Analysis of the covariance matrix in FWI through density of covariance maps

A. Jim'enez, Juan Carlos Muñoz Cuartas, S. Avendaño, Leonardo Gómez Bernal
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Abstract

Full waveform inversion (FWI) is a tool for the inversion of seismic data. There are several sources of uncertainty in the results provided by FWI. The quantification of such uncertainties has been studied through the resolution matrix (Res), which rests on a quadratic approximation that interprets the Hessian matrix as the posterior covariance matrix. Despite efforts in the use of Res, there is no published analysis of the uncertainties contained in the full correlation matrix, (R). Our approach leads to build the full R matrix, which, at the end of the day, is the final quantity that includes all the information associated with uncertainties.We focused on uncertainties related to variation in the starting models of the FWI, and thus propose a method to study the full R matrix, which is-called the Density of Correlation Map, D. By using the D map, we found that the highest uncertainty zones in the FWI inverted model are near the sources, the model boundaries, and the interfaces. We argue that D can be a complement for the study and estimation of uncertainties in FWI.
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通过协方差图的密度分析FWI的协方差矩阵
全波形反演(FWI)是地震资料反演的一种工具。FWI提供的结果存在几个不确定性来源。这种不确定性的量化已经通过分辨率矩阵(Res)进行了研究,它依赖于将Hessian矩阵解释为后验协方差矩阵的二次近似。尽管在使用Res方面做出了努力,但没有发表对完整相关矩阵(R)中包含的不确定性的分析。我们的方法导致构建完整的R矩阵,在一天结束时,它是包含与不确定性相关的所有信息的最终数量。本文重点研究了FWI启动模型中与变化相关的不确定性,提出了一种研究全R矩阵的方法,即相关密度图D。利用D图,我们发现在FWI倒置模型中,不确定性最大的区域位于源、模型边界和界面附近。我们认为D可以作为FWI不确定性研究和估计的补充。
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