CCS Reservoir Simulation using Graph Neural Networks: Building ML solutions for efficient CO2 subsurface modelling

Reducing cost and improving computability of reservoir simulation is an important goal in the process of enabling CCS (Carbon Capture \& Storage) as a large-scale technology for mitigating CO2 emissions. In terms of computation time data-driven approaches have potential to outweigh the performance of numerical reservoir simulators, learning...

Time-lapse monitoring with virtual seismology: Applications of the Marchenko method for observing time-lapse changes in subsurface reservoirs

Monitoring time-lapse changes inside the subsurface is of great significance to many geotechnical applications, such as storage of gasses in underground geological formations. Minute differences in the seismic wavefield between an initial baseline and a subsequent monitor survey have to be detected in order to observe fluid flow inside...

Data assimilation for geothermal doublets using production data and electromagnetic observations: Assimilation of production and EM data

The data assimilation process for geothermal reservoirs often relies on well data which primarily offers insights into the immediate vicinity of the borehole. However, integrating geophysical methods can provide valuable information beyond well proximity, possibly enhancing reservoir predictions. Electromagnetic methods can be sensitive to the...

Testing a Thermal Dispersion-Based Upscaling Method for Geothermal Reservoir Simulation

The United Nations’ Paris Agreement forces nations and industries to transition from conventional hydrocarbon-based energy sources to more sustainable and less-emitting alternatives such as geothermal energy. Geothermal doublets are used to provide a source of green heat to greenhouses and residential buildings. In industry, reservoir simulators...

Multi-Objective Optimization of the Punchiná reservoir in Colombia

Punchiná reservoir is part of the San Carlos Hydroelectric Power Plant, situated in the Guatapé watershed. The Guatapé river is an affluent of the Samaná Norte river, which in turn is an affluent of the Magdalena river. San Carlos Hydroelectric Project uses the waters from the rivers San Carlos and Guatapé and discharges the turbined flow...

Seasonal Hydrogen Storage in Dutch Depleted Gas Reservoirs: A Feasibility Study for The Netherlands

The Netherlands will need to transform her traditionally fossil fueled energy system in the coming decades to achieve the goal of reducing CO2 emissions to net-zero in 2050. Therefore, an increase in renewable energy sources as solar and wind energy in the overall energy mix will be essential. However, due to the highly variable energy...

Reservoir Simulation for Play-based Development of Low Enthalpy Geothermal Resources: Application to the Delft Sandstone

As implementation of deep geothermal energy projects in the Netherlands increases, reservoir simulation for these geothermal systems stands to play a key role in understanding how these systems will behave and how large scale projects can be optimised to save cost and reduce risk. In this thesis, an extensive simulation study has been conducted...

Proxy-model for Flow and Transport in Geothermal Reservoirs

The hot water produced from a geothermal doublet possesses energy, which once utilized, the water cools down and is re-introduced back into the same reservoir at a sufficient distance using an injector well. As cold water flows through the reservoir, it acquires thermal energy from surrounding in-situ rocks. This process recurs until a...

POD-Based Deflation Method For Reservoir Simulation

Simulation of flow through highly heterogeneous porous media results in large ill-conditioned systems of equations. In particular, solving the linearized pressure system can be especially time-consuming. Therefore, extensive efforts to find ways to address this issue effectively are required. In this work, we introduce a POD-based deflation...

Modeling and Upscaling of Shale Gas Using a Discrete Fracture Modeling Approach

Gas flow in fractured nano-porous shale formations is complicated by a hierarchy of structural features, ranging from nanopores to microseismic and hydraulic fractures, and by several transport mechanisms that differ from standard viscous flow used in reservoir modelling. In small pores, self-diffusion becomes more important than advection, also...

Permeability Estimation Using a Non-Parametric Bayesian Network

This thesis addresses the problem of permeability estimation of an oil reservoir using oil production data, a process known in the oil industry as computer-assisted history matching or data assimilation. Zilko (2012) compared the well-known Ensemble Kalman Filter method for data assimilation with the Non-Parametric Bayesian Beliefs Network (NPBN...

Non-Parametric Bayesian Networks (NPBNs) versus Ensemble Kalman Filter (EnKF) in Reservoir Simulation with non-Gaussian Measurement Noise

Lately, the objective of reservoir engineering is to optimize hydrocarbon recovery from a reservoir. To achieve that goal, a good knowledge of the subsurface properties is crucial. The author is concerned with estimating one of the properties of the field: the permeability of a reservoir. To characterize the fluid flow, a two phase (oil-water)...