Abstract
Marine surveys in many of today's exploration hotspots encounter interference from other seismic crews shooting in close proximity. The crew noise interference appears as a pattern that can be readily identified by the human eye in seismic shot displays (Figure 1). To date, no efficient automated method has been established to remove these interference patterns prior to CMP stacking so that the data can be used for accurate amplitude versus offset (AVO) analysis. Neural networks have been used successfully in many geophysical applications due to their superior pattern recognition capabilities. The purpose of this study is to train a neural network to identify crew noise interference patterns for subsequent removal. The desired result is a clean pre-stack shot display that is ready for further processing.
Original language | English (US) |
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DOIs | |
State | Published - 1999 |
Event | 1999 Society of Exploration Geophysicists Annual Meeting, SEG 1999 - Houston, United States Duration: Oct 31 1999 → Nov 5 1999 |
Other
Other | 1999 Society of Exploration Geophysicists Annual Meeting, SEG 1999 |
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Country/Territory | United States |
City | Houston |
Period | 10/31/99 → 11/5/99 |
ASJC Scopus subject areas
- Geophysics