Coalbed methane (CBM) has become an important source of clean energy in the recent decades worldwide including the US, China, Australia, India and Russia with more than 60 countries having different degrees of promising coal reserves. CBM reservoirs are distinguished from conventional reservoirs due to the major difference in the mechanism of gas storage and production of water. In CBM reservoirs, pores act as the major storage mechanism as gas is trapped and stored there and produced by means of dewatering and thus lowering the reservoir pressure. Free gas forms as the pressure is lowered leading to increased gas permeability of coal and thus increasing recovery. Microbial activity and thermal maturation of organic compounds are the main mechanisms of methane generation in lower-and-higher rank coals, respectively. Even though methane is an abundant and clean energy source, there are certain operational, technical and economic challenges involved in its production due its unique nature outlined above. Thus, a strong understanding of the parameters and uncertainties that influence the recovery is crucial.
Due to the fact that the organic materials that make up coals generally have a stronger affinity for CO2 than for methane, CO2 is used as an enhanced recovery method to displace methane as an enhanced coalbed methane recovery (ECBM) method. While there is no current comprehensive optimization study on the effects of such factors, ECBM has a very significant role in the future of energy as it means more energy out of natural gas while eliminating the adverse effects of greenhouse gases.
In this study, a standard SPE reservoir simulation model is used to study the factors influencing the recovery in coal bed methane reservoirs by investigating the significance of parameters including but not limited to porosity, adsorption capacity, fracture permeability along with coal density and irreducible water saturation.
The optimization results obtained by means of coupling a full-physics commercial numerical reservoir simulator with an optimization/uncertainty tool are presented outlining the different degrees of significance of these factors on production and ultimate recovery for better understanding of the phenomenon that will lead to more robust reservoir management decisions.