Journal of Applied Geophysics最新文献

{"title":"Reconstruction of geophysical logging and intelligent lithology identification of mineralized layer: A case study of the Baolongshan uranium deposit in the Southern Songliao Basin","authors":"Zhimo Zhang ,&nbsp;Zhibing Feng ,&nbsp;Li Jiang ,&nbsp;Xiao Huang ,&nbsp;Bocheng Zhang","doi":"10.1016/j.jappgeo.2025.106012","DOIUrl":"10.1016/j.jappgeo.2025.106012","url":null,"abstract":"<div><div>Geophysical logging serves as a fundamental method in sandstone-type uranium exploration. Due to the large volume of logging data and the complexity of geological interpretation, artificial intelligence (AI) technologies provide efficient solutions for data processing and analysis. While lithological identification approaches in non-mineralized layers are similar to those used in oil, gas, and coal exploration, the mineralized layers present a unique challenge: anomalously high gamma-ray values are observed in some intervals without apparent lithological control, which can lead to misinterpretation. Therefore, accurate lithological classification of mineralized layers is therefore critical for the exploration and development of sandstone-type uranium deposits. This study focuses on the lithology of the mineralized lower Yaojia Formation in the Baolongshan uranium deposit, located in the southern Songliao Basin. A Random Forest regression model was employed to reconstruct anomalous intervals in the natural gamma-ray logging data, and an improved XGBoost model, optimized via Bayesian hyperparameter tuning, was used for lithological classification. Quantitative evaluations confirm the reliability of the reconstructed natural gamma-ray data, showing negligible differences in average values compared to non-anomalous data. Moreover, in the filled intervals where original gamma-ray values were excluded due to mineralization effects and subsequently reconstructed using the Random Forest model, the reconstructed gamma-ray curves not only exhibit morphological similarity to spontaneous potential curves but also show a mirror-image relationship with apparent resistivity and three-lateral resistivity curves, thereby further validating the reconstruction. Lithological classification accuracies for the mineralized layer across the three boreholes are 97.5 %, 96.5 %, and 98.6 %, with an average accuracy of 97.5 %. These results outperform those obtained from the original data, which yielded accuracies of 95.5 %, 96.0 %, and 97.3 %, with an average accuracy of 96.3 %. The AI-driven precise identification of lithology in mineralized layers significantly enhances the efficiency of sandstone-type uranium exploration and provides robust geological evidence for the evaluation and development of uranium resources.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"244 ","pages":"Article 106012"},"PeriodicalIF":2.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145467629","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":"Mapping hydrothermal alteration zones of Gebel MU'TIQ area using ASTER and aeromagnetic data in central eastern desert, Egypt","authors":"Osama Elghrabawy","doi":"10.1016/j.jappgeo.2025.106027","DOIUrl":"10.1016/j.jappgeo.2025.106027","url":null,"abstract":"<div><div>This study integrates ASTER VNIR–SWIR imagery with aeromagnetic data for mineral exploration in the Gebel MU'TIQ area, Central Eastern Desert of Egypt, within the Arabian-Nubian Shield. Lithological discrimination was enhanced using ASTER image-processing techniques, Optimum Index Factor (OIF), Minimum Noise Fraction (MNF), and Principal Component Analysis (PCA), enabling clear mapping of rock units such as amphibolitic schist, felsitic mylonite, sericite/muscovite schist, schist groups, biotite-hornblende gneiss, and granitoid intrusions. Hydrothermal alteration zones, including argillic, phyllic, propylitic, and ferrugenous assemblages, were identified through Feature-Oriented Principal Component Analysis (FPCA) and Constrained Energy Minimization (CEM), showing strong spatial association with NW-SE shear systems and granitoid contacts. Circular Feature Transform (CET) analysis delineated porphyry-style mineralization, particularly in the northeastern, central, and southwestern sectors, coinciding with the Arieki granitoid, Abu Ziran granite, and Um Ba'anib gneiss. Structural analysis, combining surface lineaments (ASTER PC1) and subsurface magnetic lineaments, emphasized the structural control on mineralization. The integrated exploration map highlights first-priority targets along the MU'TIQ shear zone, validated by the spatial coincidence with known Cu, Fe, Cr, Ta<img>Nb, talc, and asbestos occurrences. These results confirm that combining ASTER-based lithological and alteration mapping with aeromagnetic analysis provides a cost-effective reconnaissance tool for detecting structurally hosted mineralized zones.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"244 ","pages":"Article 106027"},"PeriodicalIF":2.