.png){kind=icon}
返回
Diffraction separation using structure-oriented orthogonal polynomial transform
.png){kind=icon}
PRE
AI
DOI：10.1190/GEO2021-0693.1.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Diffractions possess the potential to reveal subsurface discontinuities, such as faults, collapsed columns, and the rough edges of the salt body. We have developed a novel diffraction separation method that first flattens the dominant reflections and then identifies the diffraction wavefields through an orthogonal polynomial transform (OPT). Based on the plane-wave assumption and local slope, the reflection events can be predicted and flattened using plane-wave differential equations. To enhance the stability of the flattening process, a sliding window algorithm and three finite-difference forms are adopted. As the dominant coherent event, a reflection often corresponds to low-order coefficients in the OPT. To better preserve the diffraction energy, a time-varying order threshold is used when removing the dominant reflections. Two field data applications are presented to demonstrate the feasibility and effectiveness of the proposed diffraction separation strategy.
Keyword:
IMAGE
期刊
IF:
3.2
论文数:
8.4K
被引数:
3.3W
机构
暂无机构信息
引用论文
.png){kind=icon}
Prediction of microsleeps using pairwise joint entropy and mutual information between EEG channels
PREAI
分享收藏分享收藏分享收藏
查看更多内容