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When companies want to extract heavy oil from low-pressure or depleted fields, they often inject other fluid into the formation to displace the oil. In short, fluid is pumped into a well at one location, putting pressure on the oil and making it easier to pump out of the ground at another location.
The problem is that the way the fluid will flow and react with oil underground is not always an exact science, according to University of Regina petroleum engineer and software developer Qingwang Yuan. Sometimes the process is messy and oil gets left behind.
The 34-year-old postdoctoral fellow’s software uses geological data, including permeability, porosity and the condition of a reservoir to better predict the contact and resulting flow patterns of injection fluids and oil.
“We simulate this movement from the injector to the producer,” Yuan said.
Through such a simulation, he said, optimal injection pump rates can be determined.
Currently, some commercial simulation software tries to replicate what his program does, but the results are not the same, he said.
“They mainly focus on the whole field and they cannot very accurately capture the very detailed fluid dynamics between the solvent and oil.”
The data provided by his software, Yuan said, is capable of providing much more accurate simulations. As such, he hopes it can be coupled with commercial software for field testing in the future.
Currently, no field testing has been done using the software. However, Yuan is confident that it can and will produce real-world results.
“The results show that we can improve the heavy oil recovery by about 20 to 30 (per cent),” he said.
The software was primarily developed to assist in oil extraction, but Yuan says it might have future value in other areas.
For instance, in the case of a significant chemical spill, Yuan’s algorithm could potentially provide information valuable to public safety.
With some tweaking, Yuan feels his program could help predict not only what path a chemical might take after it seeps into the ground, but also how long it would take to reach a source of drinking water.
Yuan began working on the software in April 2016. His work on the software earned him the Mitacs Award for Outstanding Innovation.
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By: Brandon Harder