Probabilistic Discharge Forecasting For Improved Asset Investment Decision Support

Abstract

Abstract In this paper we present a new way of integrating discharge forecast uncertainties in asset investment decision-making. The approach can be useful in the face of uncertainties with respect to future government regulations and in the face of uncertainties in the environmental implications of a given development. We present a hypothetical case study on how an oil company could optimize its investment decision-making by comprehensively risking the various regulatory scenarios and combining these with capex and opex items of mitigating measures on the one hand, and financial penalties for exceeding certain tolerance limits on the other hand. Decision trees are used as decision-making framework. The proposed methodology is fully probabilistic in the sense that it models both discrete uncertainties (scenarios, or possible events beyond one's control) and continuous uncertainties (i.e. probability density functions of uncertain input parameters). The Monte-Carlo sampling process generates a statistical population for the production, discharge and cash flow time-series curves, and ascertains that the full information is propagated to each investment alternative at the decision nodes of the tree. For each alternative decision, the risk of exceeding discharge tolerance limits is directly calculated and translated into the financial risk of having to pay a levy. The results of the simulated decision process with two types of financial government instruments indicate that probabilistic discharge forecasting can support both governments and asset managers. Governments can quantify prior to roll-out the chance that a certain policy will have the desired impact. Asset managers can use probabilistic emissions forecasting to optimize the asset's value by improving their decisions on mitigation facilities and operational policy. The hypothetical case study, assuming realistic developments in regulatory measures, indicates that an asset manager with an assignment to optimize net present value, will choose not to make any upfront investments in discharge mitigation facilities, resulting in less potential for future environmental protection. As a result of discounting, the long-term benefits do not sufficiently compensate the early investment.