Hydraulic fracturing stimulation is one of the key technologies in shale gas development. Though it has been widely used in oil and gas industry for many years, it remains a great challenge to quantitatively characterize the hydraulic fracturing induced fracture network in shale gas development due to the complex shale gas formation and the lack of observational data. Consequently, it is extremely difficult to evaluate and predict its efficiency and environmental impacts. In this collaborative research project the investigators study the hydraulic stimulation induced fracture network through advanced statistical analysis and mathematical modelling. Armed with micro-seismic data and production yield curve, they develop a statistical dynamical system for the fracture network, mimicking the network formation process under imposed hydraulic pressure. A Bayesian framework is used for parameter inferences, utilizing prior knowledge of the geological structure of the field under study. A mathematical subsurface flow model and an advanced numerical method, the sub-region method, is used to link a given fracture network to the production yield curve, providing vital information of the unobservable fracture network underground.By combining creative statistical analysis with advanced mathematical modelling and numerical method, the project addresses a very challenging application with important national interests. The project yields a better understanding of the hydraulic stimulation process, provides useful guidance for control and optimization of hydraulic fracturing process as well as assessing its environmental risks and consequences. Such knowledge helps policy makers to make more informed decision and more accurate cost analysis. The project spans both research and education aspects, including training of undergraduate, doctoral and post-doctoral students in interdisciplinary research, crossing the boundary of statistical analysis and numerical analysis, on an important application. The resulting software, available in public domain, will be used as an educational, research, and engineering tool well beyond the project duration.
|Effective start/end date||9/1/12 → 8/31/15|
- National Science Foundation (National Science Foundation (NSF))