Estimation of Sea Surface Temperature (SST) Using Marine Seismic Data
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- 作者：Satish Kumar Sinha ; Pawan Dewangan ; Kalachand Sain
- 关键词：Marine seismic ; direct arrivals ; soundspeed ; sea surface temperature ; diurnal variations
- 刊名：Pure and Applied Geophysics
- 出版年：2016
- 出版时间：April 2016
- 年：2016
- 卷：173
- 期：4
- 页码：1305-1316
- 全文大小：1,993 KB
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Pawan Dewangan (2)
Kalachand Sain (3)
1. Rajiv Gandhi Institute of Petroleum Technology, Rae Bareli, Uttar Pradesh, 229316, India
2. CSIR-National Institute of Oceanography, Dona Paula, Goa, India
3. CSIR-National Geophysical Research Institute, Hyderabad, India - 刊物类别：Earth and Environmental Science
- 刊物主题：Earth sciences
Geophysics and Geodesy - 出版者：Birkh盲user Basel
- ISSN：1420-9136
文摘
Not much attention is given to direct wave arrivals in marine seismic data that are acquired for petroleum exploration and prospecting. These direct arrivals are usually muted out in routine seismic data processing. In the present study, we process these direct arrivals to accurately estimate soundspeed in near-surface seawater and invert for sea surface temperature. The established empirical equation describing the relationships among temperature, salinity, pressure and soundspeed is used for the inversion. We also discuss processing techniques, such as first-break picking and cross-correlation for the estimation of soundspeed, that are well known among petroleum-industry geophysicists. The accuracy of the methods is directly linked to the data quality and signal processing. The novelty in our approach is in the data conditioning, which consists essentially of spectral balancing based on a wavelet transform that compensates for spherical spreading and increases the signal-to-noise (S/N) ratio. The 2D seismic data used in this paper are from the offshore Krishna-Godavari Basin east of India. We observe a significantly higher soundspeed of 1545 m/s for near-surface water than the commonly used value of ~1500 m/s. The estimated temperature (from velocity) is about 30 °C. Interestingly, the estimated temperature matches well with the temperature recorded in the CTD profile acquired in the study area during the month of May, the month corresponding to the acquisition of seismic data. Furthermore, the estimated temperatures during different times of data acquisition correlate well with the expected diurnal variation in temperature.