A Probabilistic Approach to Seismic Diffraction Imaging

Author:

Decker Luke1ORCID,Fomel Sergey1ORCID

Affiliation:

1. Oden Institute for Computational Engineering and Sciences The University of Texas at Austin 201 E 24th St Austin TX 78712 USA utexas.edu

Abstract

Abstract We propose and demonstrate a probabilistic method for imaging seismic diffractions based on path-integral imaging. Our approach uses oriented velocity continuation to produce a set of slope-decomposed diffraction images over a range of plausible migration velocities. Utilizing the assumption that each partial image in slope is independent enables us to construct an object resembling a probability field from the slope-decomposed images. That field may be used to create weights for each partial image in velocity corresponding to the likelihood of a correctly migrated diffraction occurring at a location within the seismic image for that migration velocity. Stacking these weighted partial images over velocity provides us with a path-integral seismic diffraction image created using probability weights. We illustrate the principles of the method on a simple toy model, show its robustness to noise on a synthetic, and apply it to a 2D field dataset from the Nankai Trough. We find that using the proposed approach creates diffraction images that enhance diffraction signal while suppressing noise, migration artifacts, remnant reflections, and other portions of the wavefield not corresponding to seismic diffraction relative to previously developed diffraction imaging methods, while simultaneously outputting the most likely migration velocity. The method is intended to be used on data which has already had much of the reflection energy removed using a method like plane-wave destruction. Although it suppresses residual reflection energy successfully, this suppression is less effective in the presence of strong reflections typically encountered in complete field data. The approach outlined in this paper is complimentary to existing data domain methods for diffraction extraction, and the probabilistic diffraction images it generates can supplement existing reflection and diffraction imaging methods by highlighting features that have a high likelihood of being diffractions and accentuating the geologically interesting objects in the subsurface that cause those features.

Funder

Texas Consortium for Computational Seismology

Publisher

GeoScienceWorld

Subject

Geology

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3