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REVIEW article

Front. Earth Sci.

Sec. Solid Earth Geophysics

Volume 13 - 2025 | doi: 10.3389/feart.2025.1645896

This article is part of the Research TopicGeophysical Electromagnetic Exploration Theory, Technology and ApplicationView all 9 articles

Inverse geo-electromagnetic modeling: A systematic review and bibliometric assessment

Provisionally accepted
  • 1Computer Architecture Department, Universitat Politecnica de Catalunya, Barcelona, Spain
  • 2Universidad Nacional Autonoma de Mexico, Mexico City, Mexico
  • 3Indian Institute of Science Education and Research Pune, Pune, India

The final, formatted version of the article will be published soon.

Inverse electromagnetic (EM) modeling plays a pivotal role in subsurface exploration, enabling the characterization of the Earth's electrical properties for various applications, including resource exploration, environmental monitoring, and geohazard assessment. Despite significant advancements in the field, the EM inverse problem remains inherently challenging due to its ill-posed and nonlinear nature. A diverse range of methodologies, including deterministic, non-deterministic, and machine learning-based (ML-based) approaches, have been proposed to address these challenges. However, there is a lack of a comprehensive synthesis that integrates both the theoretical evolution of these methods and their bibliometric performance. This paper addresses this gap by combining a systematic review of modern computational methodologies with a bibliometric assessment of the scientific literature on inverse EM modeling. The systematic review critically evaluates key computational approaches, examining their theoretical foundations, practical applications, and limitations, while the biblio-metric assessment provides a quantitative assessment of scientific productivity, trends, and contributions from different nations. This integrated perspective offers a unified overview of the field, identifies emerging research directions, and highlights the state-of-the-art in inverse EM modeling. The findings provide valuable insights for researchers, practitioners, and policymakers, guiding future advancements and fostering interdisciplinary collaboration.

Keywords: Forward electromagnetic modeling, inverse electromagnetic modeling, Numerical methods, Bibliometic analysis, Geophysical Exploration

Received: 12 Jun 2025; Accepted: 15 Sep 2025.

Copyright: © 2025 Castillo Reyes, Jiménez-Andrade, Dehiya and Iturrarán-Viveros. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Octavio Castillo Reyes, octavio.castillo@bsc.es
Ursula Iturrarán-Viveros, ursula@ciencias.unam.mx

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