Automatic velocity analysis using bootstrapped differential semblance and global search methods*
Hyungwook Choi 1 Joongmoo Byun 1 2 Soon Jee Seol 11 Department of Natural Resources and Environmental Engineering, Hanyang University, 17 Haengdang-dong, Sungdong-gu, Seoul, 133-791, Korea.
2 Corresponding author. Email: jbyun@hanyang.ac.kr
Exploration Geophysics 41(1) 31-39 https://doi.org/10.1071/EG10004
Submitted: 30 November 2009 Accepted: 15 January 2010 Published: 19 February 2010
Abstract
The goal of automatic velocity analysis is to extract accurate velocity from voluminous seismic data with efficiency. In this study, we developed an efficient automatic velocity analysis algorithm by using bootstrapped differential semblance (BDS) and Monte Carlo inversion. To estimate more accurate results from automatic velocity analysis, the algorithm we have developed uses BDS, which provides a higher velocity resolution than conventional semblance, as a coherency estimator. In addition, our proposed automatic velocity analysis module is performed with a conditional initial velocity determination step that leads to enhanced efficiency in running time of the module. A new optional root mean square (RMS) velocity constraint, which prevents picking false peaks, is used. The developed automatic velocity analysis module was tested on a synthetic dataset and a marine field dataset from the East Sea, Korea. The stacked sections made using velocity results from our algorithm showed coherent events and improved the quality of the normal moveout-correction result. Moreover, since our algorithm finds interval velocity (vint) first with interval velocity constraints and then calculates a RMS velocity function from the interval velocity, we can estimate geologically reasonable interval velocities. Boundaries of interval velocities also match well with reflection events in the common midpoint stacked sections.
Key words: automatic velocity analysis, bootstrapped differential semblance, interval velocity, Monte Carlo inversion, root mean square velocity constraint.
Acknowledgment
The authors are grateful for financial support from the Ministry of Knowledge Economy of Korea through ‘Development of Exploration and Prospecting Technology of Petroleum System in Marginal Oil and Gas Field’ project, and thank the Korea Institute of Geoscience and Mineral Resources (KIGAM) for providing the real dataset and allowing publication of the results.
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* *Part of this paper was presented at the 9th SEGJ International Symposium (2009).