Technical Paper: Correlation of Porosity Uncertainty to Productive Reservoir Volume

Society: SPE
Paper Number: 164261
Presentation Date: 2013
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Monte Carlo simulations demonstrate that probabilistic models of hydrocarbon volumes should correlate the degree of porosity uncertainty to the productive volume of the reservoir. Assessments that fail to model the relationship between productive volume and porosity uncertainty may create unrealistic resource estimates and valuations.

The findings are applicable to conventional exploration prospects with significant uncertainty of productive reservoir volume, and to unconventional resource developments with high lateral variation in reservoir quality.

Probabilistic models of hydrocarbon volume include an estimate of porosity, defined by a probability density function such as a normal or lognormal distribution. The distribution models the uncertainty around the “average” porosity within the field. If a field is small, the productive volume represents a limited sampling of the reservoir. There is a possibility that the average porosity within the productive reservoir may be very high or very low. If the field is large, there is a greater chance that a high porosity in one portion of the field will be offset by a small porosity in another portion of the field, resulting in a narrow range of uncertainty around the average porosity. Probabilistic models that do not decrease the porosity range as reservoir volume increases may generate results in which a high porosity is applied to a large reservoir volume, resulting in resource volumes and economic valuations that are unrealistically high.

The solution lies in the use of multiple-segment models. If each segment represents a stratigraphic layer, or a portion of the potential productive area, and each segment is assigned the wide range of porosity appropriate for a small field, then increasing the number of productive segments will decrease the range of overall average porosity.

This paper clarifies the definition of porosity uncertainty in probabilistic models, reveals a relationship between porosity uncertainty and reservoir volume, and presents a method that will result in more realistic resource estimates and valuations.

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