Successful Delineation of Sand Bodies to Improve Carbon Capture and Storage Reservoir Modelling, A Case Study from the North Malay Basin, Gulf of Thailand

Abstract The objective of this study is to characterize sand reservoirs by using seismic inversion technique, the results were used to support CO2 storage potential identification and reservoir modeling works (storage volume calculation). The key storage targets are the saline aquifers and depleted reservoirs. These main targets were interpreted as a deposition of distributary channels occurring in the Paleo Chao Praya delta plain during Miocene. The results of this project contribute to a more accurate volume calculation for CO2 storage capacity. A rock physics feasibility analysis was carried out to understand a link between the observed seismic responses and the rock properties. Based on conclusions made in the rock physics analysis, P-Impedance could be used to delineate sand reservoir from shale, thus, a post-stack deterministic seismic inversion was selected for this reservoir characterization. Bayesian litho-classification method justifies lithology types by Probability Density Function (PDF) of P-Impedance, the resulting PDF was then applied to the inverted relative P-Impedance to create sand probability and lithology (most probable) volumes. Then, posterior validation of the lithology classification results was performed by investigating the match between the actual upscaled lithology log and pseudo lithology log from the Bayesian classification. Furthermore, the sand probability maps of the target reservoirs show an acceptable sand distribution response to the distributary channels in lower coastal plain environment that is consistent with the well results. The results of this work demonstrate how quantitative interpretation (QI) can successfully improve confidence in sand reservoirs mapping, in an area of complex faulted reservoir interval. The results presented here are beneficial for storage potential identification and reservoir modeling part, which can provide a more precise estimation of CO2 storage volume. The final results of the QI study provide good quality seismic inversion products and lithology cube, which enabled sand delineation at the target CO2 storage level. The key contributors have been ensuring optimal seismic input data, being in this case achieved through using a PSDM seismic processing technology, careful parameterization of seismic inversion process, and utilization of Bayesian classification method for lithology classification.