发布时间：2025-04-30

论文名称：Channel detection using the self-adaptive generalized S-transform

发表刊物：SEG Technical Program Expanded Abstracts 2018

摘要：Achieving a proper time-frequency (TF) resolution is the key to extract information from seismic data using TF algorithms and characterize reservoir properties using decomposed frequency components. The generalized Stransform (GST) is one of the most widely used TF algorithms. However, it is difficult to choose an optimized parameter set for the whole seismic data set. In this paper, we propose to set parameters of the GST adaptively using the instantaneous frequency (IF) of seismic traces. We name the proposed workflow as the self-adaptive generalized S-transform (SAGST). To demonstrate the validity and effectiveness of the proposed SAGST, we apply it to field data to detect channels. Real data examples illustrate that SAGST can research a better TF resolution.

合写作者：Naihao Liu, Bo Zhang, Jinghuai Gao, Yijie Zhang, and Xiudi Jiang

是否译文：否

发表时间：2018-10-18