An Effective Iterative Workflow towards an Improved History Match of a Highly Heterogeneous Giant Offshore Carbonate Reservoir - Challenges and Lessons Learned

Abstract

The subject reservoir has been on production for decades and suffered early water breakthrough due to significant geologic heterogeneity. The existing dynamic model was last history matched in 2010, and the match quality had deteriorated over the last few years of production life. Significant volume of new data had become available, including SCAL, cores, wireline logs, production and surveillance data which were recently leveraged to update the static model based on new geomodelling best practices. The justification for progressing to history match the new static model was the business need for a fit-for-purpose tool required to support the life cycle development and management strategy for the reservoir which is evolving from 5-spot flood scheme to line drive utilizing state of the art pilot well technology. Water channeling is an important phenomenon in the stratigraphically zoned reservoir, and since some of the diagenetic features are co-located at the same intervals, identifying which are key actors for fluid flow was one of the greatest challenges encountered, hence the adoption of fluid travel time concept for mapping and tracking of preferential flow pathways, and for accelerated history match learnings. Intensity attribute measured in count per foot for diagenetic features underpinned spatial permeability modification for model calibration. However, history match changes which include facies intensity modification, footprint and geometry adjustment, permeability magnitude, etc were not just expedient on achieving history match but were all data supported and fed through a closed iterative geo-engineering loop for geologic plausibility and consistency verification prior to been incorporated in the dynamic model. A good history match was achieved for all calibrated parameters, and the near-perfect vertical conformance prediction of 10 recently acquired water saturation logs is a confirmation of the integrity and predictive capability of the New Generation Model.