Intelligent Completions Design and Production Optimization: Application Reality Now Versus the Future In Digital Oilfield
- Kim Fah Gordon Goh (Schlumberger Technology Corporation, Houston US) | Shripad Biniwale (Schlumberger Abingdon Technology Center, UK) | Rashid Musayev (Schlumberger Technology Corporation, Houston US) | Mohamed Ahmed Elfeel (Schlumberger Abingdon Technology Center, UK)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 26-29 October, Virtual
- Publication Date
- Document Type
- Conference Paper
- 2020. Society of Petroleum Engineers
- 2 Well completion, 2.3 Completion Monitoring Systems/Intelligent Wells, 2.3.6 Tubular Optimisation, 3.2 Well Operations and Optimization, 3 Production and Well Operations, 3.2.7 Lifecycle Management and Planning, 2.1.3 Completion Equipment
- Production Optimisation, Digitalization, Inteligent Completions, flow control valve, Integrated Operation
- 27 in the last 30 days
- 89 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 28.00|
Intelligent Completions (IC) are deployed with the high hopes of frequent data utilization and zonal selectivity maneuver to optimize production continuously. The permanent downhole presence of measurements like pressure, temperature, rate, water-cut, gas-break provide downhole indicators and trending analysis of production performance and injection conformance. These are utilized not only to maximize hydrocarbon production but also to reduce surface handling of water and/or gas, improve injection efficiency, and reduce carbon and environmental footprint. However, the reality could be different from the evaluation stage to the application stage. The asset production engineers or the reservoir engineers face real challenges when it comes to design, downhole installation, data transmission, real-time analysis, and optimization to deliver the real value of the initial investment. These suboptimal application factors, multiplied by the complexity of IC deployment and execution with existing hardware constraints, have limited the progression towards digital well technology. By analyzing such trends, a new advanced completion optimization methodology has been devised, leveraging the latest technology and innovation, IC deployment simplification, and electrification efforts in the industry.
This paper analyses the underutilization reasons of digital well technology, such as - the ability of design and implementation, the downhole data measurement, complexity of modeling and optimization, and the bottlenecks in applying the learning from the Intelligent Completions data to optimize production. It is then compared to the easing transition to the future digital-wells, advanced modeling capabilities that are driving the oilfield digitalization by next-generation Intelligent Completion. This digital transition ranges from ease-of-deployment to ease-of-optimization and eventually towards cloud-enabled decision making. The new era of IC electrification deployment and digital solutions are twinning to provide an integrated platform to maximize value and justification for more future digital wells.
A fully digital system to control reservoir and optimize the product is becoming a reality with the transformation of modeling capability and enabled by simplification of IC deployment, and this is the digital future of IC optimization. This digital solution is continuously feeding asset subsurface, modeling, and optimization team with productivity or injectivity indexes and other inputs required for reservoir steady-state and transient evaluation. The IC industry continues to be integrating into the new solution frontiers of logging-while-producing, the testing-while-producing capability to the eventual optimizing, modeling-while-producing future, leading towards a true digital oilfield of the future.
|File Size||1 MB||Number of Pages||15|
Ahmad, M., Sayung, C.L., Muzahidin, M.S., Som, M.K., Wong, L.H., Biniwale, S., Erziyati, N., Soh, K., Roland, H., Nghia, VT and Ee, LC, 2015, March. Samarang Integrated Operations (IO)–Achieving Well Performance Monitoring, Surveillance & Optimization Through Data and Model Driven Workflows Automation. In SPE Digital Energy Conference and Exhibition. Society of Petroleum Engineers.
Ahmed Elfeel, M., Tonkin, T., Watanabe, S., Abbas, H., Bratvedt, F., Goh, G., Gottumukkala, V. and Giddins, MA, 2018, November. Employing Smart Flow Control Valves for Fast Closed-Loop Reservoir Management. In Abu Dhabi International Petroleum Exhibition & Conference. Society of Petroleum Engineers.
Dilib, F. A., & Jackson, M. D. 2012. Closed-loop Feedback Control for Production Optimization of Intelligent Wells under Uncertainty. Society of Petroleum Engineers. doi:10.2118/150096-MS
Grebenkin, I. M., & Davies, D. R. 2012. A Novel Optimisation Algorithm for Inflow Control Valve Management. Society of Petroleum Engineers. doi:10.2118/154472-MS
Ilamah, O., & Waterhouse, R. 2018. Field-Scale Production Optimization with Intelligent Wells. Society of Petroleum Engineers. doi:10.2118/190827-MS
Ramizah, A.R., Gordon, G.K., Tina, L.L., Varma, G., Muzahidin, M.S., Willem, S., Ahmad, S.H., Sanggeetha, K., Lester, T.M., Khairul, A.M. and Mabel, C.P., 2017, October. Real-time Surveillance and Analysis Tool for Intelligent Completion-An Ultimate Solution to Oil Recovery and Integrated Operation. In SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition. Society of Petroleum Engineers.
Vasper, A., Mjos, J. E. S., & Duong, T. T. T., 2016. Efficient Optimization Strategies for Developing Intelligent Well Business Cases. Society of Petroleum Engineers. doi:10.2118/181062-MS