Online Journal for E&P Geoscientists

Norman, Charles D.^*1
(1) GeoKnowledge, LaGrange, GA.

Probabilistic models of potential hydrocarbon volumes in exploration prospects typically include an estimate of “average” porosity. The estimate is input as a range defined by a probability density function such as a normal or lognormal distribution. Geologists often mistakenly assume that the distribution represents the range of porosities that may exist within the prospect: the porosity that might be encountered at any single point within a discovered field. The range actually represents the uncertainty around the total porosity within the field. Each porosity value within the distribution must be an appropriate representation of the percentage of the net rock volume above the hydrocarbon-water contact that is within pore spaces. The misconception that the porosity range represents the range of porosities within the field, rather than uncertainty around total porosity, often results in input ranges that are too broad, yielding unrealistic high-side resource estimates. A very broad porosity range is appropriate, however, if the field is very small, with a limited area or column height. If the field is small, there will be less room for vertical or lateral variation in porosity, and therefore a greater chance that the average porosity within the field will be very high or very low. The possibility of a high porosity within a small field should not be overlooked, as fields of this type are often economically attractive. As the productive area or column height increases, the degree of porosity uncertainty, the difference between the minimum and maximum values, should decrease. If the field covers a large area or interval, 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 narrower range of uncertainty around the average porosity within the field. The correlation of the degree of uncertainty to gross rock volume is difficult to capture using a single-zone Monte Carlo model. The solution lies in the use of multiple-zone, or multiple-segment models. If each segment represents a stratigraphic layer, or a portion of the potential productive area, and each segment is assigned the same range of porosities, then increasing the number of productive segments will decrease the range of total porosity. The number of segments should reflect the potential heterogeneity within the field.