Journal of Applied Geophysics最新文献_第4页

Detection of archaeological structure on the slope ground using geophysical methods: The case of the Castle of Canossa 利用地球物理方法探测斜坡地面上的考古结构：卡诺萨城堡案例

IF 2.2 3区地球科学

Journal of Applied Geophysics Pub Date : 2024-09-12 DOI: 10.1016/j.jappgeo.2024.105521

{"title":"Detection of archaeological structure on the slope ground using geophysical methods: The case of the Castle of Canossa","authors":"","doi":"10.1016/j.jappgeo.2024.105521","DOIUrl":"10.1016/j.jappgeo.2024.105521","url":null,"abstract":"<div><p>Canossa Castle is located in the municipality of Canossa 18 km South of Reggio Emilia (North Italy). It was constructed in 940 by Adalberto Atto, son of Sigifredo of Lucca. Lombard chieftains needed this strategic hill to defend their lands against intrusions of other barbarian tribes. Subsequent improvements made the stronghold one of the best-defended castles in the country. Canossa Castle became particularly famous as a site of reconciliation between King Henry IV and Roman Pope Gregory VII during the Investiture Controversy in 1077.</p><p>To redevelop the area and create an easy tourist route, the Superintendence of Archaeology, Fine Arts and Landscape for the Metropolitan City of Bologna and the Provinces of Modena, Reggio Emilia and Ferrara planned excavations in the area close to the Castle. To get precise information on where to carry out excavations geophysical surveys were undertaken in the spring of 2021. The castle stands on a rock with a steep slope and dense vegetation and this makes it very difficult to carry out geophysical prospecting. This guided the choice of geophysical methodologies to be used. For this reason, electrical resistivity tomography was used along the steep slope, while in the narrow flatter area, the ground penetrating radar methodology was used. The results demonstrate the effectiveness of the chosen geophysical methodologies.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142242660","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}

引用次数: 0

Optimal acquisition time estimation method for CSEM with high-order pseudo-random signal 采用高阶伪随机信号的 CSEM 最佳采集时间估算方法

IF 2.2 3区地球科学

Journal of Applied Geophysics Pub Date : 2024-09-12 DOI: 10.1016/j.jappgeo.2024.105517

{"title":"Optimal acquisition time estimation method for CSEM with high-order pseudo-random signal","authors":"","doi":"10.1016/j.jappgeo.2024.105517","DOIUrl":"10.1016/j.jappgeo.2024.105517","url":null,"abstract":"<div><p>High-order pseudo-random signal is gradually being applied in controlled-source electromagnetic (CSEM) exploration. In contrast to the conventional single-frequency sweep mode, the high-order pseudo-random signal enables simultaneous transmission of multiple frequencies. However, estimating a fixed acquisition time based on observed noise levels often results in poor adaptability for high-order pseudo-random signal, which only require reception of one set of waveform. In this study, we presented an estimation method for acquisition time for CSEM with high-order pseudo-random signal using an improved logistic function. The improved logistic function was proposed to introduce a time-decay factor into the governing equation for the first time. By considering the transformation rule of noise statistical characteristics with time, the specific parameters of the function have been determined to better describe the dynamic evolution process of the signal quality. The effective frequencies were extracted at various acquisition times based on the noise evaluation number, and the resulting quantity of effective frequencies was used as the fitting target. Guidance for the fieldwork was determined based on the average time of the saturation period, in accordance with the properties of the function. The reliability of the improved logistic function was validated through a transmission current data simulation. The proposed method was demonstrated through the measured data from both strong and weak interference areas.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272462","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}

引用次数: 0

Effects of rock pore and micromorphology on electromagnetic radiation characteristics 岩石孔隙和微观形态对电磁辐射特性的影响

IF 2.2 3区地球科学

Journal of Applied Geophysics Pub Date : 2024-09-11 DOI: 10.1016/j.jappgeo.2024.105518

