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A key objective in petroleum resource evaluation is to estimate oil and
gas pool size (or fi eld size) or oil and gas joint probability distributions for
a particular population or play. The pool-size distribution, together with
the number-of-pools distribution in a play can then be used to predict
quantities such as the total remaining potential, the individual pool sizes,
and the sizes of the largest undiscovered pools. These resource estimates
provide the fundamental information upon which petroleum economic
analyses and the planning of exploration strategies can be based.
The estimation of these types of pool-size distributions is a diffi cult
task, however, because of the inherent sampling bias associated with
exploration data. In many plays, larger pools tend to be discovered
during the earlier phases of exploration. In addition, a combination
of attributes, such as reservoir depth and distance to transportation
center, often infl uences the order of discovery. Thus exploration data
cannot be considered a random sample from the population. As stated
by Drew et al. (1988), the form and specifi c parameters of the parent
fi eld-size distribution cannot be inferred with any confi dence from the
observed distribution. The biased nature of discovery data resulting
from selective exploration decision making must be taken into account
when making predictions about undiscovered oil and gas resources in
3
Estimating Mature Plays
A discovery process model is one built from assumptions that
directly describe both physical features of the deposition of
individual pools and fi elds and the fashion in which they are
discovered.
—Gordon M. Kaufman
A key objective in petroleum resource evaluation is to estimate oil and
gas pool size (or fi eld size) or oil and gas joint probability distributions for
a particular population or play. The pool-size distribution, together with
the number-of-pools distribution in a play can then be used to predict
quantities such as the total remaining potential, the individual pool sizes,
and the sizes of the largest undiscovered pools. These resource estimates
provide the fundamental information upon which petroleum economic
analyses and the planning of exploration strategies can be based.
The estimation of these types of pool-size distributions is a diffi cult
task, however, because of the inherent sampling bias associated with
exploration data. In many plays, larger pools tend to be discovered
during the earlier phases of exploration. In addition, a combination
of attributes, such as reservoir depth and distance to transportation
center, often infl uences the order of discovery. Thus exploration data
cannot be considered a random sample from the population. As stated
by Drew et al. (1988), the form and specifi c parameters of the parent
fi eld-size distribution cannot be inferred with any confi dence from the
observed distribution. The biased nature of discovery data resulting
from selective exploration decision making must be taken into account
when making predictions about undiscovered oil and gas resources in
3
Estimating Mature Plays
A discovery process model is one built from assumptions that
directly describe both physical features of the deposition of
individual pools and fi elds and the fashion in which they are
discovered.
—Gordon M. Kaufman