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Fair
Market Value Determination
MONTCAR Methodology
Determination of the resource economic value of
a tract offered for lease involves calculating the amount of economically
recoverable resources, estimating recovery factors, production profiles,
exploration and development costs, operating costs, and performing a
discounted cash-flow analysis. The MMS uses a computer simulation
model to determine the resource economic value of certain OCS tracts offered
for lease by the Federal Government.
The computer model utilizes
the MONTE CARLO (or range-of-values) technique of handling calculations with
uncertain input data. It provides a means to mitigate series of
subjective judgments about each individual variable. This method
explicitly recognizes the probabilistic nature of all variables affecting
the evaluation and calculates a large number of possible outcomes based upon
random samples from input probability distributions.
Much of the geologic and
engineering data (e.g., areal extent and thickness of the hydrocarbon pay
zone, porosity, initial water saturation, recovery factors, production
rates, product prices, costs, etc.) used to evaluate a tract is known with
varying degrees of uncertainty. Providing a single number for the
resource economic value of a tract is somewhat misleading since it provides
no insight as to the relative uncertainty involved. The MONTE CARLO
technique allows obtaining a range of resource economic values (net
present worth (NPW)) for the tract with the probability of each value
reflecting the data uncertainty.
The logic of the MONTE
CARLO simulation method can be described as a four-step process.
Step 1. Estimate the range and distribution of possible values of each variable that
will affect the ultimate outcome of the venture. This requires
judgments from geophysicists, geologists, paleontologists, stratigraphers,
economists, and engineers. The most critical step in the process is
quantifying the uncertainty involved through the use of these probability
distributions. The amount of data concerning the prospect in question,
the amount of information about the trend within which a prospect is
located, and the experience of the scientists making the evaluation will
dictate the type and shape of the probability distribution curves for each
variable.
Step 2. Select, at random, one value from the distribution of each variable. Compute the tract value using this combination of selected values. This determines one point in the final distribution of possible tract
values. Select, at random, a second value from the distribution of
each of the variables. Again compute the resulting tract value. This is the second point in the distribution of possible tract values. The random selection is statistically done in such a way that, if a large
number of random selections are made (1,000 or more), the distribution of
the randomly selected values closely resembles the distribution that was
read in.
Step 3. Repeat
the process 1,000-10,000 (or more) times, each time with a set of values
selected at random from the distribution of each variable. Enough
combinations of variables should be considered to adequately describe the
shape and range of the distribution of tract values. For each trial (1
of the 1,000 or more repetitions) the tracts NPW is determined from the
combination of sample outcomes from each variable.
Step 4. The
means of the productive and dry NPW distributions are determined, the
probability of hydrocarbons being present, and factors for bonus write-off
and depletion are applied to determine the expected (risked) NPW of the
tract. This is the mean of the range of values (MROV) commonly
referred to as the Government’s reservation price. A distribution of
the MROV is also developed.
The program also calculates
what the expected NPW would be today if a tract was not leased until a later
date, taking into account differences in income and excise tax payments and
royalty or profit share payments; this is called the delayed MROV (DMROV).
This stochastic approach
allows us to account for the uncertainty of the input parameters as well as
to quantify the risk associated with exploration and production of
hydrocarbons. As a result of multiple runs, each with values sampled from
input distributions, the calculations of the Net Present Value, using the
Discounted Cash Flow Analysis, begin to converge and at the end we obtain
calculated value of the tract under the made assumptions.
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