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. BOEM 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.


Photo of platform workers monitoring activities  

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.


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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 BOEM 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 BOEM can obtain a calculated value of the tract under the made assumptions.