Print this pagePSLessons Learned from Distributions as Geological Analogs*
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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.