New Achievement of 3D Joint Inversion of Gravity and Magnetic Data Using Gramian-based Structural Similarity and Structural Direction Constraints. Case Study: Intraplate Phreatomagmatic Structure Los Contreras, Mexico - Gonzalez, Abraham Del Razo; Yutsis, Vsevolod (Science and Technology - Recent Updates and Future Prospects Vol. 1, 2024)
The development of numerical solutions for joint inversion is very important in geophysics, especially in 3D. This is in an effort to produce a fast and accurate interpretation of subsurface conditions. One of the fundamental challenges in geophysics is the calculation of distribution models for physical properties in the subsurface that accurately reproduce the measurements obtained in the survey and are geologically plausible in the context of the study area. This is known as inverse modeling. Completing a 3D joint inversion of multimodal geophysical data requires a lot of processing power. Furthermore, because it involves modeling, iterative computations are needed to obtain a solution that meets the desired qualities, which can result in final results taking days or even weeks to receive. In this paper, we propose a robust numerical solution for 3D joint inversion of gravimetric and magnetic data with Gramian-based structural similarity and structural direction constraints using parallelization as high-performance computing technique which allows us to significantly reduce the total processing time based on the available Random-Access Memory (RAM) and Video Random Access Memory (VRAM) and improve the efficiency of interpretation. The solution is implemented in the high-level programming languages Fortran and Compute Unified Device Architecture (CUDA) Fortran, capable of optimal resource management while being straightforward to implement. Through the analysis of performance and computational costs of serial, parallel, and hybrid implementations, we conclude that as the inversion domain expands, the processing speed could increase from 4x up to 100x times faster, rendering it particularly advantageous for applications in larger domains. We tested our algorithm with two synthetic data sets and field data (Intraplate phreatomagmatic structure, Maar Los Contreras), showing better results than standard separate inversion. The suggested approach is beneficial for joint geological and geophysical interpretation of gravimetric and magnetic data utilized in geophysical exploration, such as prospecting and mineral, ore, and petroleum search. Its use will greatly speed up the data processing process and improve the dependability of physical-geological models.