Typically in oil and gas production, only a small fraction of the oil present manages to flow out of an oil reservoir under the reservoir’s own pressure. Following this, fluids must be injected back into the reservoir to push the remaining oil and gas out. This displacement process is known as ``improved oil recovery (IOR)’’.
Foam is a very promising injection fluid for oil displacement in IOR. It is easy to produce foam in situ within an oil reservoir by injecting alternate slugs of surfactant solution and gas. Moreover foam can have surprisingly low mobility when propagating through a porous medium such as an oil reservoir, meaning it tends to control the motion of all the other reservoir fluids that are present including the oil being displaced.
However foam is an intrinsically complex fluid, meaning that the physical rules governing how it moves in a porous medium are still not fully established. As foam improved oil recovery proceeds, it is known that a narrow front of finely-textured, very low-mobility foam is generated, and this separates downstream liquid (surfactant solution plus oil) from upstream injected gas (typically in the form of coarsely-textured, relatively mobile foam). Understanding the evolution over time of the aforementioned finely-textured, low-mobility foam front is key to understanding the foam improved oil recovery process itself. Under single directional flow, it has been established that the finely-textured, low mobility foam front whilst remaining narrow compared to the reservoir scale, does grow gradually over time, and this growth causes the foam front to slow down over time.
What happens as the foam front changes direction however remains completely unknown. Changes in direction are however commonplace in oil and gas operations whenever additional injection and/or production wells are brought online. Under direction changes such as these, it is unclear whether the thickness of the finely-textured foam front will continue to grow, or whether it might first shrink and then grow. Likewise it is unclear whether the eventual growth rate attained by the front thickness matches what it had prior to a flow direction change having been imposed, or could be somehow different. Likewise it is also unclear whether the front mobility remains comparable or not to what it was previously.
This project under the supervision of Dr Paul Grassia is aimed at obtaining detailed mechanistic understanding of foam motion within porous media. It will perform an in-depth analysis of the mathematical equations underlying flow of a finely-textured foam front in porous media, and use these equations to compute the consequences for the front’s behaviour as changes in flow direction and/or flow configuration are imposed. Having examined the behaviour of the finely-textured foam front, the project will then scale up to the entire reservoir, with the aim of predicting the performance of foam improved oil recovery, and allied processes, e.g. foam-based soil remediation.
In addition to undertaking cutting edge research, students are also registered for the Postgraduate Certificate in Researcher Development (PGCert), which is a supplementary qualification that develops a student’s skills, networks and career prospects.
Information about the host department can be found by visiting: http://www.strath.ac.uk/engineering/chemicalprocessengineering http://www.strath.ac.uk/courses/research/chemicalprocessengineering/
Applications will be considered up to 21 January 2021. Those received before 21 September 2020 will be given priority.
This PhD project is initially offered on a self-funding basis. It is open to applicants with their own funding, or those applying to funding sources. However, excellent candidates may be considered for a University scholarship.
Students applying should have (or expect to achieve) a minimum 2.1 undergraduate degree in a relevant engineering/science discipline, and be highly motivated to undertake multidisciplinary research. This is a modelling and simulation based project, so applicants are expected to demonstrate strong modelling and computer programming skills.