Oil is produced from an Aptian carbonate reservoir averaging 400ft thick with complex internal<br>reservoir architecture. The lower reservoir units comprise continuous platform and ramp carbonate<br>layers deposited during overall transgression. A platform dominated by stacked patchy rudist build-ups<br>and inter build-up ponds developed in the south of the field during later aggradation. Rapid water<br>advance along high-permeability layers led to irregular water fingering which must be captured in the<br>static and dynamic models.<br>Facies architecture and property distributions are very different in the central highstand progradation<br>and northern late highstand clinoform domains dominated by more steeply dipping reservoir units (1-3<br>degrees). Non-reservoir carbonate mudstones associated with transgression form local flow barriers<br>confirmed by pressure and production data.<br>Different strategies were used in structural and property model building to account for heterogeneities<br>across the field. The southern platform interior with rapid facies variations of non-reservoir ‘pond’<br>facies and stacked coral/rudist shoals was modeled using well data combined with seismic attributes.<br>Production in the north is supported by peripheral water injection, WAG pattern and line-drive gas<br>injection. Deterministic mapping of 3rd and 4th order clinoform sequences is critical for understanding<br>fluid movement. A key modeling challenge was to accurately represent the clinoform geometries. With<br>dips up to 3 degrees downlap of layers occurs within 1-2km, resulting in ambiguous well-based<br>correlations. High-quality seismic data was used to map clinoform ‘corridors’ and constrain reservoir<br>thickness. Stochastic methods (SGS) guided by a deterministic layering framework and controlled by a<br>core/log-based lithofacies model were used to populate the petrophysical properties. The central area<br>comprises a thick succession of good reservoir quality facies with ‘transparent’ seismic character.<br>Recent seismic analysis has led to the recognition of clinoforms although they could not be mapped<br>deterministically. An architecture was established using well correlation guided conceptually by the<br>overall clinoform shape.


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