2-D Imaging for 3-D Ground Frequency-Domain CSEM Based on Vector Finite Element

Over the past few decades, electromagnetic field signals have been widely used to develop data interpretation methods for the ground controlled source electromagnetic (CSEM) method in the frequency domain. Identifying anomalous features from these signals, however, remains challenging, as the intensity of the signals linked to these anomalies is weaker. In order to address this issue, this article presents an inversion algorithm that uses apparent resistivity data to enhance anomaly detection. Because of the high computational complexity and memory demands of 3-D CSEM inversion modeling, many real-world surveys are interpreted using 1-D inversion schemes, which simplifies the modeling process but may limit accuracy. A quasi-2-D inversion imaging technique based on the tracking balance operator (hereafter referred to as QITB) is introduced to balance efficiency and interpretive accuracy. Rather than performing 3-D inversion, QITB applies 1-D modeling in a structured framework to approximate 3-D subsurface structures. This imaging-focused algorithm eliminates the need for complex 3-D computations while maintaining high accuracy in identifying subsurface anomalies. Numerical simulations demonstrate that wide-field apparent resistivity is significantly more effective than electric field data in highlighting subsurface anomalies. Inversion results from synthetic data show that QITB identifies anomalies and yields more accurate estimates of burial depth. In contrast, conventional 1-D inversion without the tracking balance operator, although capable of fitting 3-D data, fails to approximate the true 3-D model closely. In conclusion, QITB is an innovative and efficient method for rapidly interpreting 3-D ground CSEM data, combining computational efficiency with reliable subsurface structure identification.