The Use of Monte Carlo Analysis to Evaluate Prospective Coalbed Methane Properties

Abstract

The exploration of coalbed methane resources is underway in many countries throughout the world. The ability to accurately predict and/or estimate expected production from a prospective coalbed methane play is imperative for evaluating the potential for economic success of proposed developmental projects. However, to accurately predict coalbed methane production requires the use of a reservoir simulator and generally requires knowledge of numerous reservoir properties. It is usually difficult to reliably predict key reservoir properties based on the datasets which are available for exploratory-type coalbed projects. We have found that a probabilistic approach is useful for estimating the expected range of producibility for a prospective coalbed methane area, and for quantifying the risk associated with finding commercial production in prospective areas. The probabilistic approach provides a forecast of the expected distribution of reserves that would be expected to be realized from large-scale development of a particular area.

This paper describes a probabilistic approach for evaluating prospective coalbed methane projects which combines (1) coalbed methane reservoir simulation to predict coalbed weIl production, and (2) Monte Carlo simulation analysis to determine the distribution of expected reserves for a prospective area. This methodology allows us to predict, in a probabilistic manner, the expected average productivity and distribution of reserves for a prospective coalbed methane project. This paper explains in detail the approach used and presents a case study to show how this method is applied to a developmental coalbed methane project. The methodology presented in this paper can be applied to any new or emerging coalbed methane development project to assist in quantification of the economic viability of the project. It also provides a basis for risking investments in prospectivecoalbed methane projects.