In the heart of China’s Central South University, a groundbreaking method is being developed that could revolutionize the way we explore and understand the Earth’s subsurface. Dr. Qianwei Dai, a leading researcher at the School of Geosciences and Info-physics, has introduced an innovative approach to controlled-source audio-frequency magnetotelluric (CSAMT) data inversion, promising to enhance computational efficiency and resolution in geophysical surveys.
The challenge with traditional CSAMT data inversion methods lies in their tendency to oversmooth results, obscuring the intricate details of complex geological structures. “Our goal was to create a method that could accurately reflect the spatial distribution of subsurface physical properties,” Dai explains. To achieve this, Dai and his team turned to the Matérn covariance function, a statistical tool that can model the non-stationary nature of geological formations.
By integrating the Matérn covariance function into a stochastic partial differential equation (SPDE), Dai’s method introduces vector fields and shape parameters to account for variations in strata inclination and non-stationary physical property distributions. This approach allows for the creation of a model covariance matrix that serves as a regularization constraint during inversion, significantly improving the accuracy of subsurface imaging.
The results speak for themselves. When applied to both theoretical models and real-world data from the Ye’erkeman-Jinba gold deposit in Xinjiang, Dai’s method demonstrated a remarkable reduction in residuals—up to 51.47%—compared to conventional Occam-type inversion. This enhanced imaging performance translates to a more precise delineation of geological boundaries and a reduced uncertainty in deep area inversion results.
The implications for the energy sector are substantial. Accurate subsurface imaging is crucial for mineral exploration, oil and gas prospecting, and geothermal energy assessment. Dai’s method could lead to more efficient and effective exploration campaigns, reducing costs and minimizing environmental impact.
“Our method provides a novel technical solution for addressing the long-standing issues of computational efficiency and resolution in CSAMT inversion,” Dai states. This advancement could pave the way for more sophisticated geophysical surveys, ultimately contributing to the sustainable development of natural resources.
Published in the journal ‘Meitian dizhi yu kantan’ (which translates to ‘Modern Geophysical Exploration’), Dai’s research marks a significant step forward in geophysical inversion technology. As the energy sector continues to evolve, innovations like Dai’s will be instrumental in meeting the growing demand for accurate and efficient subsurface exploration methods. The future of geophysical surveys looks brighter, thanks to the pioneering work of Dr. Qianwei Dai and his team.