Static and dynamic models often simplify coal measures as laterally continuous seams between interburden layers. However, coals are not always laterally continuous and are frequently heterogeneously distributed within interburden. Formation water often contains a high concentration of gas, and in many cases is likely at saturation. Groundwater extraction from coal seam gas (CSG) reservoirs, therefore, will produce free gas from both: i) gas desorption from the coal matrix, and ii) gas exsolution of dissolved gas in formation water. This generated gas could be produced from the well or it may migrate up-dip in-situ due to buoyancy effects.

Accounting for solubility effects (i.e. the dissolved load degassing component of the free gas phase) while modelling gas production from coal requires additional field data gathering/analysis effort and brings extra computational cost. In this work, for both layered and heterogeneous coal-interburden systems, we use conceptual numerical simulations to demonstrate that gas dissolution/exsolution considerably affects the prediction of gas desorption rate, production rate, and gas migration flux.

Two coal-interburden systems are considered in this paper. Both contain 20% coal, one with laminated coal layers and the other with heterogeneously distributed coal bodies within a shale interburden. Static geological models were built within a 1km×1km×20m cube. A vertical production well at a constant pressure of 100kPa was placed in the middle of the models and perforated along its entire thickness. Implementing a dual-porosity dual-permeability approach, multiphase flow was modelled once with, and then without, accounting for the dissolution/exsolution of the aqueous phase. Results show that allowing the aqueous phase to produce gas leads to an increase in the gas production rate from the heterogeneous case; however, it decreases the gas production from the layered coal model in early time steps. Results suggest that a detailed understanding of the dissolved gas load in CSG reservoirs will assist in improving gas production predictions at the well head.

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