Abstract
Carbonate reservoir characterization is often a complex task, due to the interplay between primary processes (e.g. depositional environments, facies changes) and secondary processes (e.g. burial, diagenesis, faulting and fracturing, cementation). In order to properly characterize and model such a reservoir, it is paramount to unravel the order by which such processes have affected the rock, leading to the present day petrophysical properties.
In the presented case study (onshore dolomitized carbonate reservoir in Central Asia), a multi-step approach was taken for its characterization and modelling. The characterization phase was focused in understanding the key processes and controls on porosity and permeability. From the core and log data, a detailed sedimentologic and diagenetic study was performed, to identify the depositional environments and facies, as well as the pore system geometry, and its impact on fluid flow. Furthermore, several trends on reservoir quality were identified, related to faults, and associated with depositional cyclicity.
From the above work, a reservoir model was built, to support field development planning and associated uncertainties. A structural and stratigraphic framework was built, and Flow Unit Types (FUT) were defined using seismic, cores, thin sections, logs and mercury injection capillary pressure data (MICP). Property modelling was carried out for porosity and permeability, honouring FUT, depositional and diagenetic trends. In particular, two trends were modelled: a fault-related trend, to introduce the impact of diagenetic leaching related to faults (observed in core data); and a cyclicity related trend, to introduce the impact of preferential fluid flow pathways that occur at or near cycle tops. The uncertainty in the reservoir property models was evaluated with different FUT, driven by depositional and diagenetic concepts.
The results indicate that a significant improvement in reservoir understanding can be achieved with the use of an integrated study and model workflow, focusing on the key control factors that affect the pore system and the distribution of permeability. In this way it was possible to recognize spatial trends and capture the relationship between petrophysical properties, pore architecture and sweep efficiency.
