Abstract
well-defined risk and deviation measures. As the model-based economic optimization of the water-flooding process in oil reservoirs suffers from high levels of uncertainty, the concepts from the theory of risk are highly relevant. In this paper, the main focus is to offer an asymmetric risk management, i.e., to maximize the lower tail (worst cases) of the economic objective function distribution without heavily compromising the upper tail (best cases). Worst-case
robust optimization and Conditional Value-at-Risk (CVaR) risk measures are considered with geological uncertainty to improve the worst case(s). Furthermore, a deviation measure, semivariance, is also used with both geological and economic uncertainty to maximize the lower tail. The geological uncertainty is characterized by an ensemble of geological model realizations and the economic uncertainty is defined by an ensemble of varying oil price scenarios.
| Language | English |
|---|---|
| Pages | 133-138 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| DOIs | |
| State | Published - Jun 2016 |
| Event | 11th IFAC International Symposium on Dynamics and Control of Process Systems, Including Biosystems (DYCOPS-CAB 2016) - Trondheim, Norway Duration: 6 Jun 2016 → 8 Jun 2016 Conference number: 11 http://dycops2016.org/ |
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Robust optimization of water-flooding in oil reservoirs using risk management tools. / Siraj, M.M.; Van den Hof, P.M.J.; Jansen, J.D.
In: IFAC-PapersOnLine, 06.2016, p. 133-138.Research output: Contribution to journal › Conference article › Academic › peer-review
TY - JOUR
T1 - Robust optimization of water-flooding in oil reservoirs using risk management tools
AU - Siraj,M.M.
AU - Van den Hof,P.M.J.
AU - Jansen,J.D.
PY - 2016/6
Y1 - 2016/6
N2 - The theory of risk provides a systematic approach to handling uncertainty withwell-defined risk and deviation measures. As the model-based economic optimization of the water-flooding process in oil reservoirs suffers from high levels of uncertainty, the concepts from the theory of risk are highly relevant. In this paper, the main focus is to offer an asymmetric risk management, i.e., to maximize the lower tail (worst cases) of the economic objective function distribution without heavily compromising the upper tail (best cases). Worst-caserobust optimization and Conditional Value-at-Risk (CVaR) risk measures are considered with geological uncertainty to improve the worst case(s). Furthermore, a deviation measure, semivariance, is also used with both geological and economic uncertainty to maximize the lower tail. The geological uncertainty is characterized by an ensemble of geological model realizations and the economic uncertainty is defined by an ensemble of varying oil price scenarios.
AB - The theory of risk provides a systematic approach to handling uncertainty withwell-defined risk and deviation measures. As the model-based economic optimization of the water-flooding process in oil reservoirs suffers from high levels of uncertainty, the concepts from the theory of risk are highly relevant. In this paper, the main focus is to offer an asymmetric risk management, i.e., to maximize the lower tail (worst cases) of the economic objective function distribution without heavily compromising the upper tail (best cases). Worst-caserobust optimization and Conditional Value-at-Risk (CVaR) risk measures are considered with geological uncertainty to improve the worst case(s). Furthermore, a deviation measure, semivariance, is also used with both geological and economic uncertainty to maximize the lower tail. The geological uncertainty is characterized by an ensemble of geological model realizations and the economic uncertainty is defined by an ensemble of varying oil price scenarios.
U2 - 10.1016/j.ifacol.2016.07.229
DO - 10.1016/j.ifacol.2016.07.229
M3 - Conference article
SP - 133
EP - 138
JO - IFAC-PapersOnLine
T2 - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
SN - 2405-8963
ER -