Original analysis, technical briefs, benchmarks and evidence-based perspectives on subsurface AI, data quality and the technical decisions that put capital at risk.
PINN AI Research is where we publish deeper work: the data behind an observation, the method used to reach it, the limitations that remain and why the result matters to a technical or capital decision. The goal is not content volume. It is useful, attributable evidence.
How AI can reduce a large well inventory to a smaller, ranked, technically reviewable opportunity set — without replacing technical judgment.
A data-backed look at what happens when well count, evidence types, reconciliation work and cross-well comparisons grow faster than available technical time.
Well identity, curve coverage, provenance, reconciliation rates and where source records break down.
What changes when rock, production, completions, development context and uncertainty are evaluated together.
Original statistics and anonymized observations that help technical teams understand scale, coverage and decision friction.