Novel upscaling techniques for coal seam gas models

This Earmarked Scholarship project is aligned with a recently awarded Category 1 research grant. It offers you the opportunity to work with leading researchers and contribute to large projects of national significance.

Supervisor – Professor Andrew Garnetta.garnett@uq.edu.au

The ARC Linkage Project New stratigraphy and geostatistics for gas and water addresses the challenge of sustainable development of Queensland’s gas and groundwater resources. Predictive modelling is key to informing management strategies of gas extraction operations as well as the management of groundwater resources. The modelling of the flow of water and gas in coal seam gas reservoirs relies on methods developed for conventional oil and gas fields, where geological and hydrogeological conditions are different. Consequently there is an opportunity to improve the certainty of forward-looking estimates of gas and water production from coal seam gas developments. In the case of Walloon coals (Surat Basin) this is exacerbated because of the very small thickness of most coal seams that is far below a practicable reservoir simulation cell size. This thesis research will contribute to the overall goal of this ARC Linkage project by reviewing and testing currently known techniques in a series of scenarios based on gas industry field data. The insights gained from this exercise will be used to develop a fit-for-purpose methodology and work flows for reservoir simulation model building and may include theoretical and coding work as well as flow experiments.

Preferred educational background

Applications will be judged on a competitive basis taking into account the applicant's previous academic record, publication record, honours and awards, and employment history.

A working knowledge of single and multi-phase flow and numerical methods in fluid dynamics would be of benefit to someone working on this project.

The applicant will demonstrate academic achievement in the fields of petroleum engineering, environmental engineering or hydrogeology and the potential for scholastic success.

A background or knowledge of geostatistics, stochastic modelling and computer programming (Python, Matlab, R etc.) is highly desirable.

*The successful candidate must commence by Research Quarter 1, 2022. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons.

Apply now