Fluids interact with faults and fractures in the subsurface—a complex coupled system involving physical and chemical processes across multiple scales. The research combines mathematical and computational modeling with laboratory observations to uncover the fundamentals of friction and poromechanics.

The research is split into three (3) categories:
- induced seismicity: the role of fluid pressure in fault stability;
- enhanced geothermal systems: how fluids interact with fractures and how that interaction affects friction and flow properties
- multiscale modeling: earthquake source and fracturing processes involve multiple spatial and temporal scales, where processes at one scale often influence behavior at another; such multi-scale dynamics may be best modeled with ML / AL techniques

Fault poromechanics research advances the understanding of fluid–fault interactions and contributes to strategies that minimize seismic risks while maximizing fluid flow associated with subsurface energy operations, including CO₂ sequestration and geothermal energy. Insights can also be extended to other geohazard problems such as non-volcanic tremors and landslides.

RockGem address rock- and geomechanical behavior of fractured reservoir rocks (both carbonates and clastics) under drilling, completion, and production conditions – in particular in response to pore pressure changes and how they impact reservoir fluid flow and production. Results from these research activities – conducted mainly in GEMs state of the art rock mechanics laboratory – provide disruptive insights into rock’s constitutive behavior and associated fluid flow models.

Closed-Loop Reservoir Management (CLRM) represents a critical approach to optimize performance in geo-energy fields while systematically addressing risks from subsurface uncertainties, operational challenges, economic and environmental factors.

This research focuses on developing the next generation of Intelligent Closed-Loop Reservoir Management (iCLRM) framework to achieve superior capabilities in real-time predictive modeling, accurate physics characterization, uncertainty quantification, and intelligent decision-making. The framework blends cutting-edge computational methods with fundamental reservoir engineering principles to resolve challenging geo-energy problems. Specifically, iCLRM incorporates several key components: efficient surrogate modeling using the state-of-the-art deep learning and reduced-order models; high-fidelity physics simulation employing modern scientific computing methods; history matching enhanced by deep learning to calibrate reservoir models with multitude field data while quantify uncertainties; and reservoir optimization accelerated by deep learning to efficiently optimize reservoir performance with considering geological uncertainties and operational constraints. These technical advancements will position iCLRM as a practical and paradigm-shifting solution for the energy industries who seeks for efficient and sustainable management of geo-energy processes, from hydrocarbon and geothermal recovery to geological storage of CO2 and H2.

This research focuses on the development of advanced mineral extraction and processing technologies that minimize environmental impact while ensuring economic viability. We use a combination of thermodynamic modeling and process experiments with detailed mineralogical characterization, geo-metallurgical resource modeling, and stochastic optimization to achieve these goals. Specific areas of interest include the decarbonization of cement and magnesia production, comminution energy reduction, the use of hydrogen plasma in pyrometallurgical processes, the recycling of voluminous waste products like phosphogypsum and mine tailings, and the better valorization of by-products like rare earth elements or indium from existing process streams.

Collaboration with the cement industry through the Future Cement Initiative (FCI), and with Maaden on ore reduction and processing are key aspects of this research theme.

Cutting-edge efforts in carbon mineralization and mineral extraction developed innovative solutions to address climate and resource challenges. The expertise spans both in-situ and ex-situ CO₂ mineralization in basaltic and ultramafic formations, combining advanced geochemical modeling, field-based geological assessment, and laboratory experimentation. This involved the successful design and implementation of Saudi Arabia’s first CO₂ mineralization pilot in Jizan – in collaboration with Aramco – as well as a novel technology for accelerated basalt dissolution and selective recovery of valuable metals.

In an environment where major mineral discoveries are less and less likely to be made at the Earth’s surface, new approaches to mineral exploration are required to secure future supply. Integrating recent advances in remote sensing technology, geophysical and geochemical exploration methods, geological modelling techniques, and machine learning tools establish a novel and intelligent exploration framework. The goal is to acquire high fidelity information for exploration targets and explicitly accounting for subsurface uncertainties. Results help exploration companies to optimally allocate their resources for data acquisition and exploration drilling. This offsets increased costs from ever more complex exploration problems. In addition, the developed technologies have clear applications in the exploration for renewable energy resources such as geological H2, as well as low-carbon extraction and processing of minerals.

This research is fundamentally focused on understanding the regional geology of Arabia and the Red Sea in particular. It provides a critical foundation for hydrocarbon, mineral, and geothermal resource exploration, as well as underground gas storage and CO2 sequestration. The GEMs laboratory is equipped to prepare geological samples for optical and electron microscopic studies and XRF, XRD, and ICP-MS analyses.

GEMs cutting-edge research infrastructure enables advanced R&D in improved oil recovery through a comprehensive suite of experimental and modeling capabilities. The platform supports detailed investigations into conformance control and water shut-off techniques with specialized expertise in well testing and stimulation to assess reservoir performance and boost production. We conduct advanced chemical treatment studies using tailored polymers and surfactants to address complex reservoir environments. This also includes active research in CO₂-enhanced oil recovery (CO₂-EOR) through core flooding experiments and numerical simulations. Complementing these efforts is fundamental research in adsorption, wettability alteration, and interfacial dynamics, using microfluidic systems and core flooding setups. Advanced imaging tools such as micro-CT and NMR enhance these studies as they provide high-resolution insight into fluid-rock interactions and pore-scale flow behavior.