<p>Joint inversion of geophysical data offers a robust means to improve the resolution and reliability of subsurface models, particularly when integrating methods with complementary depth sensitivities. This study presents a 1D joint inversion methodology for combining Transient Electromagnetic (TEM) and Radiomagnetotelluric (RMT) data, two complementary electromagnetic methods that provide insights into different depth ranges of the subsurface. The approach is validated through synthetic modeling and applied to a landfill site to demonstrate its practical utility. Results confirm that joint inversion significantly reduces model ambiguity and enhances the delineation of key structures, including the extent of the waste body. These findings show the methodological advantages of the proposed joint inversion strategy in resolving complex, heterogeneous environments, and highlight its potential for broader applicability in environmental and engineering geophysics.</p>

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Joint inversion of transient electromagnetic and radiomagnetotelluric data for enhanced subsurface characterization

  • Ismael M. Ibraheem,
  • Pritam Yogeshwar,
  • Fereydoun Sharifi,
  • Rainer Bergers,
  • Bülent Tezkan

摘要

Joint inversion of geophysical data offers a robust means to improve the resolution and reliability of subsurface models, particularly when integrating methods with complementary depth sensitivities. This study presents a 1D joint inversion methodology for combining Transient Electromagnetic (TEM) and Radiomagnetotelluric (RMT) data, two complementary electromagnetic methods that provide insights into different depth ranges of the subsurface. The approach is validated through synthetic modeling and applied to a landfill site to demonstrate its practical utility. Results confirm that joint inversion significantly reduces model ambiguity and enhances the delineation of key structures, including the extent of the waste body. These findings show the methodological advantages of the proposed joint inversion strategy in resolving complex, heterogeneous environments, and highlight its potential for broader applicability in environmental and engineering geophysics.