Application of seismic reflection data to discriminate subsurface lithostratigraphy

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Abstract
A correlation between lithology and quantitative parameters abstracted from seismic reflection data is established. The concept and methodology developed on synthetic data has been successfully applied to discriminate between two different kinds of lithologies. A particular hydrocarbon‐bearing formation in a sedimentary basin in Western India has been considered, part of which is dominantly sandy (lithological composition: sand = 53 percent, shale = 21 percent, coal = 26 percent) and another part which is dominantly shaly (sand = 37 percent, shale = 60 percent, coal = 3 percent). These two different lithologies are mathematically modeled using one‐step Markov chains. Their seismic responses when scrutinized in time and frequency domain and subjected to statistical discriminant analysis give a fair idea about synthetic subsurface lithostratigraphy. Seismic reflection data from the same area were considered for a similar analysis. On subjecting the data to discriminant analysis, it was again possible to discriminate between the two lithologies. Also, seismograms from different areas of the same basin could be assessed in terms of subsurface lithology. Seven seismic discriminators of subsurface lithostratigraphy have been identified, three of which are abstracted from the autocorrelation function and four from the power spectrum of the seismogram. This analysis is a potential tool for diagnosing subsurface lithology from seismic data and may ultimately help discriminate an oil‐bearing stratigraphic trap from its barren surroundings in a sedimentary basin.

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