石油物探2017，Vol.56Issue(1)：26-30,5.DOI:10.3969/j.issn.1000-1441.2017.01.003
全波形反演的一个新目标函数:数据域中的微分相似优化
A new objective function for full waveform inversion: differential semblance optimization in data domain
高福春 1Paul WILLIAMSON 1R.GerhardPRATT2
作者信息
- 1. 道达尔勘探和生产研究技术中心,休士顿77002,美国
- 2. 西安大略大学,伦敦N6A 3K7,加拿大
- 折叠
摘要
Abstract
Full Waveform Inversion (FWI),while now widely practiced industrially,is less robust than many conventional velocity model building techniques,such as travel time tomography,due to its high non-linearity.Different objective functions in FWI have different degrees of non-linearity.In this study,we investigate the behavior of FWI with different objective functions and propose a new objective function based on differential semblance defined in the data domain.Preliminary tests suggest that this objective function is convex for a large range of data residuals.Gradient-based optimization schemes are therefore more robust than for the standard least-squares formulation;however,the good resolving power of waveform inversion is mostly retained.关键词
全波形反演/目标函数/非线性/微分相似优化Key words
full waveform inversion/objective function/non-linearity/differential semblance optimization分类
天文与地球科学引用本文复制引用
高福春,Paul WILLIAMSON,R.GerhardPRATT..全波形反演的一个新目标函数:数据域中的微分相似优化[J].石油物探,2017,56(1):26-30,5.
