Preserving the discontinuities in least-squares reverse time migration of simultaneous-source data
- Yangkang Chen (University of Texas—Austin) | Kui Xiang (China University of Petroleum—Beijing) | Hanming Chen (China University of Petroleum—Beijing) | Xiaohong Chen (China University of Petroleum—Beijing)
- Document ID
- Society of Exploration Geophysicists
- 2016 SEG International Exposition and Annual Meeting, 16-21 October, Dallas, Texas
- Publication Date
- Document Type
- Conference Paper
- 2016. Society of Exploration Geophysicists
- Simultaneous sources, Reverse-time, Migration, Noise
- 0 in the last 30 days
- 20 since 2007
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The simultaneous-source shooting technique can accelerate field acquisition and improve spatial sampling but will cause strong interferences in the recorded data. Direct imaging of blended simultaneous-source data has been demonstrated to be a promising research field since there is no need to separate the blended data before the subsequent processing and imaging. The key issue in direct imaging of blended data is the strong artifacts in the migrated image. Although the least-squares migration can help reduce some artifacts, there are still residual artifacts in the image. Those artifacts mainly appear in the shallow part of the image as spatially incoherent noise. Previously proposed structural smoothing operator can effectively attenuate the artifacts for relatively simple reflection structures during least-squares inversion, but it will cause damage to complicated reflection events such as the discontinuities. In order to preserve the discontinuities in the seismic image, we apply the singular spectrum analysis (SSA) operator to attenuate artifacts during least-squares inversion. Considering that global SSA cannot deal with over-complicated data well, we propose to use local SSA in order to remove noise and preserve steeply dipping components better. The local SSA operator corresponds to a local low-rank constraint applied in the inversion process. The migration operator used in the study is the reverse time migration (RTM) operator. We use the Marmousi model example to show the superior performance of the proposed algorithm.
Presentation Date: Wednesday, October 19, 2016
Start Time: 11:35:00 AM
Presentation Type: ORAL
|File Size||1 MB||Number of Pages||6|
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