Flow in porous media – a “multiscale” challenge

Dr Peyman Mostaghimi specialises in flow in porous media and characterisation of fractured and unconventional reservoir rocks to improve the productivity and competitiveness of energy resources in Australia.

Dr Peyman Mostaghimi is a Senior Lecturer in the School of Minerals and Energy Resources Engineering. He joined UNSW in 2014 to continue the research he started during his PhD and postdoctoral research on flow and transport in complex porous media and rocks.Peyman Mostaghimi

“My work has primarily concerned working on digital rock physics to understand transport phenomena at the pore scales and predict rock properties at the continuum scale,” he says.

“My research has significance to a wide range of applications from water resources and environmental sciences to geothermal and petroleum engineering.”

In 2015, he teamed up with Dr Armstrong to create the MUTRIS research group (Multiscale Transport in Porous Systems) which works on a range of projects from the very small to the very large scale. “When we are talking about flow and transport in porous media we are talking about a multiscale process, from microns to kilometres,” he continues.

Over recent years, Mostaghimi has focused on building novel routines and methods for analysis of fractured coal seam gas reservoirs to reduce the uncertainty and risk associated with the production of natural gas from these unconventional resources. He is also concerned with analysing their impact on the environment and water resources.

Natural gas has the highest energy content relative to other fossil fuels while its greenhouse gas emission is the lowest. The increasing demand for natural gas has created interest in applying advanced characterisation methods to better understand gas production from coal seams,” he says.

Australia is one of the world’s largest exporters of natural gas. Significant technological advancements in natural gas production are required to ensure environmental protection while meeting worldwide and national energy demands. I want to play a role in this by helping the industry develop advanced methods and technology for improving the competitiveness of the energy sector while fully addressing the environmental concerns.”

I create visualisation of the geometry of rocks with resolution down to a few microns. This leads to better understanding of flow and transport in subsurface conditions required for large-scale reservoir modelling and characterisation.

Dr Peyman Mostaghimi, Senior Lecturer, School of Minerals and Energy Resources Engineering

Mostaghimi explains that he uses pore-scale experiments, and theoretical and numerical developments to get a better understanding of the unique mechanisms that happen in coal seams. “Improving this understanding will help the industry characterise the reservoirs and create high fidelity models for gas production and its impact on ground water,” he says.

According to Mostaghimi it is possible to use digital coal, i.e. reproducing a piece of coal using computer algorithms, to understand how the properties of the fractures that exist in coal affect its core-scale properties, including permeability and relative permeability.

“I have also used multidisciplinary methods including PET, positron emission tomography, and X-ray imaging (common methods in medical research) to further understand transport in rocks,” he says.

“Using these methods, I create visualisation of the geometry of rocks with resolution down to a few microns. This leads to better understanding of flow and transport in subsurface conditions required for large-scale reservoir modelling and characterisation.”

Recent technological advances have added to the tools in Mostaghimi’s toolbox and he says he has started to use artificial intelligence methods from the computer sciences to further advance the knowledge bank.

“UNSW has a great reputation when it comes to digital rock technologies, but these usually depend on extensive computational simulations for modelling transport that can be very expensive,” he explains.

“By using machine learning methods, we are able to reduce these costs by our ability to cross-correlate rock microstructure, using multi-resolution images, and predict effective rock properties.”

This is a growing multidisciplinary field that will, ultimately, lead to high-fidelity subsurface reservoir models that will help industry to optimise their production while controlling the environmental impacts.

“Coal seam gas has been controversial, and is an area of public interest, but with our novel methods for coal characterisation we should be able to evaluate and quantify their impact on our environment and groundwater supplies,” Mostaghimi says.


Written by: Penny Jones


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