Play analysis is not a new concept. However, the use of probabilistic economic analysis techniques and tools can add a new dimension to the assessment of the economic value captured when entering a new play. Over the past decade there has been considerable effort devoted to modeling the economics of hydrocarbon plays. Describing the reserves in each prospect probabilistically, and setting dependencies between geologic risk factors in the prospects to compute a composite geologic probability of success is a frequently applied method. However, the play economics are often done simplistically by computing the value based on a mean development scenario, or an assumed ratio of net present value to oil-equivalent volume.

We will show how more rigorous probabilistic economics can be folded in with the standard probabilistic reserve assessment. Once hydrocarbons are found, there are generally one or more possible development scenarios depending on reserve size and production rates. By assigning probability distributions to the engineering elements of production rates and declines, investments and expenses, distributions of economic indicators such as NPV, ROR and P/I can be calculated. Conditional logic is used to build all possible development scenarios into a single probabilistic model, which can take the place of multiple decision tree cases. Such a model can be used to investigate the inherent risks and provide probabilities of achieving a positive NPV for the play, or of adding a certain volume of reserves.

In this paper we will present a Gulf of Mexico play model as an example. In this play the number of prospects has a probability distribution. In addition, we cease exploration in the play if three consecutive dry holes are drilled. For each prospect in the play we have an economic threshold. Below this threshold we abandon the prospect and incur dry hole costs. There is also a development threshold that determines whether the development uses subsea completions, or a platform. For each development scenario the production rates, investments and operating expenses are modelled as probability distributions.

Once a robust probabilistic model is built, the sensitivity of the model to the uncertainties in many variables can be readily investigated. A powerful feature of this model is that the impact on the play economics of factors such as delays can be quantified.

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