An accurate forecast of CSG production and distribution has a significant influence on the well design. To date, the forecasting strategy basically based on the single parameter property of coal medium. Whereas coal medium is heterogeneous and anisotropic and its properties vary spatially, in addition, its reservoirs are naturally fractured formations, comprising both permeable fractures, matrix blocks and other parameters. To achieve the optimal well design means a lot to environmental conservation, resource utilization, and financial expenditures. However, using a single parameter value to design production wells and predict gas production is no longer sufficient, thus a comprehensive forecast method is needed.

This research project aims to provide a comprehensive uncertainty analysis approach to optimizing CSG well design with multi-parameter. In this project, the literature review will be conducted at first, and then lab measurements will be carried out to obtain the statistic distribution of coal properties, such as elastic modulus and permeability, porosity, Langmuir constants etc. Based on the experimental results, a multi-parameter model will be applied to study the parameter sensitivity on the CSG production, as this model incorporates not only the influence from fractures but also the properties of coal matrix. After that, the specific distribution and proposed model will be implemented into the in-house software to investigate the gas production and design well layout. Meanwhile, the numerical model will also be applied to match the history data from a gas-production well. The comparison between traditional approach and this new comprehensive uncertainty analysis approach on the confidence of gas production prediction will be investigated in the end.

Funding:  China Scholarship Council
Advisor:  Assoc Prof Huilin Xing

Project members

Songtao JI

PhD candidate