Modelling the full system
"Operators mainly track pressure variations and try to infer what is happening from that," Ehsan says. "But those estimates are often uncertain, and by then it may already be too late."
The central ambition of his PhD project was to develop a predictive modelling tool that identifies when and where clogging is likely to occur. What distinguishes the approach is its scope: rather than treating the underground reservoir and surface infrastructure separately, the tool integrates both within a single coupled framework, linking subsurface conditions directly to system performance at the surface.
To complement the modelling work, Ehsan has conducted micromodel experiments in which clogging processes can be directly observed in porous media under controlled conditions. These experiments help clarify the underlying mechanisms while providing data to support model development.
Data availability has been a persistent challenge throughout the project. Most geothermal operational data is proprietary, limiting access for validation. To address this, Ehsan combined published datasets with systematic sensitivity analyses to assess how model outputs respond to uncertainty in input parameters. A collaboration with a geothermal company, initiated after a conference presentation, later provided an opportunity to apply the framework to real operational conditions.
"It turned out we were basically working on the same issues," he says.
Building on subsurface expertise
Ehsan joined DTU Offshore in February 2023, having studied petroleum engineering in Iran at Sharif University of Technology and Amirkabir University of Technology. His background is in subsurface fluid flow and reservoir behaviour, where many of the same physical processes apply. The transition to geothermal was, in this sense, a shift in application rather than discipline: the working fluid is water rather than hydrocarbons, and the objective is heat extraction rather than production of energy carriers.