Semester

Fall

Date of Graduation

2010

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Petroleum and Natural Gas Engineering

Committee Chair

Yueming Cheng.

Abstract

There are tremendous coal bed methane resources throughout the world. However, with conventional production methods, 40-80% of methane is left behind as unrecoverable. Enhanced coal bed methane (ECBM) recovery by injection of Carbon dioxide (CO2) is motivated by the dual benefits of improved gas recovery and green house gas storage. In practice, this technology is relatively new, still in the early stage of development, and the economic performance of ECBM has yet to be verified. Due to the complexity of CBM reservoirs, the production performance involves significant uncertainties. It is imperative to quantify the uncertainty of production performance in order to improve the economics of ECBM.;Uncertainty of production performance can be analyzed by reservoir modeling coupled with stochastic method such as Monte Carlo Simulation. This procedure has been proven to be an effective methodology to predict production profiles with a wide variety of reservoir properties and producing conditions. In this study, a commercial reservoir simulator is coupled with Monte Carlo simulation. Rapid assessment of CO2- ECBM performance uncertainties can be realized by considering probabilistic distributions of coal bed properties, such as cleat spacing, permeability anisotropy, water saturation, porosity and isotherm parameters like Langmuir pressure and Langmuir Volume. CO2-ECBM design, such as well pattern, well spacing and CO2 injection rate, can be investigated under these uncertain coal bed properties.;The approach is illustrated using an example case from Appalachian Basin Coals, and provides a new insight on understanding the impacts of uncertain factors on production performance as well as optimization of CO2-ECBM design.

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