Applying principal component analysis to seismic attributes for interpretation of evaporite facies: Lower Triassic Jialingjiang Formation, Sichuan Basin, China

In China and elsewhere, it is important to predict different lithologies and lithofacies for hydrocarbon exploration in a mixed evaporite-carbonate-siliciclastic system. The lower section of the second member of the Jialingjiang Formation (T1j2L) is mainly composed of anhydrite, dolostone, limestone, and siliciclastic rocks, providing a rare opportunity to reconstruct detailed facies in a [Formula: see text] 3D seismic survey with 31 wells. Wireline logs (sonic, density, and gamma ray) calibrated by core analysis are essential in distinguishing anhydrite, siliciclastics, and carbonates. Although different lithologies are characterized by different acoustic impedance (AI), with certain overlapping, it is still difficult to predict lithology by any single seismic attribute because of the limited seismic resolution in a thinly interbedded formation of multiple lithologies. In our study, principal component analysis (PCA) was applied to extract lithologic information from selected seismic attributes; the first two principal components were used to predict the content of anhydrite, siliciclastics, and carbonates. Content maps of anhydrite, siliciclastics, and carbonates — created by mixing the represented color — were used to reconstruct lithofacies of the T1j2L submember. It is quite difficult, even with the PCA approach, to uniquely resolve the three lithologies due to the overlapped AI and the limited resolution of the seismic data. However, the workflow that we evaluated dramatically improved the prediction accuracy of lithology and lithofacies. Facies transition during the deposition of the T1j2L submember in the study area was inferred from a paleo-uplift in the southwest to a restricted lagoon and then to an open marine setting in the northeast.