The challenges to effectively manage a field with stacked reservoirs that are in known hydraulic communication are enormous. Conventional management of such fields can result in many undesired outcomes such as premature water production caused by cross-communication from different reservoirs, inefficient pressure support to some of the individual reservoirs, or large volumes of bypassed oil. The major challenge is to identify the reasons and magnitude of inter-reservoir communication, and accurately capture these in the models which are utilized for optimized well placement and efficient field development. This paper discusses an integrated multi-disciplinary approach to identify and model inter-reservoir communication in a giant offshore carbonate field from UAE. Tracer study conducted for several years combined with detailed seismic interpretation suggest that the cross-flow of reservoirs due to fault juxtapositions is the major cause of inter-reservoir communication. This observation is further supported by pressure-transient analysis, logs, cores, drilling reports and regional structural studies. Hence, it becomes absolutely essential to build a robust static and dynamic model that can accurately capture the communication between different reservoirs. This paper proposes a novel approach to build a full-field integrated framework that allows coupling of multiple reservoirs that have been previously modeled independently. The methodology includes; detailed reinterpretation of faults and key chronostratigraphic surfaces, qualitative/ quantitative attribute analysis using reprocessed 3D seismic (post-stack time migrated) data, interpretation of pressure transit analysis, logs, surveillance data and regional structural history studies. The updated framework ensures accurate fault throw and fault extension in order to capture fault juxtapositions. The ability of the new model to allow inter-reservoir communication has been tested and confirmed in dynamic simulation model. This was achieved through series of simulation sensitivities where tracers injected in wells targeting specific reservoirs were successfully sampled from different reservoirs due to inter-reservoir communication through fault juxtaposition. Based on the results of sensitivity test, it is expected that the new integrated framework will provide a much improved history match in faulted areas where cross-communication across reservoir is very prominent. The improved model will lead to a better understanding of field and possibly will be used as guidance for field development plan.

As part of the ongoing development of a large offshore oil field, an asset owner places a strong emphasis on continuous improvement of the established framework for integrated post-drill well analysis. The geology of the candidate field is complex and the occurrence and distribution of the extreme permeability features that dictate early water production is highly uncertain. While much effort is devoted to mitigating their adverse impact through proper integration of surveillance data for accurate well planning, post-drill outcomes can still diverge significantly from pre-drill expectations. Several wells have been drilled in the production build-up campaign, including ground-breaking pilots and many more are following in very quick succession as part of the life cycle strategy for the field. Due to high drilling frequency, the challenges of assimilating learnings through conventional post-drill analysis for optimization of future drill wells can be enormous. To apply key lessons from these wells in building quick baseline knowledge for reservoir model update and drill plan optimization, the modeling and development team have developed an improved workflow for integrated post-drill analysis. The workflow leverages the full benefit of collaboration between multi-disciplinary teams to integrate 3D seismic data, multiple well information (including geologic reports, well logs and petrophysical results) and surveillance data from new drill wells to benchmark pre-drill expectations. An important aspect of the approach is the quick incorporation of drilling results into static and dynamic models via a cycled, closed-loop workflow for quick assessment of model fidelity through an evergreen update process. A multifunctional post-drill analysis facilitates critical consideration of well results to capture significant learnings that influence future drill well and data acquisition optimization, reservoir model history match and prediction enhancements, and identification of drilling hazards and geological features that affect reservoir performance. This paper describes the methodology used to plan and implement post-drill well analysis within a fast paced and high drill frequency environment. Key elements of the methodology are described through the use of a case study example, and include: Standardized subsurface workflow, comparison of post-drill well results with pre-drill well expectations, identification and documentation of significant observations and lessons learned improvement of history match & predictive capability of reservoir models and integration with other drill-well delivery processes.