Identification of Recovery Improvement Opportunities for a Brownfield Deepwater Asset Using Analytic Methods

Abstract Identifying opportunities to improve hydrocarbon recovery in a brownfield is usually preceded by an assessment of the effectiveness of the development strategy and the gap to potential ultimate recoverable. In recent times, the use of numerical reservoir modeling techniques has dominated the assessment of reservoir performance and prediction, leading to an improved understanding of reservoir and production systems. Despite the obvious benefits of numerical reservoir models, the development of robust reservoir models is resource-intensive and, thus, can be less attractive (on a cost-versus-benefit basis) for certain projects. In situations such as this, engineers often deploy classical analytical techniques to assess reservoir performance and predict performance within the limitations therein. This paper presents how analytical methods were used in assessing the recovery potential of a matured reservoir system, thus driving decisions on ways to improve the asset value of the brownfield. The reservoir is situated in a deep-water turbidite environment and has twelve (12) water and four (4) gas injection wells and twenty-seven (27) oil producers. Production commenced in 2006 and peaked at 207 Mbopd. Currently, production has declined to an average of 64 Mbopd, with rapidly increasing water cut and Gas-Oil-Ratio trends in some wells, among other production challenges. This decline necessitated the need for a review of the system to identify short- to medium-term opportunities to arrest the production decline. The legacy subsurface models for the reservoir were deemed not reasonably representative as the performance history could not be replicated with these models. Thus, the subsurface team deployed a fit-for-purpose value-adding alternative workflow to address a prioritized list of key asset gaps within the agreed timeframe. The workflow involved using a collection of analytic techniques such as Recovery Factor versus initial Hydrocarbon Pore Volume Curves, Reservoir Management Dashboard, etc. to understand the gas and water flood performance in the field, identify opportunities to optimize recovery, generate a range of estimates for the gap to potential, etc. Thus, deepening the integrated understanding of the reservoir. The knowledge built from the study formed the basis for the development of an updated reservoir management strategy for the reservoir.