphalia and traversed by several NW-SE-oriented fault structures. Since the tectonic structures were located by past studies based on a sparse foundation of geological data, the positions include considerable uncertainties. Therefore, it was decided to re-evaluate and refine the assumed fault locations by conducting geophysical measurements. Seismic Refraction Tomography (SRT) as well as Electrical Resistivity Tomography (ERT) was performed along seven measurement profiles with a length of up to 1.1 km. In addition to compiling individual resistivity and velocity models for all deduced measurements, ERT and SRT datasets were cooperatively inverted using the Structurally Coupled Cooperative Inversion (SCCI). This algorithm strengthens structural similarities between velocity and resistivity by adapting the individual regularizations after each model iteration. Previously assumed locations of the tectonic structures diverge from the new evidence based on ERT and SRT surveys. Especially in the western and eastern parts of the research area, differences between the survey results and formerly assumed locations are in the order of 100 m. Seismic and geoelectric measurements further indicate a fault structure in the southern part of the area, which remained undetected by past studies. The cooperative inversions do not improve the geophysical models qualitatively, since the individually inverted datasets already provide results of good quality and resolution.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"231 ","pages":"Article 105549"},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Salt dome identification using incremental semi-supervised learning and unsupervised learning-based label generation","authors":"Kui Wu ,&nbsp;Wei Hu ,&nbsp;Yu Qi ,&nbsp;Yixin Yu ,&nbsp;Sanyi Yuan","doi":"10.1016/j.jappgeo.2024.105552","DOIUrl":"10.1016/j.jappgeo.2024.105552","url":null,"abstract":"<div><div>Salt domes represent distinctive geological anomalies in seismic data, crucial for pinpointing hydrocarbon reservoirs and strategizing drilling paths. Conventional seismic attributes or computer vision methods usually fail to capture the intricate details of salt domes, resulting in interpretation results marred by noise. While deep learning presents a promising approach for intelligent 3D salt dome interpretation, its effectiveness is heavily dependent on the availability of labeled samples. To facilitate accurate interpretation, we propose an innovative workflow that integrates an unsupervised label generation component with an incremental semi-supervised learning framework utilizing the U-Net architecture. To generate salt dome labels, we prioritize both the root mean square (RMS) amplitude attribute and variance attribute (VA) as foundational data. Utilizing convolutional autoencoders (CAE), we establish a relationship between the input RMS attribute and the output reconstructed attribute. The intermediate features extracted by CAE are transformed into the salt boundary feature via principal component analysis and K-Means clustering. Concurrently, we employ K-Means clustering on VA to ascertain the salt internal feature. We further propose a feature aggregation method to consolidate the salt boundary feature and the salt internal feature for label generation of the salt dome. For 3D salt dome interpretation, we begin by predicting adjacent test datasets using labels generated by the unsupervised salt dome label generation module. The prediction results of these test datasets are then integrated into the training datasets to enhance the interpretation performance of U-Net, steering it towards an incremental semi-supervised learning method for salt dome interpretation. Additionally, we extend this research by applying transfer learning techniques for identifying mound-shoals using the same semi-supervised model parameters initially developed for interpreting salt domes. This method is validated using datasets from the Netherlands F3 block for salt domes and the North China block for mound-shoals. The results demonstrate that this innovative process only requires a minimal number of labels from unsupervised methods to precisely interpret salt domes across 3D seismic data. Furthermore, the low-level features of salt domes learned from neural network can be seamlessly transferred to mound-shoal identification. This automated approach significantly streamlines the interpretation process, reducing the time and resources traditionally necessary for reservoir analysis.