7th European Geothermal Workshop - Characterization of Deep Geothermal Systems

Session

Session 8: Computing and Data Management, Machine Learning

Oct 10, 2019, 4:00 PM

KIT - AudiMax (Karlsruhe)

143. The Development of a Coupled Wellbore-Reservoir Simulator for Geothermal Application

Maziar Gholami Korzani (KIT)

10/10/19, 4:00 PM

Topic 8: Computing and Data Management, Machine Learning

Oral

Boreholes under dynamic conditions are a highly non-linear and complexly coupled thermo-hydraulic system. Multiple parameters, for instance, temperature, pressure, specific heat, enthalpy, viscosity, flow regime, heat transfer, degassing, steam quality and salinity are inter connected. Production and injection often entail several engineering challenges and operational problems, within the...

118. Accelerating reactive transport simulations with on-demand learning algorithms

Dr Allan M. M. Leal (ETH Zurich)

10/10/19, 4:15 PM

Topic 8: Computing and Data Management, Machine Learning

Oral

Reactive transport simulations help us better understand how geochemical reactions affect complex geothermal systems. However, geochemical reaction calculations can be extremely costly, sometimes accounting for over 99% of all computing costs in the simulation. As a result, the common practice is to simplify chemical details of fluids and rocks in the computer model to make it more...

128. An efficient discrete fracture model for variably saturated flow in fractured porous media

Behshad Koohbor (LHyGeS, University of Strasbourg)

10/10/19, 4:30 PM

Topic 8: Computing and Data Management, Machine Learning

Oral

Flow in fractured porous media is encountered in a broad spectrum of industrial, environmental, and engineering applications. This covers, for example, geothermal systems and hydraulic fracturing, carbon dioxide sequestration, management of karstic aquifers, and oil production. For those and other applications, modeling has become an indispensable tool for several purposes, such as...