Using Synthetic Production Data from an Open Source Carbonate Reservoir Model to Improve our Understanding of Flow Behaviour

Abstract

This work presents a new open access carbonate reservoir case study that uniquely considers the major uncertainties inherent to carbonate reservoirs using one of the most prolific aggradational parasequence carbonate formation sets in the U.A.E., the Upper Kharaib Member (Early Cretaceous), as an analogue. The ensemble considers a range of interpretational scenarios and geomodelling techniques to capture the main components of its reservoir architecture, stratal geometries, facies, pore systems, diagenetic overprints and wettability variations across its shelf-to-basin profile. Fully anonymized data from 43 wells across 22 fields in the Bab Basin in the U.A.E from different geo-depositional settings and height above the free water level (FWL) was used. The data comprises of a full suite of open-hole logs and core data which has been anonymized, rescaled, repositioned and structurally deformed; FWLs were normalized and the entire model was placed in a unique coordinate system. The resultant static and dynamic models(s) capture the geological setting and reservoir heterogeneities of selected fields but now at a manageable scale. Synthetic production data has been generated by adding wells to an undisclosed ‘truth case’ model to obtain field-wide and well-by-well production data (oil, gas, and water rates, bottom-hole pressures etc.) from simulation runs. The original oil in place (OOIP) and reserves that have been computed from these models are synthetic and unique. Here we present an initial field development plan and corresponding reservoir simulations that showcase the heterogeneity inherent to the model and demonstrate the variability of the flow and storage capacity of the different reservoir architectures found in and around the Bab Basin. This is an example application of how we can use synthetic production data to improve our understanding of flow behaviours in carbonates. The novelty of our work is the provision of a unique open access dataset which enables reproducible science in the field of reservoir characterisation and simulation, and helps training new generations of geoscientists and reservoir engineers in the art of characterising, simulating and predicting the reservoir performance of carbonate reservoirs under different recovery processes.