Dr. Denis Voskov

Dr. Denis Voskov is an Associate Professor at the Department of Geoscience and Engineering, TU Delft, and Adjunct Professor at the Department of Energy, Science and Engineering, Stanford University. He is leading a research group on the development of advanced simulation capability for energy transition applications which includes geothermal, CO2 sequestration and hydrogen storage. Dr. Voskov is a co-author of more than 50 peer-reviewed journal publications and many conference papers on this topic. Before joining TU Delft, Denis was a Senior Researcher at the Department of Energy Recourses Engineering, Stanford University. His previous positions also include Chief Technology Officer of Rock Flow Dynamics Company (developer of t.Navigator), Chief Engineer at YUKOS EP company, and a leading specialist at the Institute for Problems in Mechanics, Russian Academy of Sciences. He holds a Ph.D. degree in applied mathematics from Gubkin’s Russian State University of Oil and Gas. Dr. Voskov is an Associate Editor of the Society of Petroleum Engineers and Geoenergy Science and Engineering Journals.

Abstract

Improving Geothermal Energy Production: Forward Modelling and Data Assimilation with Consideration of Uncertainty

In my talk, I will first introduce the DAPwell project, a living lab that will be a focal point of deep geothermal research and education at TU Delft. This project involves the drilling of a geothermal doublet designed for direct heat purposes. The production and multiple observation wells will be equipped with a wide range of advanced geophysical tools for monitoring and data acquisition. However, effective utilization of this data presents new challenges for forward modeling, data assimilation, and uncertainty quantification in geothermal energy production. During my talk, I will showcase the modeling technologies we have employed to accurately reproduce production and monitoring results while preserving and updating the geological model. Since the characterization of the reservoir entails uncertainties, it is crucial to perform accurate uncertainty quantification, which we can now achieve at a geological scale and fully support with distributed pressure, temperature, strain, and acoustic measurement inside the production well. Besides, additional information from electromagnetic sensing in the ultra-deep observation well will be integrated into the data-assimilation framework for the DAPwell project. To thoroughly evaluate potential hazards arising from hydraulic and thermal stresses, we have developed a fully coupled formulation with geomechanics. The modeling results can be linked with strain and acoustic sensing inside the production well and shallow observation wells around the doublets. To integrate all these forward and inverse modeling technologies, we have implemented them in our open-source modeling platform called the Delft Advanced Research Terra Simulator (DARTS). The combination of these modeling technologies and the DARTS platform empowers us to create an efficient and effective digital representation of the DAPwell project, enabling us to optimize energy production while ensuring its safety and sustainability.