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571702","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":"Statistical rock physics inversion for assessing source rock properties from seismic signatures: An application to the Canning Basin, Australia","authors":"Jiayuan Huang ,&nbsp;Allegra Hosford Scheirer ,&nbsp;Tapan Mukerji","doi":"10.1016/j.jappgeo.2025.106026","DOIUrl":"10.1016/j.jappgeo.2025.106026","url":null,"abstract":"<div><div>Quantifying source rock properties is essential for subsurface characterization but remains a high-dimensional and nonlinear inverse problem. A statistical rock physics inversion workflow is implemented to efficiently estimate source rock properties from seismic and well-log data and quantify associated uncertainty. A thermal-maturation-dependent rock physics model is calibrated through Monte Carlo simulation to link source rock parameters with elastic properties. Weighted Approximate Bayesian Computation (ABC) integrates prior petrophysical knowledge, model calibration errors, and measured elastic data to estimate posterior distributions of source rock properties. The workflow is first validated through well-log inversion, showing posterior updates in source rock properties. Then the workflow is applied to seismic inversion after outlier detection using a robust Mahalanobis distance method, generating spatially coherent 2D distributions of rock properties in the Goldwyer III of the Canning Basin, consistent with well-log observations. Sensitivity analysis identifies porosity, kerogen, and illite as the most influential parameters. The workflow provides a robust, uncertainty-aware framework for source-rock property estimation.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"244 ","pages":"Article 106026"},"PeriodicalIF":2.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571701","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":"Image subsurface karst in coastal areas using gravity gradient method: A case study in Guangxi, China","authors":"Nuoya Zhang ,&nbsp;Huaifeng Sun ,&nbsp;Zhiyong Zhang ,&nbsp;Shangbin Liu ,&nbsp;QiuyanFan","doi":"10.1016/j.jappgeo.2025.105990","DOIUrl":"10.1016/j.jappgeo.2025.105990","url":null,"abstract":"<div><div>Water inrush from subsurface karst causes serious issues to limestone mining engineering in coastal areas, such as hindering mining operations and damaging the surrounding hydrogeological environment. Identification of the subsurface karst channels is an important and urgent task to ensure the safety of mining engineering. Electromagnetic exploration is generally ineffective in coastal areas due to the strong natural shielding effect of seawater. However, there is a discernible density anomaly between the water-filled karst channel and the surrounding rock. Therefore, gravity exploration is capable of karst channel exploration. Compared with conventional gravity data sets, gravity gradient data sets offer higher resolution and can reveal more details of subsurface density variation. In this study, we applied the gravity gradient method to image subsurface karst channels of large-opening limestone mines operated by China Resources Cement (Hepu) in Guangxi Province, China, which have suffered from water inrush problems for years. We successfully predicted five potential karst water-connected channels and the associated karst water inrush risk, which is in good agreement with the known geological evidence and drilling data. Our results provided reliable geophysical data for mine water inrush treatment. This study highlights the strong potential and advantages of the gravity gradient method for imaging subsurface karst in coastal areas and demonstrates its value in guiding grouting treatment strategies in mining engineering.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"244 ","pages":"Article 105990"},"PeriodicalIF":2.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145419906","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":"Application of passive surface-wave imaging for porphyrite iron deposit exploration: A case study of Nihe iron mine, Luzong ore district, Eastern China","authors":"Anguo Chen ,&nbsp;Yingwei Yan ,&nbsp;Shu Zhang ,&nbsp;Yuanzhu Liang ,&nbsp;Xiaofei Chen ,&nbsp;Jing Li ,&nbsp;Ruizhe Sun ,&nbsp;Shichuan Yuan ,&nbsp;Hanbing Ai","doi":"10.1016/j.jappgeo.2025.106021","DOIUrl":"10.1016/j.jappgeo.2025.106021","url":null,"abstract":"<div><div>The application of passive surface-wave imaging (PSWI) in mineral prospecting remains limited, as the data acquirement process is often compromised by non-stationary noise originating from active mining production. In addition, the ore deposits are often hosted in hard rock environments, which is usually highly complex and heterogeneous compared with the sedimentary rock environments, these sites are indeed a challenge for current PSWI methods. As an experimental study, this paper presents a case study of mineral exploration using PSWI. Specifically, the S-wave velocity imaging of Nihe iron deposit, Luzong ore district, eastern China is realized using the PSWI with a linear array, and the preconditioned steepest-descent (PSD) is selected as the inversion algorithm. The obtained S-wave velocity tomogram is in good agreement with the geological materials of the survey area, and two known iron orebodies are also reflected, clearly. Furthermore, the extra prospecting target is also identified from the tomogram. The imaging result is also evaluated in the data domain, consisting of the fittings of dispersion data and sensitivity kernels, and the excellent convergence of the PSD algorithm has been confirmed. The S-wave velocity tomogram is also compared with those results of other geophysical methods to further show the advantages of the PSWI in mineral exploration. The comparison results indicate that the PSWI is highly suitable for detailed resource investigation during the mineral exploration or mining process. Finally, the stability of the inversion system and subarray division are also analyzed in the discussion part.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"244 ","pages":"Article 106021"},"PeriodicalIF":2.