Seismic analysis using wavelet transform for hydrocarbon detection in paleokarst reservoirs
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Recent advances in deep hydrocarbon explorations reveal that paleo-karst systems could be among one of the important prolific hydrocarbon reservoirs. However, a challenging problem is to distinguish the hydrocarbon-bearing karsts from the water-saturated ones before drilling. In this study, we show that as one of the most advanced wave decomposition techniques, wavelet transform could aid seismic analysis for hydrocarbon detection in paleo-karst reservoirs. In wavelet transform, seismic wave is decomposed into different frequency contents. Amplitude anomalies for each frequency are identified for possible association with hydrocarbon occurrence due to seismic attenuation. For the studied deep paleo-karst reservoir of an Ordovician age in the Tarim basin of China, processed 3D post-stack data sets are used to detect hydrocarbon zones by analyzing the low frequency signals in the decomposed domain. It is found that low-frequency anomalies on the spectrogram of a frequency of 20Hz best correlate with the occurrence of oil-saturated paleo-karsts in the studied area, whereas the spectrogram at high-frequency end e.g., 70 Hz could reveal thin beds and other high-resolution structural and/or stratigraphic information of the reservoirs. 2011 Society of Exploration Geophysicists.
SEG Technical Program Expanded Abstracts 2011
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