Frequency dependent seismic reflection analysis: a path to new direct hydrocarbon indicators for deep water reservoirs
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To better study frequency related eﬀects such as attenuation and tuning, we developed a frequency dependent seismic reﬂection analysis. Comprehensive tests on full waveform synthetics and observations from the Teal South ocean bottom seismic (OBS) data set conﬁrmed that normal moveout (NMO) stretch could distort both frequency and amplitude information severely in shallow events and far oﬀset traces. In synthetic tests, our algorithm recovered amplitude and frequency information ac-curately. This simple but robust target oriented NMO stretch correction scheme can be used on top of an existing seismic processing ﬂow for further analyses. By combining the NMO stretch correction, spectral decomposition, and crossplots of am-plitude versus oﬀset (AVO) attributes, we tested the frequency dependent workﬂow over Teal south and Ursa ﬁeld data sets for improved reservoir characterization. As expected from NMO stretch characteristics, low frequencies have been less aﬀected while mid and high frequency ranges were aﬀected considerably. In seismic attribute analysis, the AVO crossplots from spectrally decomposed prestack data conﬁrmed the improved accuracy and eﬀectiveness of our workﬂow in mid and high frequency regions. To overcome poor spectral decomposition results due to low signal to noise ratio (S/N) in the Teal South application, we also implemented a substack scheme that stacks adjacent traces to increase S/N ratio while reducing the amount of data to process and increasing the accuracy of the spectral decomposition step. Synthetic tests veriﬁed the eﬀectiveness of this additional step. An application to the Ursa, Gulf of Mexico, deep water data set showed signiﬁcant improvement in high frequency data while correcting biased low frequency information.
Yoo, Seung Chul (2007). Frequency dependent seismic reflection analysis: a path to new direct hydrocarbon indicators for deep water reservoirs. Doctoral dissertation, Texas A&M University. Available electronically from