Geophysical Potential Fields: Geological and Environmental Applications, Volume Two, investigates the similarities and differences of potential geophysical fields, including gravity, magnetics, temperature, resistivity and self-potential, along with the influence of noise on these fields. As part of the Computational Geophysics series, this volume provides computational examples and methods for effectively solving geophysical problems in a full cycle manner. Including both quantitative and qualitative analysis, the book offers different filtering and transformation procedures, integrated analysis, and special interpretation methodologies, also presenting a developed 3D algorithm for combined modeling of gravity and magnetic fields in complex environments.

The book also includes applications of the unified potential field system, such as studying deep structure, searching hydrocarbon and ore deposits, localizing buried water horizons and rockslide areas, tectono-structural mapping of water basins, and classifying archaeological targets. It is an ideal and unique resource for geophysicists, exploration geologists, archaeologists and environmental scientists.

Author Biography

Lev Eppelbaum is author of about 390 publications, including 9 books, 13 chapters in books and about 150 articles. He is currently Associate Professor at the Department of Earth Sciences at Tel Aviv University. Previously, he was a Senior Researcher at the Gravity and Magnetics Dept. at the All-Union Geophysical Institute in Azerbaijan. He is recipient of a few awards including Christian Huygens medal of the European Geosciences Union (2019). He is currently Associate Editor in the EGU Journal “Geophysical Instrumentation, Methods and Data Systems and member of Editorial Board in several International Journals. His research interests include geophysical potential field comprehensive analysis, tectonics and geodynamic reconstructions with application of paleomagnetic data, environmental and archaeological geophysics, and integrated geophysical-geological data analysis.

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