A comprehensive model to history match and predict gas/water production from coal seams

Coalbed methane (CBM) currently accounts for approximately 5% of U.S. annual gas production. The performance prediction of CBM is very complex. It is highly affected by the complexity of porosity-permeability variation, reduction due to formation compaction, enhancement due to matrix shrinkage, and the two-phase flow effects. An additional complexity is added if the initial gas content, permeability, and porosity are not available. In this paper an integrated model was developed to simulate the behavior of CBM. A developed generalized material balance equation is used to account for the solubility of the methane in water, and the changes of porosity and permeability with pressure depletion. The equation is formatted similarly to the conventional material balance of oil reservoirs. An optimization algorithm was also used with the integrated model. The model could be used as a history matching tool to estimate the original gas-in-place (the adsorbed gas-in-place and the free gas-in-place), the initial formation permeability, the gas and water relative permeability exponents, and the matrix shrinkage coefficient that reflected the permeability changes. The developed model was validated by use of different simulation cases generated with a commercial simulator. The results show a good match between the simulation cases and the integrated model. The model was then used to analyze the production data of different CBM formations (the Fruitland and the Upper Pottsville Formations, USA). The model was used to match the production history data (gas and water rates) in order to estimate the gas-in-place and the formation properties. These parameters were then used to predict the production performance. The model can be run with different production control conditions such as the constant water rate or the constant bottom-hole flowing pressure. This model could be used as a helpful tool in CBM investment and development. It can also be used to obtain the key reservoir parameters for newly discovered reservoirs such as gas-in-place, initial water-in-place, water production rate, gas production rate, and the peak gas rate. With this information, an investor will better determine the feasibility of a project. Also, this model can be used to optimize the dewatering rate (initial water production rate) in order to optimize the time taken to reach the peak gas rate. (C) 2015 Elsevier B.V. All rights reserved.