Maximizing Recovery in a Mature Rich Gas Condensate Field: Using Rate Transient Analysis to Identify Infill Opportunities

Rate Transient Analysis (RTA) is a powerful technique in petroleum engineering that can be used to diagnose reservoir behavior, leading to better reservoir understanding and production optimization. In this study, RTA was used as a simple and agile analytical technique for the Field A reservoir. Field A is a rich tight gas condensate reservoir in a complex structure composed of six sub-units with varying geological characteristics located in Oman's north Field. The main purpose of this study was to understand the connected volume seen by existing wells and thereby identify sweet spots for future infills that would help maximize field recovery. A clear and structured approach was followed in this study. First, the gap to top quartile was defined with an understanding of reservoir challenges and reservoir data uncertainties. Second, data were gathered to apply basic analytical techniques. Third, the analytical technique Blasingame was used to history match the connected pore volume. Fourth, a numerical technique was used to match the analytical approach, where the condensate banking effect was considered. Finally, the connected volume was estimated per well, and drainage areas were marked on a map to identify potentially undrained areas and infill opportunities. Individual well RTA was performed for two blocks of the Field A reservoir, the East and West blocks, consisting of 31 wells in total. The effect of condensate dropout on the effective permeability-thickness (kh) of the reservoir was inferred from RTA. Well-level numerical models were generally able to match condensate-gas ratio decline trends and the effective kh reduction due to condensate banking. Changing skin was observed in many of the RTAs (initial negative skin gradually going towards 0), indicating gradual closure of hydraulic fractures. The study results indicate nine potential infill opportunities in both blocks of the Field A reservoir. The identified infill opportunities were ranked through economic evaluation, considering factors such as the cost of drilling and completing new wells, the expected increase in production rates, and the projected increase in reserves. This study provides valuable insights for enhancing field performance and consequently improving field recovery. The study represents an agile approach in how field understanding, opportunities identification, and maturation can be developed quickly yet effectively using existing data and limited manpower in a limited time frame. RTA offers efficient analysis of changing reservoir and well conditions, surpassing limitations of traditional methods and dynamic simulation, providing a practical alternative for identifying infill opportunities and optimizing production strategies. The approach used can be replicated for other similar reservoirs, and the results have significant implications for the petroleum industry.