3D Imaging of Porosity Modifying Phases in Shuaiba Reservoir, Al Shaheen Field

Existing porosity and permeability predictions in the Shuaiba reservoir of the Al Shaheen Field are largely based on detailed core observations and measurements that have been integrated with geochemical data and linked to robust conceptual models. This approach has been successful at predicting general porosity and permeability trends mainly related to deposition on the platform, barrier and basinal environments and the processes of dissolution and cementation; however, there is a lot of uncertainty in correlating and predicting the spatial variation of dissolution and cementation styles within each depositional environment. This uncertainty becomes larger when trying to identify rock types for petrophysical prediction and also to correlate the diagenetic patterns at field scale. The work summarized in this contribution demonstrates how we have gone beyond the classic characterization of diagenesis and have moved toward the quantification and 3D visualization of diagenetic products that modify the pores and pore throats. Present day porosity and permeability of the Shuaiba limestones in the platform area has been significantly modified by calcite and minor pyrite cementation, hence in this study detailed and calibrated paragenetic data have been integrated with 2D quantitative mineral and elemental maps obtained with the use of QEMSCAN and coupled with 3D images using an in-house micro-CT scanner. Meticulous segmentation of grey levels in the 3D micro-CT images allowed the recognition and quantification of the cement phases and corresponding porosity before cementation, which could then be reconstructed and used to assess the porosity at any given diagenetic stage. This integrated, object-based, approach has the potential to significantly improve our ability to identify rock types, to help predict the spatial distribution of porosity and permeability in the Shuaiba reservoir and to ultimately improve realizations of reservoir connectivity for flow simulation.