A working portfolio documenting my transition toward roles at the intersection of subsurface geoscience and data science — combining geological domain knowledge with Python, machine learning, and geospatial tooling.
01-force2020-lithology/— wireline log lithology prediction (FORCE 2020 dataset), integrating physics-informed feature engineering with ML classification. (in progress)02-mineral-prospectivity/— spatial ML for mineral prospectivity mapping using open geoscience datasets. (planned)03-plate-reconstruction/— plate tectonic reconstruction using pyGPlates. (planned)04-seismic-basics/— introductory seismic interpretation with segyio. (planned)notes/— short technical write-ups accompanying each topic as I work through it.
PhD in Geodynamics (Istanbul Technical University), with a career spanning structural geology, petroleum systems, mineral exploration, and geotechnical data QA/QC. This repo tracks my hands-on return to subsurface data workflows, one topic at a time.
-
Wireline log fundamentals — GR, RHOB, NPHI, DTC and the physics behind lithology and gas-effect crossplots.
-
Sequence stratigraphy fundamentals — accommodation space, system tracts (LST/TST/HST), and why the maximum flooding surface is a strong source rock candidate.
-
Petroleum systems fundamentals — the five elements, timing risk, vitrinite reflectance, and CRS mapping logic.