Stochastic Modeling for Estimating Coalbed Methane Resources

In this paper, an integrated workflow was developed to estimate coalbed methane (CBM) probabilistic resources. This workflow captures all of the uncertainty parameters in CBM modeling, including the structural surface and coal thickness in the structural modeling and the coal facies, logging density, etc. in the property modeling. These uncertainties were statistically analyzed and quantified. Sensitivity analysis was carried out to rank the impact of these parameters on the resources, and six sensitive parameters were chosen. Then, multiple stochastic models were generated using the aforementioned six parameters to determine the resource distribution, from which the P90, P50, and P10 resources were chosen. Finally, the low, middle, and high probabilistic models corresponding to these three probabilistic resources were attained. This workflow was applied to a CBM field in Australia, and the simulated results show that for the low, middle, and high probabilistic resource models the resources are always high in the central and western part of the study area.