微震
算法
加性高斯白噪声
先验与后验
计算机科学
噪音(视频)
概率逻辑
高斯分布
上下界
到达时间
白噪声
统计
地质学
数学
地震学
物理
数学分析
哲学
人工智能
工程类
量子力学
图像(数学)
运输工程
认识论
作者
Ivan Abakumov,Aurelian Roeser,Serge A Shapiro
出处
期刊:Geophysics
[Society of Exploration Geophysicists]
日期:2020-03-31
卷期号:85 (4): U65-U76
被引量:11
标识
DOI:10.1190/geo2019-0589.1
摘要
ABSTRACT Traveltime-based methods depend on the accurate determination of the arrival times of seismic waves. They further benefit from information on the uncertainty with which the arrival times are determined. Among other applications, arrival-time uncertainties are used to weight data in inversion algorithms and to define the resolution of reconstructed velocity models. The most physically meaningful approaches for the estimation of arrival-time uncertainties are based on probabilistic formulations. The two approaches for the assessment of the lower bound of arrival-time uncertainties, the Cramér–Rao Bound (CRB) and the Ziv–Zakai Bound (ZZB), have been reviewed. The CRB determines the minimum-achievable estimation error under the assumption of a high signal-to-noise ratio (S/N) but underestimates said error for small S/N. The ZZB provides a better result for noisy data because it utilizes a priori information. The CRB and ZZB require knowledge of the spectral variance of the signal, which often is hard to determine in seismic experiments. Furthermore, both bounds assume additive white Gaussian noise (AWGN), which does not hold for seismic data. To overcome these problems, alternative expressions have been proposed, which yield comparable estimates as CRB and ZZB but are solely based on the S/N and the dominant period in the data. Moreover, a recipe to correct the S/N and account for the difference between the seismic noise and AWGN has been provided. For a case study of downhole microseismic monitoring, it is determined that the new expressions provide station-dependent arrival-time uncertainties, which are used as weights to improve source location uncertainties.
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