Metallurgical logging and core-photography standardisation
Improved core logging and photography workflows to create more consistent treatment of recovery, core loss, geological boundaries, image naming and storage.
A selected and anonymised record of technical, operational and product work.
Improved core logging and photography workflows to create more consistent treatment of recovery, core loss, geological boundaries, image naming and storage.
Built an automated tool for producing end-of-hole charts and reviewing assay information.
Developed utilities that reduced repetitive preparation before survey and geological information was loaded into enterprise systems.
Developed an analytical tool linking gamma responses with logged stratigraphy to support geological interpretation and correlation.
Combined database records, maps and aerial imagery to assess historical drilling disturbance and rehabilitation status.
Developed a rules-based system for checking drilling and geological datasets, then re-engineered it from VBA into Python to improve speed, maintainability and scale.
Built automated report-generation and distribution workflows, progressing the process into a scheduled data pipeline with interactive reporting outputs.
Analysed recovery and production by geology, stratigraphy, shift, drilling method and ground conditions to distinguish operational performance from geological difficulty.
Built a reusable data model and reporting product for penetration rates by rig, geology, stratigraphy and operating conditions.
Created a spatial assessment workflow so planned holes could be checked against known underground hazards.
Combined geological, assay and spatial constraints to identify technically suitable alternative drilling locations.
Worked with data teams to expose drilling, logging and operational information in a governed enterprise data environment.
Developed a scheduling concept combining project priorities, expected drilling durations and available rig capacity.
Developed automated comparisons between contractor invoices and operational records to identify discrepancies.
Built an ArcGIS Pro Python toolbox that automated drilling pad and sump layouts and reduced repetitive GIS preparation.
Developed a reporting concept that progressively populated project-completion information from live operational and QAQC data.
Reviewed a large reporting portfolio, removed duplication and rebuilt priority drilling, geology and QAQC products in a modern BI platform.
Coordinated an AI project to recognise and classify information from core photographs, including the creation of review datasets and a validation workflow.
Developed a workflow concept for extracting depth and related metadata from core photographs to reduce manual indexing and improve searchability.
Identified and developed practical AI use cases across drilling, geology, earthworks, imagery and operational data.
Developed methods for classifying terrain and slope conditions to support drilling access, pad design and earthworks planning.
Developed GIS scripts that combined planning datasets, proposed drillholes and spatial assignment information.
Built a Python toolbox for optimising drillhole orientations and released it for operational testing.
Assessed whether heavy-equipment telemetry could improve earthworks forecasting and equipment-performance analysis.
Developed a machine-learning prototype using rolling behavioural features to identify equipment at elevated risk of crossing an approved work boundary.
Developed an AI-supported approach to drill-pad orientation and optimisation using geological, terrain and earthworks inputs.
Explored how pad-optimisation outputs could connect with operational planning and machine-guidance systems.
Developed an agentic AI workflow for assisting with density-hole program design while retaining deterministic geological and operational checks.
Developed a traceable scoring concept for assessing possible RC twin holes and supporting density planning.
Built an agentic AI application that queried governed data, applied spatial and geological checks, and proposed candidate drilling programs for user review.
Established a structured portfolio of geoscience AI projects with clear ownership, testing and validation responsibilities.
Developed a semantic layer and conversational analyst capable of answering natural-language questions across drilling, geology and QAQC information.
Helped develop a governed conversational interface that allowed users to interrogate operational and geological data without manually searching multiple reports and systems.
Combined activity, production, equipment and operator information to investigate operational performance and distinguish between allocation, task and equipment-related constraints.
Coordinated internal and external technical teams to establish a governed proof of concept for sharing operational data between systems.
Developed a concept combining geological logging, structured QAQC information, comparison holes and core imagery within a conversational analysis workflow.
Participated in a pilot to test rapid development and deployment of lightweight internal applications against governed geoscience data.