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SUBPRO - Production Optimization Dinesh Krishnamoorthy, NTNU
SUBPRO SUBSEA PRODUCTION AND PROCESSING SUBPRO - Production Optimization Dinesh Krishnamoorthy, NTNU © Statoil ASA © 2016 SUBPRO/NTNU. Distribution, copying and publishing only with written consent from NTNU
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Outline Introduction to SUBPRO Digitalization and Automation in SUBPRO
Production Optimization Handling uncertainty Conclusion
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Industry partners: Commercial utilization
SUBPRO SUBPRO Still gaps in knowledge and technology for subsea systems and solutions, that may: increase the recovery from existing fields enable developments of new and more demanding oil and gas fields reduce cost and complexity of subsea field developments Many future challenges require multi-disciplinary collaboration Help industry to accelerate the level of innovations within selected areas of the subsea oil and gas field NTNU: Research Åsgard SGC, Photo: Øyvind Hagen, Statoil ASA Industry partners: Commercial utilization Innovations
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SUBPRO’s objective & goals
The primary objective of the center is to become a global leader for research based innovation within subsea production and processing NTNU: Research Industry partners: Commercial utilization International excellence in fundamental and applied research Knowledge, methods, technology and system understanding – as basis for industrial innovation Internationally high level of graduated master and PhD candidates Innovations
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SUBPRO Partners
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Laboratories and test rigs
SUBPRO Laboratories and test rigs Ugelstad laboratory Specialized in surfactant chemistry and flow assurance Laboratories for testing of: Droplet breakage Solvent characterization Membranes New test rigs at the Dept. of Petroleum Engineering and Dept. of Production and Quality Engineering Focus on: Test of compact separation concepts, for bulk separation Test of process control and operation of compact separation equipment
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SUBPRO Field architecture Sigbjørn Sangesland RAMS Mary Ann Lundteigen
Separation – Fluid characterization Gisle Øye Separation - Process Concepts Hugo Jakobsen System Control Sigurd Skogestad Subsea gate box Mariana Diaz New safety and control philosophy for subsea HyungJu Kim Produced water quality Marcin Dudek Membranes for gas dehydration Kristin Dalane Dynamic simulation model library Christoph Backi Field development concepts Diana Gonzalez Reliability and availability in design Juntao Zhang Wax deposition Jost Ruwoldt Membranes for gas dehydration (experim.) Mahdi Ahmadi Modelling for control of subsea processes Torstein Kristoffersen Multiphase boosting models Gilberto Nunez Condition and prognostic maintenance Yun Zhang Sequential separation Are Bertheussen Combined H2S and hydrate control Eirini Skylogianni Adaptive control of subsea processes Sveinung Johan Ohrem Optimizing condition monitoring Himanshu Srivastav Modeling of coalescence Aleksandar Yordanov Mehandzhiyski Characterization of particle breakup Nicolás La Forgia Process control algorithms Mishiga Vallabhan Fluid particle breakage Eirik Helno Herø Estimation of un-measured variables Tamal Das Compact separation Håvard Slettahjell Skjefstad Enhanced virtual flow metering Timur Bikmukhametov Control for extending component life Adriaen Verheyleweghen Production optimization under uncertainty Dinesh Krishnamoorthy
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Systems Control SUBPRO 3.4 Model library:
Collect, integrate and manage simulation models of subsea equipment 3.5 Modelling and multivariable control of subsea systems: Develop formalisms for control of subsea systems 3.6 Control of subsea processes: Test of control strategies for demanding processes, like compact equipment 3.7 Estimation of un-measured variables: Model-based estimation of process parameters 3.8 Control for extending component life: Control strategies for extending remaining useful life 3.9 Production optimization Robust modelling for production optimization 3.10 Enhanced virtual flow metering Improve multiphase flow rate estimation 3.11 Process Control Algorithms
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SUBPRO Digitalization New digital technologies combined with data-driven insights can transform oil and gas operations
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3.9 Production Optimization
SUBPRO 3.9 Production Optimization Integrating real time data into real time decision making
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Daily Production Optimization
SUBPRO Daily Production Optimization Optimal decision variables Process constraints Economic Model System Model Production optimization – How to operate the field in an economically optimal way Need to take decision on production targets, allocation of reseources etc Challening for a large network with complex subsea tie-ins Often requires mathematical optimization techniques. In industry today – Use Prosper and GAP Troll Field in the Norwegian Continental shelf. Source:
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Modelling – prone to uncertainty
SUBPRO Modelling – prone to uncertainty External Disturbance unmeasured unknown Physical models Lack of knowledge Simplification Well tests Sparsity of tests Unreliable for subsea Process uncertainty Production Optimization Parametric uncertainty Structural uncertainty But the well models are prone to uncertainty Measurement uncertainty Market uncertainty
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Production Optimization
SUBPRO Production Optimization max $ 𝑜 𝑞 𝑜 + $ 𝑔 𝑞 𝑔 − $ 𝑔𝑙 𝑞 𝑔𝑙 + … 𝑠.𝑡 𝑞 𝑔 ≤ 𝑄 𝑔 𝑚𝑎𝑥 Ideal case uncertain models uncertain models Constraint violation Unused capacity Start optimization
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Motivation Gas capacity constraint Nominal case: Prioritize well 2
SUBPRO Motivation 𝑞 𝑔 ≤ 𝑞 𝑔 𝑀𝑎𝑥 Well 1 Well2 GOR 30 25 ±2 ±10 1 2 Gas capacity constraint Nominal case: Prioritize well 2 worst case: Prioritize well 1
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Step-by-step approach to uncertainty
SUBPRO Step-by-step approach to uncertainty Step 1: Data analysis to identify and characterize uncertainty Step 2: Uncertainty propagation Step 3: Optimization under uncertainty
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Optimization under uncertainty
SUBPRO Optimization under uncertainty
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Adaptive optimization
SUBPRO Adaptive optimization Use real time data to update models online Re-compute new optimal setpoints
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Adaptive optimization
SUBPRO Adaptive optimization
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Scenario optimization
SUBPRO Scenario optimization Optimize over different possible scenarios !
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Conclusion Digitalization and automation is key.
SUBPRO Conclusion Digitalization and automation is key. Production optimization under uncertainty crucial for efficient subsea operations. Step-by-step approach to handling uncertainty. Optimization under uncertainty - Adaptive or Scenario appraoch
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Thank you ! SUBPRO SUBSEA PRODUCTION AND PROCESSING
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