Digital rock analysis goes mainstream
Professor Christoph Arns’ research focus is digital core analysis, particularly the classification or description of heterogeneity and its influence on physical properties. His research has revolutionised the oil and gas industry.
Professor Christoph Arns has been a pioneer in the field of digital rock analysis for the last 20 years and he led the petrophysics efforts of an UNSW/ANU consortium which, in 2015, established a unique 3D micro-CT facility at UNSW.
The exclusive facility enables researchers and industry to measure and characterise complex material structure and properties in 3D at high resolution under reservoir pressure conditions.
“The 3D micro-CT facility enables us to optimise strategies for oil recovery,” Arns says. “Our ability to observe the fluid flow process means we can better understand what surfactants do and how the residuals (i.e. oil) are distributed. Using that knowledge, we can modify the distribution of fluids, so the residuals can flow again.”
Unlike conventional core analysis, which works on the assumption that homogeneous rock samples comprise a single distinguishable rock-type, digital core analysis allows for a detailed assessment of the heterogeneity and classification of the physical properties of a core. This leads to more robust calibrations of well-logging data as well as a better understanding of mechanisms correlating different physical measurements, thus reducing uncertainty.
“Understanding heterogeneity is important, because it can lead to uncertainties in reservoir performance parameters, which is important to know if a single well can cost up to $US200 million, such as the Deepwater Gulf of Mexico,” he says.
Arns explains that the technique has other significant advantages, including the fact that it is much faster, taking weeks instead of months, and that it enables researchers to carry out numerical experiments where standard laboratory experiments are impossible.
“It also allows us to digitally ‘store’ samples, which we can make available worldwide and which can be shared and re-analysed with more advanced simulation tools as new techniques become available,” says Arns.
Understanding heterogeneity is important, because it can lead to uncertainties in reservoir performance parameters, which is important to know if a single well can cost up to $US200 million.
Professor Christoph Arns, School of Minerals Energy Resources Engineering
“There are also opportunities to reduce the carbon footprint of the industry because you can more efficiently recover resources. This is obviously quite interesting, especially when you add carbon capture and storage into the equation too.”
Although he has been working on digital rock analysis for many years, Arns says it is only recently that the technology is going mainstream. “Establishing digital core analysis in the, rather conservative, petroleum industry has required a paradigm shift, but now we’re at a point where the leading companies in the oil industry have formed their own internal research groups, and the technology is getting deployed,” he says.
At this delicate juncture, Arns sees his research group’s role as being about engagement as much as being about research. “There are not enough trained professionals available to do digital rock analysis, so we have a responsibility in terms of quality control, i.e. providing education and training PhD and postgraduate students in this technology,” he says.
“Our other engagement role concerns working with industry on advanced projects. Digital rock analysis is very complex and there is no one-size-fits-all approach. There has to be a very well-defined objective to actually get the benefits, and this is one way we can help industry.”
In terms of future research, Arns explains that his group’s key focus areas include the physical properties of complex fluids and their interactions with rock surfaces in heterogeneous rock. In particular, they will be looking at carbonates and finely laminated reservoir rock which is a target for future carbon dioxide storage.
“We are applying super-resolution and machine-learning techniques in the process of reservoir characterisation to quantify uncertainty stemming from small-scale details. Once we’ve achieved this, we will be able to develop efficient numerical algorithms to test and challenge our assumptions while embedding data structures for upscaling physical properties from the pore scale,” he continues.
The value of Arns’ work in enhancing the understanding of processes critical to oil and gas recovery has been widely recognised by the international scientific and industrial communities. The resulting innovative technology and its successful commercialisation has seen Arns awarded with Eureka and NSW Premier's prizes and named in the Engineers Australia Top 100 Engineers.