Coal bed reservoir simulation with geostatistical property realizations for simultaneous multi-well production history matching: A case study from Illinois Basin, Indiana, USA

Coal seam degasification is a means to recover energy from the methane gas retained in coal, and is also a supplementary measure to ventilation, which is proven to be one of the most effective ways to reduce methane emissions to a safe level in coal mines. Reservoir simulation is probably the most effective way to assess the coal seam as a gas reservoir and thereby its fluid-storage and flow-related properties. This objective is achieved by taking advantage of history matching of wellbore production. Reservoir simulation with multi-well history matching is a tedious process as important coal properties that affect wells' production characteristics are spatially variable across the seam. The common practice is to change various properties at the well blocks during the history matching process, and assume that they are uniform across the domain of interest. This process, however, often does not produce realistic and effective results for well or coal reservoir management In this work, a multi-level approach to coal bed reservoir simulation is demonstrated for a group of coalbed methane wells in the Illinois Basin producing from the Seelyville Coal Member of the Linton Formation of the Carbondale Group (Pennsylvanian) in Indiana. This approach includes, in order, gas and water deliverability analyses of wells, geostatistical simulation and co-simulation, and coal bed reservoir simulation. It is shown that a reservoir model, which utilizes the geostatistical maps of important coal properties, is effective for simultaneous history matching of all wells, and eliminates the need for guessing and changing values of coal properties at and around individual well blocks. This methodology also provides realistic distributions of reservoir parameters and how they change during gas depletion, and thus aids in coal seam and coal gas management. Published by Elsevier B.V.