Application of the Non-Intrusive Reduced-Basis Method in Magnetotellurics for High-Temperature Geothermal Systems

Estimating the lithium content in a hydrothermal reservoir using a modelling-based sensitivity analysis: Case study at the location Horstberg

The North German basin holds high potential for geothermal lithium exploration. Yet, so far, the assessment of reservoirs concentrates on locations in the Upper Rhine Graben. This thesis gives an example for the evaluation of a potential geothermal lithium reservoir of the Middle Buntsandstein at the location Horstberg in Lower Saxony. The...

Combining Geophysics and Basin Modeling to Develop a Thermal Model in an Offshore Block, Mexican Gulf of Mexico: Constraining Source Rock Maturity Through OAT Sensitivity Analyses of Key Inputs

The recent discovery of the Zama field in offshore Sureste Basin in the southern Gulf of Mexico has piqued interest in the Mexican petroleum industry regarding the hydrocarbon potential within the region. In this study, a deposition-only thermal model was developed in an area of interest (AOI) in this region. Using structural input obtained from...

Monitoring Backward Erosion Piping with Self-Potential Geophysics

Backward erosion piping is a dike failure mechanism. It is the internal erosion process by which sand is eroded away from underneath a dike or levee by seepage flow. This erosion process progresses in the direction opposite to the direction of seepage flow and forms a small pipe directly beneath the dike. As erosion continues, this process can...

Inversion of ERT data including uncertainties using the FE and RB methods

The inversion process of data sets acquired with the electrical resistivity tomography can be a computational expensive calculation, because it requires a lot of forward simulations. Since computational resources are limited, the inversion for large field surveys can require immense computing times. One approach for reducing the computing times...

Coupling unsupervised segmentation in wells with automatic implicit modeling in a Bayesian framework

The automatic interpretation of well logs has been the focus of research, especially in oil and gas industry, for more than 50 years and, aside from that, benefits from the fast developments of machine learning algorithms during the recent decades. Moreover, Bayesian inference is increasingly utilized to model geological data, enabling the...

Using reflected seismic waves to estimate rheological properties of the fluid-mud layer for port applications

Current Port of Rotterdam procedure is to define the nautical depth based on the density of a fluid-mud layer, that settles at the bottom of the port. Rheological parameters could be an improved indicator for nautical depth and decrease the frequency and cost of dredging. I investigate the use of reflected seismic waves to derive in situ...