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145520244","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":"Method for predicting the microwave heating sensitivity of hard rocks: Application to microwave-mechanical excavation and microwave stress release in tunnels","authors":"Shiping Li,&nbsp;Xia-ting Feng,&nbsp;Chengxiang Yang,&nbsp;Feng Lin,&nbsp;Xiangxin Su,&nbsp;Tianyang Tong,&nbsp;Jiuyu Zhang","doi":"10.1016/j.jappgeo.2025.105995","DOIUrl":"10.1016/j.jappgeo.2025.105995","url":null,"abstract":"<div><div>Accurate evaluation of the microwave heating sensitivity of hard rock in deep engineering, and its correlation with dielectric properties is crucial for predicting the microwave-mechanical rock breaking efficiency and assessing microwave-induced stress release effectiveness. Based on coaxial line transmission/reflection dielectric property test equipment, the dielectric properties of synthetic rocks made from different rock powders are tested, and the reliability of this method is verified. The dielectric properties and the microwave average heating rate of different rock minerals are tested, which provides the basis for the preparation of synthetic rocks. Taking engineering granite as an example, three main rock mineral powders are mixed thoroughly in different proportions, compressed into synthetic granite under 400 MPa to test their complex dielectric constant. A prediction model method for the dielectric properties of synthetic granite based on the mineral content is established. The research results indicate that the preparation pressure is positively correlated with the loss tangent of the sample and negatively correlated with the microwave penetration depth (<em>D</em>_<em>p</em>). The greater the <em>D</em>_<em>p</em> is, the smaller the loss tangent and the lower the microwave average heating rate of rocks. The classification standards for rock microwave heating sensitivity are discussed (microwave frequency of 2.45 GHz): strong sensitivity (<em>D</em>_<em>p</em> &lt; 4 cm), moderate sensitivity (4 cm ≤ <em>D</em>_<em>p</em> ≤ 8 cm), and weak sensitivity (<em>D</em>_<em>p</em> &gt; 8 cm). In engineering applications, the method for predicting rock microwave heating sensitivity provides a basis for selecting microwave parameters in different hard rock excavation areas or stress release areas.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"244 ","pages":"Article 105995"},"PeriodicalIF":2.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145467564","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":"Seismic local event slopes estimation using cycle generative adversarial network based on perceptual loss and self attention mechanism","authors":"Chao Li,&nbsp;Chenghan Zhang,&nbsp;Xiaotao Wen,&nbsp;Xingye Liu,&nbsp;Fen Lyu,&nbsp;Shaohuan Zu","doi":"10.1016/j.jappgeo.2025.106005","DOIUrl":"10.1016/j.jappgeo.2025.106005","url":null,"abstract":"<div><div>Accurate estimation of local event slopes is critical for seismic data processing. This study introduces an advanced deep learning framework for robust seismic local event slope estimation under challenging acquisition conditions. The proposed method integrates perceptual loss modules and self-attention mechanisms within a cycle-consistent adversarial network architecture. This approach operates without requiring precisely paired seismic-slope training data by leveraging bidirectional adversarial learning with cycle consistency loss constraints. The perceptual loss component preserves essential geological structural features through hierarchical feature space optimization, while self-attention mechanisms enable effective modeling of long-range dependencies in irregularly sampled seismic data. Comprehensive evaluation demonstrates the framework’s superior performance compared to conventional plane-wave destruction methods, particularly when processing seismic data with substantial noise contamination and missing traces. Validation across synthetic benchmarks and field datasets confirms enhanced slope estimation accuracy and improved structural continuity. The method’s ability to extract transferable seismic representations further benefits downstream processing tasks including data reconstruction and noise attenuation.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"244 ","pages":"Article 106005"},"PeriodicalIF":2.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145467630","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":"Near-surface geothermal reservoir exploration by multichannel analysis of passive surface waves using urban traffic noise in Shanxi","authors":"Ling Ning ,&nbsp;Tianyu Dai ,&nbsp;Guoshu Huang ,&nbsp;Liang Liu ,&nbsp;Hanbing Ai ,&nbsp;Chaoqiang Xi","doi":"10.1016/j.jappgeo.2025.106032","DOIUrl":"10.1016/j.jappgeo.2025.106032","url":null,"abstract":"<div><div>Geothermal resource exploration is a key driver of urbanization and economic transformation in northern and northwestern China. Traditional geophysical methods (e.g., active-source seismic and electrical resistivity tomography), however, often struggle with high costs, limited spatial coverage, and low resolution in deeper layers under complex noise conditions, hindering accurate subsurface characterization. To address these problems, we applied the multichannel analysis of passive surface waves (MAPS) to investigate local-scale geothermal reservoirs in central Shanxi Province, northern China. Two pseudo-linear arrays were deployed to record ambient seismic noise. Using less than one day of noise data, we extracted a subset of the total station pairs to perform seismic interferometry and dispersion measurements. Beamforming