An efficient optimization of well placement and control for a geothermal prospect under geological uncertainty

Journal Article · Sun Oct 19 00:00:00 EDT 2014 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2014.10.036· OSTI ID:1809196

Chen, Mingjie ^[1]; Tompson, Andrew F.B. ^[2]; Mellors, Robert J. ^[2]; Abdalla, Osman ^[3]

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1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sultan Qaboos Univ., Muscat (Oman)
2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
3. Sultan Qaboos Univ., Muscat (Oman)

This work applies an efficient optimization technique based on a multivariate adaptive regression spline (MARS) technique to determine the optimal design and engineering of a potential geothermal production operation at a prospect near Superstition Mountain in Southern California, USA. The faster MARS-based statistical model is used as a surrogate for higher-fidelity physical models within the intensive optimization process. Its use allows for the exploration of the impacts of specific engineering design parameters in the context of geologic uncertainty as a means to both understand and maximize profitability of the production operation. The MARS model is initially developed from a training dataset generated by a finite set of computationally complex hydrothermal models applied to the prospect. Its application reveals that the optimal engineering design variables can differ considerably assuming different choices of hydrothermal flow properties, which, in turn, indicates the importance of reducing the uncertainty of key geologic properties. The major uncertainty sources in the natural-system are identified and ranked first by an efficient MARS-enabled total order sensitivity quantification, which is then used to assist evaluating the effect of geological uncertainties on optimized results. At the Southern California prospect, this parameter sensitivity analysis suggests that groundwater circulation through high permeable structures, rather than heat conduction through impermeable granite, is the primary heat transfer method during geothermal extraction. Reservoir histories simulated using optimal parameters with different constraints are analyzed and compared to investigate the longevity and maximum profit of the geothermal resources. The comparison shows that the longevity and profit are very likely to be overestimated by optimizations without appropriate constraints on natural conditions. In addition to geothermal energy production, this optimization approach can also be used to manage other geologic resource operations, such as hydrocarbon production or CO₂ sequestration, under uncertain reservoir conditions.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Office
• Grant/Contract Number: AC52-07NA27344
• OSTI ID: 1809196
• Alternate ID(s): OSTI ID: 1247573
• Report Number(s): LLNL-JRNL--652422; 772854
• Journal Information: Applied Energy, Journal Name: Applied Energy Journal Issue: na Vol. 137; ISSN 0306-2619
• Publisher: Elsevier
• Country of Publication: United States
• Language: English

Related Subjects

15 GEOTHERMAL ENERGY
geothermal
optimization
sensitivity
surrogate
uncertainty