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105552"},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microseismic precursor response characteristics of rockburst in the super-long working face: A case study","authors":"Fei Tang ,&nbsp;Yueping Qin","doi":"10.1016/j.jappgeo.2024.105550","DOIUrl":"10.1016/j.jappgeo.2024.105550","url":null,"abstract":"<div><div>Rockburst is one of the significant dynamic hazards of coal and rock bodies during super-long working face mining. Microseismic (MS) technology has been widely used to monitor the dynamic hazards of coal and rock bodies. By analyzing the parameters and statistics of seismic events, the level of rock burst hazard can be assessed. Then, the prevention and control measures taken in advance in the working face should be guided to reduce the impact damage. This study analyzed the precursor characteristics of rockburst MS signals in super-long working faces from spatial distribution, total daily energy, number of MS events, spectrograms, and b-value of MS signals. The results show that the MS events are mainly distributed in the coal seam roof three days before the occurrence of rockburst, the proportion of daily MS events in the coal seam roof increases, and the number of MS events shows a continuous decline. The proportion of large energy MS signals is higher than that of conventional and inclined seam workings in super-long workings before rockbursts; the amplitude of the MS signals from the super-long working face is large, the vibration duration is long (0.8–1.4 s) and the frequency is low; with the approach of rockburst, the low-energy frequency band tends to increase and the frequency decreases. The proportion of the low-energy frequency band (0–40 Hz) of the precursor of impact ground pressure is high. The main frequency of the MS signal of the super-long working face is lower than that of the conventional working face and the inclined coal seam working face when the rockburst occurs; rockburst often occurs in the b-value decreasing stage, and the number of MS events and b-value changes before the rockburst shows the same downward trend, rockburst occurs when the occurrence of the b-value is less than 0.8. The study results for the safety of the super-long working face mining back to provide a scientific basis.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105550"},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved sub-ice platelet layer mapping with multi-frequency EM induction sounding","authors":"Mara Neudert ,&nbsp;Stefanie Arndt ,&nbsp;Stefan Hendricks ,&nbsp;Mario Hoppmann ,&nbsp;Markus Schulze ,&nbsp;Christian Haas","doi":"10.1016/j.jappgeo.2024.105540","DOIUrl":"10.1016/j.jappgeo.2024.105540","url":null,"abstract":"<div><div>In Antarctica, sub-ice platelet layers (SIPL) accumulate beneath sea ice where ice crystals emerge from adjacent ice shelf cavities, serving as a unique habitat and indicator of ice-ocean interaction. Atka Bay in the eastern Weddell Sea, close to the German overwintering base Neumayer Station III, is well known for hosting a SIPL linked to ice shelf water outflow from beneath the Ekström Ice Shelf. This study presents a comprehensive analysis of an extensive multi-frequency electromagnetic (EM) induction sounding dataset in Atka Bay. Employing an open-source inversion scheme, the dataset was inverted to determine fast ice and platelet layer thicknesses along with their electrical conductivities. From electrical conductivity of the SIPL, we derive the SIPL solid fraction. Our results demonstrate the capability of obtaining high-resolution maps of SIPL thickness over extensive areas, providing unprecedented insights into accumulation patterns and identifying regions of ice-shelf water outflow in Atka Bay. Calibration in a zero-conductivity environment on the ice shelf proves effective, reducing logistical efforts for correcting electronic offsets and drift. Moreover, we demonstrate that both instrument noise and motion noise are sufficiently low to accurately determine SIPL thickness, with uncertainties within the decimeter range. Notably, this investigation is the first to cover the entirety of Atka Bay, including ice shelf fringes, overcoming limitations of prior studies. Our approach represents a significant advancement in studying ocean/ice-shelf interactions using non-destructive EM methods, emphasizing the potential to assess future changes in sub-ice shelf processes. In the future, the adaptation of this method to airborne multi-frequency EM measurements using drones or aircraft has the potential to further extend spatial coverage.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105540"},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research and application of joint-constrained inversion of transient electromagnetic multivariate parameter","authors":"Jian-lei Guo ,&nbsp;Yan-wei Hou ,&nbsp;Xiong-wei Li ,&nbsp;Zhi-peng Qi ,&nbsp;Ke-rui Fan ,&nbsp;Wen-han Li ,&nbsp;Wei-hua Yao ,&nbsp;Xiu Li","doi":"10.1016/j.jappgeo.2024.105548","DOIUrl":"10.1016/j.jappgeo.2024.105548","url":null,"abstract":"<div><div>Due to the phenomena of stratigraphic inclination, complex structure, and lateral discontinuity of resistivity or layer thickness in most of the coal seams, the traditional one-dimensional transient electromagnetic inversion method has limitations in interpretation accuracy. In addition, two- and three-dimensional inversion and artificial intelligence inversion have problems of large computation and large sample size, respectively, which limit their application in small- and medium-sized engineering exploration. To improve the inversion effect, this study proposes a method of joint-constrained inversion of transient electromagnetic multivariate parameters. This method achieves the joint constraint inversion of the transient electromagnetic