Global Structure-Constrained 4D prestack inversion

Abstract

Prestack seismic inversion often suffers from inherent ill-posedness and is significantly affected by complex factors such as the wavelets, parameter coupling, heterogeneous media, fault displacements, and stratigraphic variations, making it difficult for the conventional inversion methods to accurately recover subsurface information. To address these challenges, this paper proposes a global inversion method based on multi-dimensional matrix multiplication to optimize the inversion results under structure constraints. This method first represents the inversion model as a four-dimensional tensor representing spatial and parameter dimensions. By performing multi-dimensional matrix multiplication operations in various directions of the model, a multi-dimensional tensor of observed data is effectively constructed. Secondly, multi-dimensional regularization are introduced. By analyzing the impact of different dimensional constraints on the inversion results, targeted parameter selection and adjustment are achieved, significantly enhancing the stability of the inversion process and effectively suppressing noise. Finally, stratigraphic and fault constraints extracted from seismic interpretation are incorporated to improve the geological coherence and reasonableness of the inversion results. Both synthetic and field data experiments demonstrate that the proposed method effectively enhances the robustness of inversion in complex structural areas while maintaining high computational efficiency, validating its effectiveness in practical applications.