返回
An efficient local operator-based Q-compensated reverse time migration algorithm with multistage optimization
DOI:10.1190/GEO2017-0026.1.png)
摘要
En 中文
Most existing Q-compensated reverse time migration (Q-RTM) algorithms are based on pseudospectral methods. Because of the global nature of pseudospectral operators, these methods are not ideal for efficient parallelization, implying that they may suffer from high computational cost and inefficient memory usage for large-scale industrial problems. In this work, we reported a novel Q-RTM algorithm - the multistage optimized Q-RTM method. This Q-RTM algorithm uses a finite-difference method to compensate the amplitude and the phase simultaneously by uniquely combining two techniques: (1) a negative tau method for amplitude compensation and (2) a multistage dispersion optimization technique for phase correction. To prevent high-frequency noise from growing exponentially and ruining the imaging results, we apply a finite impulse response low-pass filter using the Kaiser window. The theoretical analyses and numerical experiments demonstrate that this Q-RTM algorithm precisely recovers the decayed amplitude and corrects the distorted phase caused by seismic attenuation effects, and hence produces higher resolution subsurface images with the correct structural depth information. This new method performs best in the frequency range of 10-70 Hz. Compared with pseudospectral Q-RTM methods, this Q-RTM approach offers nearly identical imaging quality. Based on local numerical differential operators, this Q-RTM method is very suitable for parallel computing and graphic processing unit implementation, an important feature for large 3D seismic surveys.
Keyword:
PERFECTLY MATCHED LAYER
WAVE-PROPAGATION
DOMAIN DECOMPOSITION
FOURIER-TRANSFORM
DEPTH MIGRATION
CONSTANT-Q
ATTENUATION
EQUATION
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.2
论文数:
8.4K
被引数:
3.3W
机构
引用论文
Seismic wave attenuation and dispersion resulting from wave-induced flow in porous rocks - A review
GEOPHYSICS
IF3.2
Diffusion Generative Model-Based Learning for Smart Layer-Wise Monitoring of Additive Manufacturing基于扩散生成模型的学习,用于增材制造的智能分层监控
Attenuation compensation for least-squares reverse time migration using the viscoacoustic-wave equation
GEOPHYSICS
IF3.2

