Research Work

Petroleum Projects

Master in Applied Geology (cum laude)

Fluid identification with the use of Petrophysics and Rock Physics of Bredasdorp Basin, South Africa

This study uses an integrated approach of Petrophysics and Rock Physics to analyse and improve reservoir forecasting. The goal of this study was to compute the clay volume, porosity, permeability, cementation factor, and fluid zones.

Additionally, the fluid substitution model was utilized to determine the effect of different pore fluids (brine, oil and gas) on acoustic properties (compressional velocity, shear velocity, and density) using the rock frame properties. Furhtermore, this research aimed to generate rock units based on core permeability and porosity using Winland R35 and Flow Zone Indicator methods. The analysis included core logging, creation of thin section, XRF analysis, core porosity and permeability determination with PoroPerm, Water Saturation determination with EPS-A, and finally the use of Interactive Petrophysics to model laboratory results.

Article: Reservoir Characterization through Integrated Petrophysical Analysis, Hydraulic Flow Zonation, and Rock Physics in the Bredasdorp Basin

www.researchgate.net/publication/394959094_Reservoir_Characterization_through_Integrated_Petrophysical_Analysis_Hydraulic_Flow_Zonation_and_Rock_Physics_in_the_Bredasdorp_Basin

Machine Learning for Reservoir Property Prediction

Explored machine learning approaches for predicting reservoir properties using wireline log data.

Models were trained on Gamma Ray, Resistivity, Porosity, and Permeability logs within a known interval (1500–2300 m), then used to predict porosity and permeability in an unknown interval (2350–2450 m) using only Gamma Ray and Resistivity logs.

Models Tested

Gradient Boosting
Random Forest
Neural Network (MLP)
Polynomial Regression

Key Observations

Gradient Boosting and Random Forest captured porosity trends reasonably well.
MLP and Polynomial Regression struggled, likely due to limited training data.
Permeability prediction remains challenging because of its complex relationship with pore structure.

Inspired by the growing use of AI in subsurface workflows across SLB, Halliburton, and Baker Hughes.

Geospatial Analysis & GIS Projects

Drone mapping meets geology

I took the opportunity to fly a drone over an area and used QGIS to create a 3D surface model, integrating underground borehole data into the visual. This experience reminded me of how powerful geospatial tools are in modern geology, blending fieldwork, remote sensing, and data integration to tell a more complete story. I'm excited to keep learning and applying digital tools in geology

Drone Technology

Using drone technology, digital elevation models, and Agisoft photogrammetry software to showcase an existing glory hole. By combining aerial data with 3D modelling, I was able to create a detailed visualization that highlights how modern digital tools can enhance the way we study and interpret geological features. This workflow not only improves safety by reducing the need for physical access but also provides high-resolution insights for geological understanding and planning. Let's keep exploring the intersection of geoscience and digital innovation.

Exploration Geology

Integrated Exploration Geology Workflow

Developed a conceptual exploration geology workflow integrating geological interpretation, borehole analysis, GIS-based spatial interpretation, and 3D subsurface visualization.

Project Components

Regional geological mapping
Borehole visualization and interpretation
Fe assay analysis and mineralization classification
Grade distribution and depth analysis
Weighted average grade calculations
Exploration-style reporting and presentation outputs

The project simulated how geological, spatial, and assay datasets can be integrated into a modern exploration targeting workflow.

All datasets used were synthetic/generated for demonstration purposes, while reflecting real-world exploration and geological concepts.

This project strengthened my interest in the intersection of geology, GIS, data analysis, and technical interpretation within the mining industry.

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