multi-parameter by making full use of the geological data and a priori information to construct the initial model and adding the constraints such as the resistivity, the thickness, and the layer interface of each layer in the inversion objective function, and at the same time, taking into account the spatial correlation of the stratigraphic structure between the neighboring measurement points, as well as the transverse and vertical constraints between the measurement points along the direction of the survey line and perpendicular to the survey line. First, a series of typical geoelectric models are established and numerically simulated, and the results are compared with those of the traditional inversion method to verify the applicability and effectiveness of the method. Then, the constrained inversion is carried out on the physical simulation and measured data, and the results are in good agreement with the actual geological conditions. The numerical simulation, physical simulation and measured data inversion results consistently prove that this method can effectively reduce the uncertainty of the inversion at the isolated measuring points, improve the spatial continuity of the formation boundary, and better reflect the actual geoelectric characteristics of the formation.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105548"},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insights from electrical resistivity tomography on the hydrogeological interaction between sand dams and the weathered basement aquifer","authors":"Hannah Ritchie ,&nbsp;Ian Holman ,&nbsp;Justus Nyangoka ,&nbsp;Paul Bauman ,&nbsp;Alison Parker","doi":"10.1016/j.jappgeo.2024.105542","DOIUrl":"10.1016/j.jappgeo.2024.105542","url":null,"abstract":"<div><div>Sand dams, composed of recent alluvial aquifers behind concrete dam walls, are a water management technique in drylands. However, their level of hydraulic connectivity with their surrounding weathered basement aquifer is debated. This study aims to constrain this hydrogeological uncertainty in order to better understand their ability to meet water needs and improve dryland water security. The study is the first to use 2D geophysics (Electrical Resistivity Tomography) to provide evidence of seepage from sand dams at three mature and three newly built sites. A generally greater hydraulic connectivity was found between sand dams and their surrounding aquifer than has been assumed in some previous studies, with sites providing at least some local recharge rather than existing as isolated storage structures. This improved understanding is beneficial for both site selection and the performance of sand dams and can help ensure that maximum benefits are derived from the construction of a sand dam depending on its intended purpose.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105542"},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geophysical characterization of the bedrock and regolith in the Pranmati basin critical zone, Uttarakhand Himalaya","authors":"G. Pavankumar,&nbsp;Akashdeep Barman,&nbsp;M. Demudu Babu,&nbsp;Raj Sunil Kandregula,&nbsp;N.N. Chakravarthi,&nbsp;Ajay Manglik","doi":"10.1016/j.jappgeo.2024.105547","DOIUrl":"10.1016/j.jappgeo.2024.105547","url":null,"abstract":"<div><div>The young active Himalayan mountain is characterized by steep slope and dissected topography in overall compressive tectonic setting. The mountain belt has primarily coarse textured soil with poor water holding capacity and is highly prone to erosion. The erosion not only affects many ecosystems located at downstream but also has detrimental effects on the <em>critical zone (CZ)</em>. In the present study, we have carried out DC electrical resistivity study in the Pranmati catchment of the Alaknanda basin, a Himalayan critical zone in the Lesser Himalaya, to understand the pattern of soil erosion, transportation and deposition by characterizing the bedrock architecture and hence regolith thickness. A total of 6 electrical resistivity tomogram (ERT) profiles were laid at two locations in the catchment, one in a plain grassland and another at a crop field located on a hill slope of &gt;25^o. The study area in the Baijnath klippe, consists of quartz-biotite gneisses with layers of quartz mica-schist enclosed by thrust faults. Electrical resistivity sections of the downslope grassland site show a sharp resistivity contrast between the southwest and northeast transects suggesting south-eastern increase in dip of the bedrock, oblique to the north-east facing surface topography and a thick regolith (&gt; 10 m). The resistivity sections of the site located on the hillslope yield a very thin layer of regolith (&lt; 2 m) indicating significant soil erosion and high weathering of the bedrock. We propose that the water–rock interaction within the porous regolith facilitated by subsurface water circulation might be a potential source for the thick regolith. The observations substantiate existing hypotheses for the evolution and development of deep critical zones. From the results, it has been hypothesized that the bedrock architecture and water channel paths within the CZ together control the regolith thickness.