Scholarlink

<p>This study introduces FTCSEM, a FORTRAN-based, parallelized one-dimensional controlled-source electromagnetic (CSEM) forward modeling and inversion software capable of accommodating arbitrary source-receiver configurations. In comparison to existing one-dimensional CSEM tools, FTCSEM incorporates several significant enhancements: it supports transmitters of diverse shapes, quantities, and spatial locations; permits receivers to be positioned flexibly on the surface, subsurface, or in the atmosphere; facilitates simulations and inversions in both frequency and time domains; integrates an adaptive regularized inversion algorithm with multiple model constraints; and leverages GPU-accelerated parallel computing to attain high computational efficiency. Validation through numerical experiments and field data inversion confirms the program’s accuracy and practical applicability. The findings indicate that FTCSEM performs robustly in complex geoelectric environments, multi-source and multi-receiver arrangements, as well as multi-component joint inversion scenarios, thereby offering a versatile and powerful tool for advancing CSEM research and applications.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

FTCSEM—A FORTRAN-based parallelized 1D CSEM forward and inversion program for arbitrary source-receiver geometry

  • 期刊论文

  • 发表日期：

    2026年2月7日

查看全文
  • Wei-ying Chen,
  • Si-xu Han,
  • Wan-ting Song,
  • Yu-lian Zhu,
  • Zheng Liu

摘要

This study introduces FTCSEM, a FORTRAN-based, parallelized one-dimensional controlled-source electromagnetic (CSEM) forward modeling and inversion software capable of accommodating arbitrary source-receiver configurations. In comparison to existing one-dimensional CSEM tools, FTCSEM incorporates several significant enhancements: it supports transmitters of diverse shapes, quantities, and spatial locations; permits receivers to be positioned flexibly on the surface, subsurface, or in the atmosphere; facilitates simulations and inversions in both frequency and time domains; integrates an adaptive regularized inversion algorithm with multiple model constraints; and leverages GPU-accelerated parallel computing to attain high computational efficiency. Validation through numerical experiments and field data inversion confirms the program’s accuracy and practical applicability. The findings indicate that FTCSEM performs robustly in complex geoelectric environments, multi-source and multi-receiver arrangements, as well as multi-component joint inversion scenarios, thereby offering a versatile and powerful tool for advancing CSEM research and applications.