Abstract

Prospect interdependencies, if present and positively correlated, result in a higher standard deviation of the portfolio volumetric expectation curve, compared to a portfolio with independent prospects. This wider uncertainty range offers options for companies to increase the expected cumulative net present value (NPV) of the exploration portfolio. To investigate these effects on exploration portfolios, a methodology has been developed for modeling these dependencies spatially and updating them in time as new information is acquired. The methodology integrates Bayesian belief network techniques into a stochastic exploration business process simulator. Applying this methodology to the Netherlands gas portfolio clearly demonstrates an increase in both the range and expected value of NPV of the expected recoverable volume from the exploration portfolio. Proper tuning of the exploration strategy, using an efficient frontier approach, and regular updating of portfolio economic forecasts increase the probability of realizing the upside at minimum risk when compared to independent prospect portfolios. The staged decision strategy and the value of information underlying the gradual increase of expected NPV can also be calculated and visualized through decision tree analysis techniques.

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