{"title":"Effects of rock pore and micromorphology on electromagnetic radiation characteristics","authors":"","doi":"10.1016/j.jappgeo.2024.105518","DOIUrl":"10.1016/j.jappgeo.2024.105518","url":null,"abstract":"<div><p>Electromagnetic radiation (EMR) is a crucial tool for monitoring and early warning of underground engineering disasters. Investigating the inherent pore characteristics of rocks is essential for a comprehensive understanding of the EMR phenomenon. The EMR was monitored during various types of rock splitting failures. The pore structure and micromorphology of rocks are studied using quantitative methods such as mercury intrusion porosimetry, fractal analysis, and the Gray Level Co-occurrence Matrix (GLCM). Results indicate that the fractal dimension of red sandstone is significantly lower than the other three rocks. The fractal complexity increases sequentially from red sandstone to marble, granite, and limestone. As the fractal dimension decreases, the signal waveform characteristics of the four rocks become more complex before the main fracture, with a significant increase in signals during the compaction and elasticity stages. Higher fractal dimensions lead to a shift in energy and count from elasticity stage to the post-peak stage. The main fracture amplitudes of the four rocks generally exhibited a consistent pattern, following the sequence of granite > marble > limestone > red sandstone. The main fracture amplitude decreases with increasing complexity of the rock's pore micromorphology. Rock pore characteristics affect frequency domain characteristics by influencing rock strength and crack expansion. An increase in the average pore diameter tends to decrease both the main and center frequencies.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142242662","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}

引用次数: 0

Electrical resistivity imaging of crude oil contaminant in coastal soils – A laboratory sandbox study 沿海土壤中原油污染物的电阻率成像--实验室沙盘研究

IF 2.2 3区地球科学

Journal of Applied Geophysics Pub Date : 2024-09-11 DOI: 10.1016/j.jappgeo.2024.105516

{"title":"Electrical resistivity imaging of crude oil contaminant in coastal soils – A laboratory sandbox study","authors":"","doi":"10.1016/j.jappgeo.2024.105516","DOIUrl":"10.1016/j.jappgeo.2024.105516","url":null,"abstract":"<div><p>Characterizing the subsurface distribution of crude oil after a spill in a coastal environment is challenging due to variations in the soil and fluid properties. In situ sampling is limited in capturing the lateral and vertical migration of the crude oil within the vadose and saturated zones. This study presents a laboratory sandbox framework used to assess the effectiveness of electrical resistivity imaging for investigating the spatiotemporal distribution of crude oil in coastal sandy soils. A sandbox with dimensions L = 240 cm, W = 60 cm, and H = 60 cm was constructed using a 10 mm plexiglass and filled to a 40 cm height with 2 mm medium to fine-grained sand. At each stage of the experiment, 20 kg of sand was mixed with 1 l of water to create moist sand, after which the mixture was flushed over 12 h to remove suspended fine particles. Both saturated and unsaturated conditions were simulated by setting the water table at 10 cm and draining a fully saturated system overnight. Two liters of crude oil were spilled and monitored for 30 h. A surface array of 98 electrodes, with a unit electrode spacing of 2 cm, was installed along two transects 12 cm apart. Resistivity measurements were collected using a dipole-dipole array before, during, and after the simulated crude oil spill. The time-lapse electrical resistivity results revealed an initial gravity-induced vertical migration under both saturated and unsaturated conditions; over time, lateral migration of crude oil became apparent. In the saturated zone, there was a noticeable reduction in the percentage difference in resistivity from 700 % to 400 % after 24 h, depicting a spatial and temporal redistribution of the crude oil attributed to variation in pore geometry. This highlights the sensitivity of electrical resistivity measurements to subtle but measurable anisotropy in the distribution of soil pores. Overall, electrical resistivity proved successful in imaging the non-ideal behavior of crude oil pollutants and the associated spatial changes in the pore-size distribution of subsurface sediments.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142242659","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}

