Characterizing reservoir architecture and fluid property distributions at the early exploration and appraisal stage are critical for reservoir assessment, planning and management. Particularly for thinly laminated reservoirs, identification of hydrocarbon-bearing zones and determination of the flow unit sizes have profound impact on long term production predictions. In this paper, a case study is presented that integration of reservoir fluid property distribution with other logs leads to accurate reservoir understanding. In this method, downhole fluid analysis (DFA) is used to identify key production parameters of reservoir fluids in real time and at downhole conditions. DFA results are combined with other logs to develop a view of reservoir architecture especially pinpointing thin pay zones with low resistivity, which could be treated as wet by open-hole logs. Indeed, 19 DFA stations were performed in this particular well and represents a typical number of DFA stations per well in this field (another well in this field had significantly more DFA stations that established a world record). The results of the improved interpretation are confirmed by subsequent well test data. The case study indicates that the methodology of integrating DFA with other logs provides a powerful and cost effective approach for reservoir understanding and assessment at the exploration stage, which is invaluable for optimal reservoir management and development planning.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.