This paper presents the methodology and technical solutions used to perform an evaluation of Gas Resources for two coalbed methane (CBM) projects in former coal mining basins in the North and East of France. These assessed gas volumes constitute one of Europe's important reported coal bed methane's resources. Successful gas flow rates were also obtained from a horizontal well drilled in coal strata. CBM resources classification principles as described in the Guidelines for Application of the Petroleum Resources Management System (PRMS - November 2011) were applied. The main issues encountered were the allocation and categorization of the 1C/2C/3C Contingent Resources and Low/Best/High Prospective Resources. Dealing rigorously with uncertainties inherent to the type of data used was an essential part of the study.
A fully integrated workflow was used to undertake the resources evaluation. The Gas Initially in Place (GIIP) estimation is based on 3D geological models. Project specific criteria were applied to derive the final volume estimation in the context of CBM resources in the vicinity of former coal mines. Potential recovery factor calculations followed 3 different approaches: Langmuir isotherm curves, material balance based on mining data and 3-D dynamic simulation based on pilot horizontal well results. Due to large uncertainties existing on various parameters, a sensitivity analysis was performed to evaluate their relative impact on production during the dynamic simulation, using experimental design techniques. The final resources calculations and their respective categorization were based on a probabilistic methodology using Monte Carlo simulations with specific distributions for all parameters used at each stage of the workflow (net coal, gas content, coal density, level of coal undersaturation, permeability and recovery factor distributions).
Key parameters were identified as critical with a large impact on the final assessment (gas content, level of undersaturation, shape of Langmuir isotherm curve, abandonment pressure). The elaborated workflow allowed the classification in Contingent and Prospective resources as well as evaluating their respective range of uncertainty which was required to complete the evaluation.