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we said that modern petroleum explorationists have two
main professional responsibilities:
opportunities (= prospects).
them objectively, in terms of chance of success; reserves expectations
(estimated ultimate recovery); and profitability.
opportunities is the fun part of the exploration business, the
value-adding part. It involves new geography, new geology, new
tools, secrecy -- and the competitive excitement of the hunt!
if we are to stay in business, the measurement part is also important.
it's often mundane -- even uncomfortable -- especially if our
prospects are judged to be uneconomic. And let's face it, a lot
of geologists are just naturally less interested in dollars than
dolomite or downwarping!
so, measuring the economic value of our prospects is a key part
of our professional obligations to our clients and investors.
assessing prospect value necessarily involves estimating many
geotechnical parameters (and some economic ones) that affect prospect
For the geotechnical parameters, estimating is required because:
cannot crawl down into the subsurface with a measuring tape
Earth is a very coarse filter.
A lot of investment capital is riding on our ability to objectively
estimate variable factors -- such as productive area, average
net pay thickness, hydrocarbon recovery factor (bbl/af or mcf/af),
recoverable reserves, etc. -- and existence factors, such as our
confidence (= probability) that reservoir, closure, top seal or
hydrocarbon charge requirements are satisfied at depth.
This month, we'll discuss the variable factors.
general industry convention is to estimate the variable factors£--
those uncertainties involving recoverable reserves, or flow rates,
or prices and costs -- as probabilistic ranges, using cumulative
In figure 1, for example, the exploration team is 90 percent sure
that, given a discovery, the productive area will be at least
40 acres; they think there's only a 10 percent chance it could
be larger than 2,000 acres.
What really boggles the mind is that, despite the huge capital
investments being laid out yearly by dozens of competing corporations
on highly uncertain oil and gas ventures, very few petroleum geoscientists
or engineers have ever received any formal training in effective
estimating techniques! Lots of math, physics, chemistry, geoscience
and computer science, to be sure -- but no training in estimating.
Almost no geologist or engineer ever took a course called "Estimating
also should learn how to eliminate systematic bias as well --
the tendency for us to consistently overestimate reserves or underestimate
costs, to give two examples.
Two biases that commonly bedevil our geotechnical forecasts are
overconfidence (setting predictive ranges too narrow, resulting
in frequent surprising outcomes) and overoptimism (motivational
bias, caused by excessive zeal in "selling" the prospect).
These techniques have proved to be useful in refining our estimates
of exploration variables and eliminating bias:
- Use of multiple working hypotheses and maps.
Prepare several possible interpretations -- optimistic and pessimistic
-- to test the envelope of possibilities surrounding all key
parameters: MAKE MORE THAN ONE MAP!
(This is one drawback to conventional workstation mapping, which tends
to focus on THE answer.)
- Independent Multiple Estimates.
Get input from exploration team members, exploration committee
reviews or other joint-venturers in partnership prospects. For
example: Averaging independent estimates by four seasoned experts
usually gives a better (and quicker) answer than having one geoscientist
work four more weeks on the problem!
- Honor Nature's Envelopes.
Make predictions employing a parameter's observed (and therefore
expectable) distribution (exponential for percent decline-estimates,
lognormal for prospect reserves estimates, etc.).
- Reality Checks.
Is your prospect reserves distribution reasonable compared with
a current field-size distribution?
Are your estimates of reservoir parameters credible considering
Are the extreme outcomes (P99 percent, P1 percent) plausible?
Is it remotely possible (P1) that the productive area of the prospect
in figure 1 could be as large as 10,000 acres? Could it be as
small (P99) as eight acres, and still support flow into the
- Use Proper Statistical Measures.
For exploration portfolios, the mean
(= average) is the single best representation of the prospect
reserves distribution. Use probabilistic ranges, rather than
Avoid the meaningless term "most likely," as well as single-number
- Learn From Prior Predictions.
Start preserving all your predictions, and compare them against actual
What can you learn about your predictive performance? Do you typically
overestimate? Are your ranges too narrow?
How can you improve your estimating ability?
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, we'll take a look at existence factors.