1. College of Geophysics, China University of Petroleum (Beijing), Beijing 102249, China; 2. State Key Laboratory of Petroleum Resources and Prospecting, Beijing 102249, China
Abstract：Although acoustic impedance inversion technology is quite mature, there are still some issues such as the ill-posedness of inverse problems, low resolution of inversion results, and the inability to delineate the stratigraphic boundaries. To this end, a seismic “blocky” acoustic impedance inversion method based on L1-2 regularization is proposed. Based on existing research, this paper introduces L1-2 regularization into the model-based acoustic impedance inversion and directly obtains the acoustic impedance inversion results from post-stack seismic data according to the idea of total variation regularization. First, the paper deduces a linearized forward modeling equation of acoustic impedance and analyzes its accuracy. Then, based on Bayesian theory, the paper constructs the objective function of the acoustic impedance inversion by the L1-2 regularization and solves the function through an iterative reweighted least squares (IRLS) algorithm to obtain the acoustic impedance inversion results. Since the acoustic impedance inversion is a single-trace inversion method, when it is applied to multi-trace data inversion, there is a spatial discontinuity. Therefore, an f-x space predictive filtering method is used to alleviate the discontinuity caused by noise and single-trace inversion. The quantitative comparison of correlation coefficients proves that the inversion results obtained by the L1-2 norm are better than those obtained by L1 and L2 norms, and synthetic and field data inversion examples demonstrate the effectiveness and feasibility of the proposed method.
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