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105547"},"PeriodicalIF":2.2,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spectral decomposition predicts the distribution of steep slope fans in the rift basin of eastern China","authors":"Ling Li ,&nbsp;Zhizhang Wang ,&nbsp;Weifang Wang ,&nbsp;Wentian Fan ,&nbsp;Zhiheng Zhang","doi":"10.1016/j.jappgeo.2024.105543","DOIUrl":"10.1016/j.jappgeo.2024.105543","url":null,"abstract":"<div><div>Deep reservoirs associated with gravity-flows are garnering considerable attention. Predicting reservoirs deposited by nearshore subaqueous fans is challenging and often underreported in seismic sedimentology analysis. Utilizing post-stack seismic attributes is a quick and straightforward method for quantitatively characterizing these reservoirs. However, reservoir prediction deteriorates when dealing with complex sedimentary volumes and intricate tectonic development. Spectral decomposition (SD) offers an alternative approach to optimize the seismic data. The frequency-dependent S-transform (ST) holds great potential in seismic interpretation. SD based on the ST was employed in the seismic sedimentary characterization of steep slope complex fan reservoirs. Three fourth-order sequence stratigraphic boundaries and three complex fans were ideally shown on seismic frequency decomposition profiles. A 20 Hz seismic sedimentology analysis frequency was determined by comparing three spectral decomposition results following the well-seismic reflection analysis. The internal architectures of fan deltas and the individual outlines of nearshore subaqueous fans were more distinguishable in 20-Hz frequency decomposition data than in full-frequency data. The progradation direction of steep slope fans can be better recognized in frequency decomposition profiles compared to full-frequency seismic data. Three factors influence the seismic sedimentary characterization and prediction of steep slope fans when employing SD. The ability of the ST to preserve phase is crucial for improving the imaging quality of the amplitude attribute. Sedimentary mechanisms control the sedimentary features of steep slope fans, impacting the imaging of seismic attributes. While channelized fan deltas can be better identified, unchannelized nearshore subaqueous fan deposits, which exhibit more heterogeneous sedimentary characteristics, present limitations. The unique volcanic evolution is another factor that impacts the image of the root-mean-square (RMS) attribute. Despite demonstrating excellent local adaptability in signal analysis, the S-transform cannot fully compensate for the combined effects of faults and sedimentary heterogeneity in nearshore subaqueous fans.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105543"},"PeriodicalIF":2.2,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An interpretation-based convolution neural network framework for geophysical data fusion and aquifer structure identification","authors":"Zhenjiao Jiang ,&nbsp;Jinxin Wang ,&nbsp;Xuanyi Chen","doi":"10.1016/j.jappgeo.2024.105545","DOIUrl":"10.1016/j.jappgeo.2024.105545","url":null,"abstract":"<div><div>Identification of 3D realistic aquifer structures is essential for predicting physicochemical processes in groundwater systems. However, the characterization of highly heterogeneous aquifers remains challenging because it relies on the effective fusion of multiple geophysical data sources having wide areal coverage, as well as downhole geophysical data featuring high resolution. This study establishes a novel 3D convolutional neural network model to generate aquifer structure from 3D seismic data, constrained by sparse downhole sonic and lithology logs. In the model, the data fusion procedure is designed to follow the logics of conventional manual interpretation of multiple geophysical data, and to address the 3D spatial relationships between geophysical data and lithology. The method is implemented in a typical fluvial aquifer featuring coarse paleovalley sediments (sandstone) embedded in the tight surrounding rocks (claystone), in order to identify channelized sandstone from low-permeability claystone. It is confirmed that the proposed model reliably generates 3D aquifer structures based on seismic amplitudes, downhole sonic and lithology logs. The method is compared to traditional machine learning models that focus on 1D conversion from geophysical attributes to lithology. The results show that the newly-developed model performs more robustly and accurately because the use of 3D convolution allows considering the relationships between seismic amplitude, sonic velocity and lithology in both vertical and horizontal directions. Moreover, the inclusion of sonic logs constraint in the model, following the logics of manual seismic data interpretation, significantly improves the model accuracy. The method can find broad applications for the characterization of subsurface heterogeneity even featuring non-gaussian permeability distribution like the demonstrated fluvial aquifer.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105545"},"PeriodicalIF":2.2,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}