Gravity Inversion in Spherical Coordinates With Dynamic Re-Weighting Matrix

Nearly all global datasets from satellite missions have been instrumental in advancing research on regional and global-scale underground density structures. However, satellite gravity inversion faces challenges such as instability, multiple solutions, and low resolution due to the ill-posed nature of the problem. Methods like depth-weighting and different norms improve resolution but can introduce instability and noise sensitivity, requiring further refinement for optimal results. This article proposes a novel gravity inversion method in spherical coordinates, employing dynamically re-weighting matrix to enhance inversion resolution. Initially, weights are assigned to each tesseroid based on cross-correlation coefficients, forming an initial model weighting matrix. This matrix is then iteratively optimized by minimizing two regularized objective functions that incorporate the kernel matrix and observed data, refining the weights distribution to better approximate the actual geological situation. Synthetic model studies demonstrate that this method significantly improves the resolution of inversion results, particularly in identifying gently dipping density anomalies. Application of this method to the India-Asia collision zone reveals consistent subduction plate geometry with previous studies, validating its practicality and effectiveness in imaging intricate density patterns. This approach offers a substantial advancement in gravity inversion techniques, providing clearer and more accurate geological models.