Risk-Quantified Decision Making in Reservoir Management

• Author / Creator

  Yang, Di

• Limited understanding of the complex subsurface brings uncertainty and risk of production shortfalls in the oilfield development. Geostatistics provides tools to model the geological uncertainty that occurs in reservoir decision making. The common decision criterion under uncertainty is to find the strategy that maximizes the expected return. But the value of assets is influenced by investors' tendency to risk, which could lead to different responses in decision-making problems. Therefore, risk-quantified decision making becomes increasingly important in reservoir management.

  Decision analysis tools such as minimizing expected loss and maximizing expected utility are suitable for many petroleum applications. They are often employed when investors are sensitive to risk. Since the specific utility function is difficult to quantify in practice, the mean-variance criterion and maximizing the risk-adjusted value are widely employed when there is no explicit utility function. These approaches employ variance as the measure of risk. The variance, however, is often considered inadequate to quantify risk as investors dislike the downside volatility and are less concerned about unusual windfalls. This research develops techniques to improve risk-quantified decision making in reservoir management. The main contributions of the thesis include: (1) The impact of preferences on decision analysis is demonstrated, and a workflow is proposed to establish the relationship between the preference measurements. The relationship is constructed by connecting the risk tolerance of utility functions and penalty factor of loss functions. (2) The downside-risk approach is introduced in reservoir decision making within the expected utility framework. The risk in this approach is reflected by the downside volatility and quantified by the lower partial variance, which is able to improve the reservoir decision making by explicitly analyzing risk. (3) Preferences are taken into account in value of information (VOI) analysis by integrating the utility theory into the simulation-regression approach. The consideration of different risk preferences leads to a more robust VOI analysis in spatial decision situations.

  The proposed methodologies are applied to the design of production strategies. The impact of different preferences in the decision-making process is documented, and the limitations of current approaches are revealed. The ultimate goal of this research is to improve reservoir management in the presence of geological uncertainty by explicitly quantifying and managing risk.

• Subjects / Keywords

  • Reservoir decision making
  • Risk management
  • Geological uncertainty

• Graduation date

  Fall 2022

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/r3-jz9k-7a40

• License

  This thesis is made available by the University of Alberta Library with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.