Designs for Risk Evaluation and Management, or DREAM, is a tool that generates and optimizes monitoring programs for detecting potential leaks from geological carbon storage. DREAM analyzes outputs from full-physics simulators, geophysical models, or reduced order models and uses probabilistic and heuristic algorithms to identify the best monitoring network based on user-defined objectives and constraints.
DREAM is a tool for leakage monitoring design and optimization at geological carbon storage (GCS) sites. The National Risk Assessment Partnership’s (NRAP’s) DREAM tool was developed to assist in the design of effective and efficient GCS leakage monitoring networks (Yonkofski et al., 2016, 2019). DREAM searches the solution space for ensembles of leakage simulations to find the optimal monitoring design to minimize objectives, such as time to leak detection, cost, and percent of leaks detected. To accomplish this, DREAM uses a computationally-efficient simulated annealing approach that interactively mutates potential monitoring schemes. The tool can accept simulation output from full-physics numerical simulators, reduced-order models, or from integrated assessment models generated in NRAP-OPEN-IAM. It can account for spatial and temporal monitoring constraints, limitations in monitoring technology detection capability, and budget constraints (cost or monitoring equipment availability). Recent demonstrations of coupled application of DREAM and NRAP-Open-IAM highlights the value of effective monitoring design to build confidence in GCS containment effectiveness and to support justification for early site closure (Bacon et al., 2019).
For more information on DREAM, please access the PNNL website link and github repository under Resources.
Additional relevant publications:
Bacon, D.H.; Yonkofski, C.M.; Brown, C.F.; Demirkanli, D.I.; Whiting, J.M. (2019). Risk-based post injection site care and monitoring for commercial-scale carbon storage: Reevaluation of the Future. Gen 2.0 site using NRAP-Open-IAM and DREAM. Intl. J. Greenhouse Gas Control, 90, 102784.
Yonkofski C., G.D. Tartakovsky, N.J. Huerta, and A.M. Wentworth. 2019. "Risk-Based Monitoring Designs for Detecting CO2 Leakage through Abandoned Wellbores: An application of NRAP's WLAT and DREAM tools." International Journal of Greenhouse Gas Control 91. PNNL-SA-140291. doi:10.1016/j.ijggc.2019.102807
Yonkofski C.; Davidson, C.L.; Rodriguez, L.R.; Porter, E.A.; Bender, S.R.; Brown, C.F. (2017). Optimized, budget-constrained monitoring well placement using DREAM. Energy Procedia, 114, 3649-3655.
Yonkofski, C. M.; Gastelum, J. A.; Porter, E. A.; Rodriguez, L. R.; Bacon, D. H.; Brown, C. F. (2016). An optimization approach to design monitoring schemes for CO2 leakage detection. Intl. J. Greenhouse Gas Control, 47, 233–239.