Multi-attribute Comprehensive Prediction of Thin Sand and Mudstone Reservoirs in the Slope Belt of the Orient Basin in South America

Abstract

Orient basin of Ecuador locates in the north of sub-Andes foreland basin chain in South America. The major target for oil and gas exploration in its eastern slope zone are M1, U and T formations of Cretaceous Napo group which characterize thin clastic reservoir with average thickness 8.5 ft of sandstone reservoir. Reservoir distribution is difficult to be predicted with conventional data which restricts oil and gas exploration in this area. Confronting to geological difficulty in study area, one special techniques pointing to solve fine description and prediction for thin sandstone have been adopted, which is multi-dimension and multi-attribute reservoir comprehensive prediction. Based on the high resolution seismic data obtained by frequency band recovery and utilized data-driven artificial intelligence algorithm, fine prediction and description for thin reservoir with thickness of 8–10 ft can be achieved which guarantees trap recognition and description for thin reservoir and obtains excellent onsite results through seismic attribute analysis and optimization, high resolution frequency spectrum decomposition, seismic impedance inversion. One new discovery has been discovered in the south of block after application of this technology, and several newly drilled appraisal wells succeed.KeywordsOrient BasinSeismic frequency band recoveryData-driven artificial intelligence algorithmNonlinear combinationMulti-dimension and multi-attribute reservoir comprehensive prediction