Reservoir Model Updating and Value of Information Using Probabilistic Economic Forecasting

Abstract

Abstract This paper presents a probabilistic economic analysis procedure that accounts for uncertainty in production forecasts arising due to incomplete geologic information. In addition, this paper also presents a procedure to assess the worth of progressive updating of reservoir models using additional data in context of value of information. For the first objective, a workflow to model reservoir uncertainty and its economic analysis is presented and a procedure for probabilistic economic analysis using real options is developed. The workflow also demonstrates how to incorporate flow rate uncertainty in the real options valuation (ROV) calculations. For the second objective, we compared the value of new information obtained by either drilling an additional exploratory well or acquiring seismic for developing a reservoir model. The base case reservoir model is obtained by conditioning data along 5 production wells and the value of new information is assessed both in terms of uncertainty reduction and increase in economic returns. Comparison of economic forecast from ROV and discounted cash flow (DCF) approach shows an interesting contrast between the forecast results obtained from these two techniques for all sources of information. The forecast by DCF changes drastically after 2–3 years of production when compared with the forecast by ROV. ROV analysis preserves the uncertainty in reservoir characteristics till the very end of production, while the uncertainty in DCF decreases practically to zero at the end time of production. Even though in this particular case neither drilling an additional exploratory well nor acquiring seismic brought significant improvement to the economic forecast over the base case forecast, the example demonstrates the workflow for updating reservoir models and assessing the value of new information.