Print this pagePSLessons Learned from Distributions as Geological Analogs*
By
Gary P. Citron1,
James A. MacKay2,
James Gouveia2,
Robert
M. Otis2,
and Richard Nehring3
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Abstract
Geological analogs can be inappropriately applied in exploration, often leading to deterioration of project value. A natural place to start considering discovery analogs is with distributions of EUR (estimated ultimate recovery), and their component parts (e.g. area, porosity and production rate) for related trends. Examination of such data helps avoid the bias of selecting the wrong distribution shape in the assessment. The lognormal distribution often best approximates discovery data with broad variance distributions. However, the versatile beta distribution offers considerable flexibility for characterizing parameters with restricted ranges associated with hydrocarbon yield. Frequent deviations from the pure mathematical expectation of distribution shapes can add confusion for decision makers, but these are often related to either growth limitations within geologic systems or business interventions associated with the desire for increased profitability. The part of the distribution most overlooked is the low end. However, these low EUR data, often considered “not possible for our company,” are a critical component of unbiased analog assessment. In unconventional resource plays where individual anomalies are difficult to differentiate, EUR-per-well distributions are helpful, particularly in portfolio amalgamation techniques. Associated minimum commercial production rates can be correlated to EUR size for the appropriate commercial size threshold. If a target prospect or onshore trend has an offshore analog, the field size distribution of the analog trend needs to be re-constructed with underreported minimal discoveries to reveal its true character. We share lessons learned from examples from Canada, U.S., and Australia to illustrate how analog experiences lead to unbiased profitable learning.