Enthusiastic, skilled, and reliable geophysics engineer; pursuing for a challenging project based Ph.D. education that reflects my resourceful experience, skills, and personal attributes besides dedication, meeting goals, creativity, and the ability to follow through.
- MSc GEOPHYSICAL ENGINEERING, ISTANBUL TECHNICAL UNIVERSITY, MASLAK, ISTANBUL, TURKEY (2018-2019)
- BSc GEOPHYSICAL ENGINEERING, ISTANBUL TECHNICAL UNIVERSITY, MASLAK, ISTANBUL, TURKEY (2012-2017)
Project Title: Heterogeneities in hydraulic-mechanical coupled reservoir properties
Host Institutions: RWTH Aachen, ETH Zürich, Geoenergie Suisse
Supervisory Team: Florian Amann, Marian Hertrich, Peter Meier
Start date: 1.4.2021
Previous experience with intermediate scale in-situ stimulation experiments has demonstrated that heterogeneities in hydro-mechanical-coupled (HM) reservoir properties substantially affect the efficiency of stimulation and exploitation of reservoirs.
It is essential to anticipate such heterogeneities prior to operation and the design of hydraulic treatments from borehole logging and borehole testing.
The project aims at a systematic investigation of relationships between reservoir features (i.e. structures) and heterogeneities based on existing data from in-situ experiments and new data acquisition.
The main purpose of this research is to establish a workflow to quantify subsurface uncertainty of hydro-mechanical properties in a realistic 3D structural environment in enhanced granitic reservoirs by integrating data from different sources. Uncertainty parameters in question include fault and fracture densities and their geometrical attributes, permeability, porosity, rock deformation properties and resulting pressure distributions. For this purpose, I have applied fracture analysis to constrain the geometrical attributes of the fracture network at the ISC site (Grimsel lab) which will result in a range of probable discrete fracture network (DFN) simulations with FracMan software. To conclude, preliminary fracture network analysis allows us to build realistic 3D DFN models by constraining the thickness of damage zones and using orientation and frequency data as input.