Seismic data reconstruction in Dreamlet domain based on compressive sensing

被引：0

作者：

Wang, Xinquan ^{[1
]}

Geng, Yu ^{[2
]}

Wu, Ru-Shan ^{[2
]}

Song, Pengpeng ^{[1
]}

机构：

[1] Tuha Division, BGP Inc., CNPC, Hami, 839009, Xinjiang

[2] University of California at Santa Cruz, Santa Cruz

来源：

Shiyou Diqiu Wuli Kantan/Oil Geophysical Prospecting | 2015年 / 50卷 / 03期

关键词：

Compressive sensing; Data reconstruction; Dreamlet domain; random sample; Sparse data;

D O I：

10.13810/j.cnki.issn.1000-7210.2015.03.002

中图分类号：

学科分类号：

摘要：

A new signal processing technique was developed recently due to the progress of compressive sensing theory, which is attracted attention in petroleum and nature gas exploration. Recently great progress has been made in seismic data random sparse sampling, seismic data reconstruction, seismic data regularization, and optimized geometry design. In this paper, we propose a new data reconstruction method based on the data reconstruction method in Dreamlet domain presented by Ru-Shan Wu. According to energy great variation in time and space domain and strong noise of seismic data, we reconstruct and compare synthetic data of random sparse sampling and real seismic data by optimizing parameters and the reconstruction process. Synthetic and real data tests show that the proposed method is a high-efficient and high-quality one. ©, 2015, Science Press. All right reserved.

引用

页码：399 / 404

页数：5

共 9 条

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