Analysis of some error-causing factors in two-dimensional geoelectrical studies and providing a solution to minimize them by Hosein Moghaddasi, Mohsen Moghaddasi, Ahmad Neyamadpour

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A Review of the Advantages and Limitations of Geophysical Investigations in Landslide Studies by Veronica Pazzi, Stefano Morelli, Riccardo Fanti

“…Since the ‘70s, the international community (mainly geophysicists and lower geologists and geological engineers) has begun to employ, together with other techniques, geophysical methods to characterize and monitor landslides. …”
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High-level radioactive waste repository: How Geology combined with societal principles can lead to public acceptance—the German experiment by Schafmeister, Maria-Theresia

“…As the general consensus is that the rocks of earth crust’s are the best option for a controlled storage, scientists including geologists, geophysicists and hydrogeologists are looking worldwide for safe underground repository sites. …”
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ABOUT THE SOURCE OF THE KURSK MAGNETIC ANOMALY by V.V. Gordienko, V.M. Tarasov

“…The article contains the results of the study of the Kursk magnetic anomaly, which has attracted the attention of many geophysicists for decades, including in the form of field disturbances recorded by the equipment of artificial Earth satellites. …”
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Application of different edge detection methods for faults identification in Anza Basin, Kenya by Gege Li, Qing Chen, Bingqiang Yuan, Xianfeng Tan, Hao Chen, Xiaoyu Huang, Lang Pan

“…However, the traditional potential field boundary identification method has limited ability to detect the boundaries of buried deep geological bodies. Therefore, geophysicists at home and abroad have proposed various new techniques for potential field boundary identification. …”
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Petrophysical Regression regarding Porosity, Permeability, and Water Saturation Driven by Logging-Based Ensemble and Transfer Learnings: A Case Study of Sandy-Mud Reservoirs by Shenghan Zhang, Yufeng Gu, Yinshan Gao, Xinxing Wang, Daoyong Zhang, Liming Zhou

“…Consequently, CRBM-Bayes-LightGBM combined with transfer learning is solidly demonstrated by a stronger capability and an expected robustness on the prediction of porosity, permeability, and water saturation, which then clarify that the proposed predictor can be viewed as a preferential selection when geologists, geophysicists, or petrophysicists need to finalize a characterization of sandy-mud reservoirs.…”
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