Industry collaboration / Serpentinite Labs
Petroleum: geological workflows and AI collaboration
We are interested in working with petroleum geoscience teams on how geological descriptions and their supporting evidence move between field records, data tables and technical reviews.
Focus on the handover between people and tools
Descriptions can lose context when copied between documents and spreadsheets. A potential collaboration could focus on organizing measured-section records, checking naming conventions and units, or linking a data entry to its source photograph and notes.
Keep interpretation reviewable
An AI-generated summary should identify the source records it uses and leave uncertainty visible. Lithological similarity alone does not establish a correlation. Review criteria and responsibility for interpretation need to be agreed with the participating geoscientists.
Current scope
G-Spyke supports stratigraphic field documentation. We do not currently offer a dedicated petroleum product, reservoir simulator, well-log interpretation system or production forecasting tool. Sector-specific work would be developed and evaluated with partners.
Discuss a practical collaboration
A suitable first discussion includes one repeatable task, an authorized sample of data, the required deliverable and the current review process. The aim is to test usefulness on that task before proposing a broader integration.