outputs revealed that the azimuth of the ambient noise sources was mainly aligned with the linear array direction, resulting in cross-correlation functions with good temporal symmetry. Coherent surface waves in the frequency range of 0.5 to 3 Hz were successfully retrieved, and robust phase-velocity dispersion curves were obtained from virtual shot gathers using multichannel analysis of surface waves. The consistency of the dispersion curves with the results derived from both pseudo-linear-array analysis of passive surface waves (PLAS) and the spatial autocorrelation (SPAC) methods confirms that they are not affected by the off-line noise sources. These curves were inverted using a sine-cosine algorithm to obtain shear (<em>S</em>)-wave velocity profiles, which showed strong agreement with the resistivity profiles from electromagnetic inversion. This case study demonstrates the value of using integrated geophysical methods in geothermal exploration. Combining passive surface-wave with electromagnetic techniques, we can overcome the limitations of individual methods, improving both the resolution and reliability of subsurface imaging. Such integration enables more accurate assessments of geothermal systems and supports the sustainable use of geothermal energy in geologically complex settings.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"244 ","pages":"Article 106032"},"PeriodicalIF":2.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571653","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":"Diffraction wave separation and imaging by encoder–decoder network embedded Transformer","authors":"Ming Ma ,&nbsp;Rui Zhang ,&nbsp;Feng Ma ,&nbsp;Qianzong Bao","doi":"10.1016/j.jappgeo.2025.106023","DOIUrl":"10.1016/j.jappgeo.2025.106023","url":null,"abstract":"<div><div>High-precision detection of geological anomalies can be achieved through diffractions generated when seismic or electromagnetic waves propagate in subsurface discontinuities, e.g., caves and fractures. However, capturing the diffracted portions of the full wavefield from acquired seismic or ground penetrating radar (GPR) data is challenging due to the strong interference and waveform blending. Furthermore, compared with reflections, diffractions possess low magnitudes and complex shapes. The aforementioned factors hinder difficulty in deploying robust diffraction extraction and imaging across various data domains. To enhance the accuracy of diffraction imaging and simplify the processing steps, we have built a new intricate mapping from full wavefield in dip-angle domain common image gather (Dip-ADCIG) to unique migrated diffractions with deep learning (DL) technique. By virtue of the encoder–decoder framework, characteristics of diffracted waves can be depicted, which are applied to classify disordered waveforms with improved efficiency. Self-attention computation in the improved backbone Swin Transformer V2 ensures the coincident fidelity between input and prediction result. Apart from the utilization of optimally configured encoder panel, mode of feature maps concatenating is modified in decoder module so as to obtain the diffraction imaging of small-scale heterogeneities. Through a stable training with a flood of data for the diverse designed geological models, the new workflow can provide a high-resolution depth-domain imaging of diffractions even with poor quality input gathers. Numerical and field data tests verify the high performance and validity of our proposed method.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"244 ","pages":"Article 106023"},"PeriodicalIF":2.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145520241","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":"Geophysical characterization of a sand deposit in a small-scale mining in the central east region of São Paulo State, Brazil","authors":"Jorge Luís Porsani ,&nbsp;Victor Hugo Hott Costa ,&nbsp;Nathália de Souza Penna ,&nbsp;Rodrigo Corrêa Rangel ,&nbsp;Marcelo Cesar Stangari ,&nbsp;Gustavo Isnard Jarussi ,&nbsp;Gabriel Alencar Silva Almeida Dantas ,&nbsp;Rafael Josimar Araos Huaman","doi":"10.1016/j.jappgeo.2025.105986","DOIUrl":"10.1016/j.jappgeo.2025.105986","url":null,"abstract":"<div><div>This research employs Electrical Resistivity Tomography (ERT), Ground-Penetrating Radar (GPR), and Transient Electromagnetic (TEM) to characterize a sand deposit located in a small-scale mining (SSM) in Leme, São Paulo State, Brazil. The region has a high demand for sand, particularly in the construction industry. The applied geophysical methods provide complementary information. ERT and GPR data enable the investigation of shallow subsurface layers (up to ∼30 m), whereas TEM is employed to investigate deeper structures, reaching depths of up to ∼350 m. The integrated geophysical results allowed the identification of a geoelectrical stratigraphy down to a few hundred meters, characterizing both unsaturated and saturated sand layers. A 3D model of the sand deposit was built based on the geophysical results and lithological information from boreholes in the study region. This model includes the deposit's geometry, mass, and volume, which are crucial information for an economic assessment of the SSM. Moreover, our results demonstrate how near-surface geophysical methods can be employed to help with a sustainable exploration of a sand deposit in an SSM.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"244 ","pages":"Article 105986"},"PeriodicalIF":2.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145366112","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}