引用次数: 0

Optimized gradient boosting models and reliability analysis for rock stiffness C13 岩石刚度 C13 的优化梯度提升模型和可靠性分析

IF 2.2 3区地球科学

Journal of Applied Geophysics Pub Date : 2024-09-11 DOI: 10.1016/j.jappgeo.2024.105519

{"title":"Optimized gradient boosting models and reliability analysis for rock stiffness C13","authors":"","doi":"10.1016/j.jappgeo.2024.105519","DOIUrl":"10.1016/j.jappgeo.2024.105519","url":null,"abstract":"<div><p>The Extreme gradient boosting algorithm XGBoost has been confirmed to be an accurate method for predicting rock stiffnesses and anisotropic parameters from basic input features such as rock porosity, density, vertical compression stress, pore pressure and burial depth (Nguyen-Sy, T., To, Q.D., Vu, M.N., Nguyen, T.D. and Nguyen, T.T., 2020. Study the elastic properties and the anisotropy of rocks using different machine learning methods. Geophysical Prospecting, 68(8), 2557–2578). This study has the following contributions: reducing the R2-error score (that is, 1-R2) by 35 %, RMSE by 21 % and MAE by 16 % comparing to the previous study by considering an advanced CatXG hybrid boosting model in combination with the optimizer Optuna for predicting <span><math><msub><mi>C</mi><mn>13</mn></msub></math></span> (the most difficult stiffness to accurately predict); 2-conduct a reliability analysis for the predicted stiffness <span><math><msub><mi>C</mi><mn>13</mn></msub></math></span> with respect to the randomness of the input features. We also discuss the use of <span><math><msub><mi>C</mi><mn>11</mn></msub></math></span> or <span><math><msub><mi>C</mi><mn>33</mn></msub></math></span> as additional input features for accurately predicting <span><math><msub><mi>C</mi><mn>13</mn></msub></math></span> as well as the prediction of the related anisotropic parameter <span><math><mi>δ</mi></math></span>. This significant improvement of predicted stiffness <span><math><msub><mi>C</mi><mn>13</mn></msub></math></span> is extremely important because it encourages petrophysical engineers to use machine learning for predicting the elastic stiffnesses of rocks.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142242658","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}

引用次数: 0

Construction and experimental verification of wave velocity model for source location in goaf overlying rock strata 用于上覆岩层鹅卵石源定位的波速模型构建与实验验证

IF 2.2 3区地球科学

Journal of Applied Geophysics Pub Date : 2024-09-10 DOI: 10.1016/j.jappgeo.2024.105515

{"title":"Construction and experimental verification of wave velocity model for source location in goaf overlying rock strata","authors":"","doi":"10.1016/j.jappgeo.2024.105515","DOIUrl":"10.1016/j.jappgeo.2024.105515","url":null,"abstract":"<div><p>The geological structure of the goaf overlying rock is complex, a consequence of coal mining that has modified the original stratified structure of the sedimentary strata. To enhance the accuracy of microseismic source location in such intricate geological formations, a wave velocity model for the “three zones” goaf was constructed based on natural divisions within the strata using Snell's law and assuming a homogeneous medium. The model took into account the effects of rock deformation and fracture development, enabling the derivation of formulas for microseismic wave propagation path and travel time calculation. Additionally, the concept of equivalent wave velocity was defined. An indoor simulation test using similar materials was conducted to establish a geological model of the goaf. By comparing the errors between the theoretical and measured values of equivalent wave velocity, assessing the locating effects before and after implementing the wave velocity model of the goaf, and verifying the feasibility of the model, it was demonstrated that establishing a wave velocity model based on the characteristics of the strata structure was crucial for improving the accuracy of the microseismic source location. Notably, as the propagation path of microseismic waves in the goaf increased, the equivalent wave velocity decreased. The wave velocity structure in the goaf exhibited nonuniformity, with the relative error between the theoretical and measured values of equivalent wave velocity being limited to 10 %. The incorporation of this established wave velocity model into the location method resulted in a substantial 58.57 % increase in locating accuracy.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229158","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}

