A tool for leakage monitoring design and optimization at GCS sites. NRAP’s DREAM tool was developed to assist in 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 placement of monitoring devices in order to minimize the time to leak detection. 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, from reduced-order models, or from integrated assessment models. It can account for spatial and temporal monitoring constraints, limitations in monitoring technology detection capability, and budget constraints (cost or monitoring equipment availability). Recent demonstration 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).
DREAM v2.0 can be downloaded from the NRAP Tools Collaborative Workspace on the National Energy Technology Laboratory’s (NETL) Energy Data Exchange (EDX).
- Sign into EDX and find the DREAM v2.0 tool materials at https://edx.netl.doe.gov/workspace/resources/nrap-tools
- Must be a member of the NRAP Tools EDX workspace to access
- Download an executable; DREAM_2.0_Windows.jar or DREAM_2.0_Mac.jar
- Download the documentation
- Download the example datasets
- Run (double click) executable
- Follow along with examples in the documentation
- DREAM requires Java Runtime Environment (JRE) version 8 or newer.
- Please update to the latest version of Java if you are having issues running the application.
User Manual for DREAM v2.0 (https://edx.netl.doe.gov/workspace/resources/nrap-tools) (Must be a member of this EDX workspace to access)
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 FutureGen 2.0 site using NRAP-Open-IAM and DREAM. Intl. J. Greenhouse Gas Control, 90, 102784.
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.
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.