Foam Improved Oil Recovery: Effects of Flow Reversal

The context of this project is improved oil recovery.

In petroleum extraction operations, only a fraction of the oil manages
to flow out of a reservoir under the reservoir's own pressure.

After that, petroleum engineers resort to injecting fluids into the
reservoir to try to push out remaining oil.

Foam (consisting of bubbles of gas dispersed in aqueous surfactant
liquid) is a promising candidate injection fluid to achieve that.

Because oil and gas reservoirs are difficult to access (being
underground and often in harsh environments), it is generally not
possible to observe directly how an injected foam flows inside them.

Having a mathematical model of the reservoir flow is therefore
very valuable.

This project will develop one such model, so called ``pressure-driven
growth'', which is particularly computationally efficient, as it
focusses just on a foam front as it propagates through the reservoir,
rather than on the state of the entire reservoir away from the front.

Despite its computational efficiency, the pressure-driven growth model
currently has a number of limitations.

One such limitation is that the model is not currently able to
describe a situation in which the foam front undergoes a sudden change
in direction.

This is an issue since, during foam improved oil recovery, foam that
is already within the reservoir after a period of foam injection into
a given well, may change its direction of motion if a new adjacent
injection well is brought online.

The purpose of this project is to adapt the pressure-driven growth
model to describe situations such as this.

However in order to do this, we need first to explore another model
(namely so called ``fractional flow'' theory) which underpins
pressure-driven growth.

Fractional flow theory actually contains a finer level of detail than
pressure-driven growth does, providing very specific information about
exactly what is happening at a foam front at which gas and liquid
meet.

Such information includes how gas and liquid fraction profiles vary
across the foam front, how thick the front is, and how mobile it is:
all this information then feeds into parameters governing the less
detailed description given by pressure-driven growth.

Our aim therefore is to explore how fractional flow theory responds to
changes in flow directions, and to use the fractional flow results to
re-parameterise pressure-driven growth.

Having achieved this, our objective will be to test the
re-parameterised pressure-driven growth model in a number of petroleum
engineering situations that involve flow direction changes.

Results from the model will also be compared against a much more
computationally intensive ``entire reservoir'' approach, which is
conventionally employed in petroleum engineering.

The main application area that will benefit is of course oil and gas,
with the oil and gas industry managing to recover more fluids and
hence generate more revenue from existing sites.

In certain cases, e.g. for very mature oil fields, employing foam
improved oil recovery might even make the difference between keeping a
field open or needing to shut it down.

By using modelling tools predicting how foam improved oil recovery
proceeds, oil companies will be able to plan and optimise operations,
prior to performing any costly drilling, thereby limiting the need to
resort to trial and error approaches.

Although benefits of the project focus mostly on oil and gas, wider
benefits are also anticipated.

The front propagation models that we will study for foam fronts in oil
reservoirs are remarkably similar to models governing a number of
other systems, including mechanics of solid-liquid suspensions,
supersonic flow through air, spread of epidemics, pedestrian flow and
fire front propagation, amongst others.

New insights into other systems such as these can therefore derive
from the project.

This project on foam improved oil recovery will generate impact on a
number of levels.

First of all, the project will generate new knowledge on how foam
injected into an oil and gas reservoir manages to push oil out,
particularly in situations when the direction of the foam flow changes
as a new injection well comes online. Specifically we will develop
models that will allow petroleum engineers to optimise oil recovery
from existing reservoirs, with the models thereby informing optimal
placement of wells. Given that in oil extraction operations, drilling
a well in the wrong place can be a costly mistake, having robust
models of where and when to drill, will be of immense value to the oil
industry.

Although the work is set in the context of oil recovery, the knowledge
that we generate will have wider impact beyond this field. Indeed the
set of mathematical models we need to study arise not just in
petroleum engineering applications but in many other contexts as well,
including suspension mechanics, supersonic flow, spread of epidemics,
pedestrian flow and fire front propagation. The knowledge generated
in the present project will therefore have impact across the wider
applied mathematics community, and even beyond: ability to model
propagation of a bushfire front for instance, is of great importance
in regions affected by drought exacerbated by climate change.

In addition to impacting upon knowledge, the project will also impact
on people. Specifically it will contribute to the pipeline of
talented researchers working in the area of engineering and applied
mathematics. The project will achieve this not only directly (i.e. by
providing the named researcher, Carlos Torres, with postdoctoral
funding) but also indirectly: after completion of the project, Torres
will return to an academic post in his home country (Chile) where he
will be able to encourage a new generation of early-career Chilean
researchers to choose UK as their preferred research destination,
consolidating the UK's position as one of the leading countries for
attracting global talent.

In addition to the above, the project will also have economic impact.
The oil and gas industry has been a major contributor to the UK
economy for decades. However with North Sea oil fields now very
mature, oilfield revenues face significant decline unless recovery
techniques manage to improve. Improving recovery will also have an
economic benefit as the UK oil industry gradually moves toward
decommissioning: there is a clear economic driver to extract as much
oil as possible from an oil reservoir prior to any decommissioning
operation.

Yet another impact of the project will be social. The oil and gas
industry is one of the biggest employers UK-wide, meaning that many
livelihoods depend on it. This project will provide modelling tools
and associated training for UK oil industry employees, enabling them
to plan and direct improved oil recovery operations, not just in the
UK, but anywhere in the world. This skill set and expertise will then
position the UK as a service provider to the oil and gas sector
globally, helping to create even more UK jobs whilst simultaneously
leading to impact far beyond UK-based extraction operations. Finally,
to ensure that there is a ready supply of trained UK people able to
fill these future UK jobs, we will use public engagement as a tool to
attract young people towards science and engineering disciplines. This
will be achieved with the help of the University of Strathclyde-based
public engagement group ``Really Small Science''.