引用次数: 0

A model integration approach for stratigraphic boundary delineation based on local data augmentation 基于本地数据增强的地层边界划分模型集成方法

IF 2.2 3区地球科学

Journal of Applied Geophysics Pub Date : 2024-09-10 DOI: 10.1016/j.jappgeo.2024.105514

{"title":"A model integration approach for stratigraphic boundary delineation based on local data augmentation","authors":"","doi":"10.1016/j.jappgeo.2024.105514","DOIUrl":"10.1016/j.jappgeo.2024.105514","url":null,"abstract":"<div><p>Identification of stratigraphic boundaries is a fundamental task in the seismic interpretation of oil and gas reservoir locations. When employing deep learning techniques to interpret stratigraphic boundaries, insufficient training data and sample imbalances are common challenges affecting model training. In regions with intricate geological structural changes, conventional deep-learning segmentation algorithms, such as U-Net often struggle to accurately capture the features of complex local structures. To address these limitations, we propose a model integration approach that incorporates global and local uneven-type stratigraphic data augmentation to enhance the accuracy of stratigraphic boundary identification in uneven-type regions. To address the problems of class imbalance and insufficient complex variation samples, we adopted a strategy of separately training global and local data and integrating predictions, thereby handling the disparity between uneven-type and flat-type stratigraphic data during model training. By testing the Netherlands F3 dataset with sparsely labeled profiles, it was demonstrated that the proposed method can effectively improve the delineation accuracy of stratigraphic boundaries compared to the benchmark U-Net model.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169017","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}

引用次数: 0

A comprehensive review of deep learning techniques for salt dome segmentation in seismic images 地震图像中盐丘分割的深度学习技术综述

IF 2.2 3区地球科学

Journal of Applied Geophysics Pub Date : 2024-09-10 DOI: 10.1016/j.jappgeo.2024.105504

{"title":"A comprehensive review of deep learning techniques for salt dome segmentation in seismic images","authors":"","doi":"10.1016/j.jappgeo.2024.105504","DOIUrl":"10.1016/j.jappgeo.2024.105504","url":null,"abstract":"<div><p>Salt dome detection in seismic images is a critical aspect of hydrocarbon exploration and production. Salt domes are subsurface structures formed from the accumulation of salt deposits and can trap oil and gas reservoirs. Seismic imaging techniques are used to visualize the subsurface structures and identify the presence of salt domes. Historically, the process of detecting salt domes in seismic images was done manually, which was time-consuming and required the input of domain experts. However, in recent years, automated methods using seismic attributes and machine learning algorithms have been developed to improve the efficiency of salt dome detection. Deep learning-based methods have shown promising results in salt body segmentation, and several techniques have been proposed in recent years. This review examines recent deep-learning architectures for salt body segmentation in seismic images, offering a concise overview of the various models proposed in the literature. It delves into established benchmark datasets, highlighting potential limitations and emphasizing the importance of data quality for robust models. It explores performance evaluation metrics used in the literature to capture a more comprehensive picture of segmentation performance. This paper identifies several promising areas for further research and development opportunities to refine and enhance the current state-of-the-art salt body segmentation in seismic images. This comprehensive analysis provides a valuable roadmap for researchers and practitioners interested in understanding how deep learning can be utilized for salt body classification in seismic exploration.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142169167","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}

引用次数: 0

Application of machine learning methods for earthquake detection from high-density temporary observation seismic records on a volcanic island 应用机器学习方法从火山岛高密度临时观测地震记录中探测地震

IF 2.2 3区地球科学

Journal of Applied Geophysics Pub Date : 2024-09-07 DOI: 10.1016/j.jappgeo.2024.105503

