Separation of Blended Seismic Data Using the Synchrosqueezed Curvelet Transform

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Time-frequency (TF) analysis algorithms are widely used to process seismic data. Unfortunately, most TF analysis algorithms cannot process 2-D seismic data, which contain more information than 1-D data. In fact, 2-D x-t domain seismic data should be analyzed in the multi-dimensional phase space (MDPS). In this letter, we develop and explain an MDPS analysis method for 2-D seismic data. In order to map the 2-D seismic data into MDPS, the synchrosqueezed curvelet transform (SSCT) is extended from the x-y domain to the x-t domain. By comparing the 2-D synchrosqueezing transform (SST) with the 1-D SST, we explain how the 2-D SST makes the connection between the 4-D curvelet domain and the 4-D space-time-wavenumber-frequency domain (xt-kf domain). This new analytical method can help us to obtain the angle, scale, frequency, and wavenumber information, which are useful to separate the overlapped seismic data. The numerical example and real data example illustrate the effectiveness of this method.

Original languageEnglish
Article number8772154
Pages (from-to)711-715
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Volume17
Issue number4
DOIs
StatePublished - Apr 2020

Keywords

  • Multi-dimensional phase space (MDPS)
  • seismic data
  • source separation
  • synchrosqueezed curvelet transform (SSCT)

Fingerprint

Dive into the research topics of 'Separation of Blended Seismic Data Using the Synchrosqueezed Curvelet Transform'. Together they form a unique fingerprint.

Cite this