摘要

This paper presents a novel covariation approach for seismic inversion under the assumption that the real seismic signals follow non-Gaussian alpha-stable distribution. To verify the correctness and effectiveness of the proposed method, two computer inversion simulation experiments on synthetic data inversion and real seismic acoustic impedance inversion are conducted using covariation, covariance and Bayesian methods. In the inversion experiment, covariation method performances better than the covariance and Bayesian, and the inverse results are very close to the true solutions. In the real seismic data inversion case, the sample quantile method was applied to estimate the characteristic exponent of a seismic trace from a nearby well before inversion. The estimated characteristic was applied in the 2D seismic impedance inversion where the moment p of the whole survey is set to be less than it. The results from the inversion of the 2D real data set are consistent with the well log interpretation.