{"title":"Application of machine learning methods for earthquake detection from high-density temporary observation seismic records on a volcanic island","authors":"","doi":"10.1016/j.jappgeo.2024.105503","DOIUrl":"10.1016/j.jappgeo.2024.105503","url":null,"abstract":"<div><p>We applied two machine learning models to detect earthquakes from records observed with seismometers temporarily installed on a volcanic island. The two models are based on different principles: one regards seismic waveforms as images, using a convolutional neural network (CNN) to determine the first arrival times of P-waves, S-waves. The other model regards seismic waveforms as series data. The model processes seismic waveforms as data in a specific order of noise, P-wave, and S-wave, similar to natural language.</p><p>The purpose of this study is to present the results of using machine learning first arrival times identification models with two principles for noisy seismic waveforms, caused by sea waves and strong winds in volcanic islands, and to evaluate the effectiveness of machine learning models for noisy observation records.</p><p>We created a Confusion Matrix using first arrival times determined by an expert and evaluated the detection performance of these two models using some metrics of the matrix. Additionally, we assessed accuracy of the model-identified first arrival times by generating a frequency distribution of the difference from the expert's detecting time.</p><p>The study discovered that the model treating data as series had superior detection ability for noisy data compared to the one treating data as images and the accuracy of the first arrival time detection was also better for the series data model too.</p><p>We compared the results obtained on this island with those obtained at the permanent station, which is considered to have less noise interference, described in <span><span>Mousavi et al., 2020</span></span>. It was found that the difference in detection ability between the two models is slight for data obtained at permanent stations with low noise interference, but that the difference in detection ability between the algorithms of the two models is significant in noisy environments.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229159","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}

引用次数: 0

Identification and estimation of the subsurface anisotropy from the 2D electrical resistivity tomography surveys 从二维电阻率层析成像测量中识别和估算地下各向异性

IF 2.2 3区地球科学

Journal of Applied Geophysics Pub Date : 2024-09-06 DOI: 10.1016/j.jappgeo.2024.105505

{"title":"Identification and estimation of the subsurface anisotropy from the 2D electrical resistivity tomography surveys","authors":"","doi":"10.1016/j.jappgeo.2024.105505","DOIUrl":"10.1016/j.jappgeo.2024.105505","url":null,"abstract":"<div><p>This research was dedicated to examining regions rich in schist rock near the Singhbhum shear zone in Ghatshila, Jharkhand. The aim was to detect schist rocks that were sheared, fractured, and highly foliated in both shallow and deeper layers. Electrical resistivity tomography (ERT) measurements were conducted using a 2 × 21 electrode configuration, with nine profiles covering inter-electrode spacings ranging from 3 m to 10 m. A recently developed software called Anisotropic DC resistivity Forward and Inverse (ADCFI) was employed to conduct 2D isotropic and anisotropic inversion of the collected data. The 2D interpreted sections along the profiles indicated non-continuous resistivity values at their intersections. Furthermore, areas demonstrating irregular resistivity values showcased anisotropy coefficients exceeding unity, indicating significant anisotropy in these particular zones. The irregular resistivity patterns additionally provided further evidence for the existence of substantial anisotropic behavior within the region.</p><p>The outcomes of the 2D anisotropic inversion conducted in Ghatshila unveiled significant anisotropy coefficients beyond a depth of 20 m. This depth correlated with the presence of layers containing chalcopyrite, suggesting stratified deposition originating from a volcanogenic setting. Furthermore, the existence of schist rocks in shallow borehole depths contributed to the observed anisotropic tendencies. Notably, regions with heightened anisotropy demonstrated thicker layers in the isotropic section compared to the anisotropic section across all profiles. Anisotropy coefficient values derived from areas abundant in schist rock in Ghatshila were approximately 2.00. This substantial anisotropy was attributed to the inherent foliation and schistosity of the dominant rock type, namely schist.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142242664","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}

引用次数: 0