Skip to main content
QuarterlyCareersClient loginContactEN
earthscan
Book a demo

Insights

Sharing how the people building the field see the future of energy.

Featured
Subsurface AI

The Pilot That Pivoted: How a Geomechanics Proposal Shipped as a Fracture-Detection Transformer

The engagement we were funded to run in August 2020 was a 10-month geomechanics ANN estimating in-situ stress and elastic moduli from borehole deformation. What shipped, three years later, was a fracture, bedding and vug detection transformer. This is the honest account of how the technical core pivoted without the contract dying, and why the phase-gate structure is what made that survivable.

Tannistha MaitiTannistha MaitiSenior AI Researcher
Case study Article|8 min read
Showing 7 of 380 insights
Case study/MLOps

Agentic MLOps: From 6-week retrains to overnight

A global supermajor cut model retrain cycle time 40× and lifted production-forecast accuracy 22% using an agentic MLOps loop that monitors drift, reconciles data, and retrains autonomously — with geoscientists as approvers, not operators.
Tarry SinghTarry SinghFounder & CEO
Case study|8 min read
Case study/Computer Vision

From Pixels to Pores: Automated Vug Detection in Carbonate Reservoirs

A computer vision pipeline achieved 2,000× finer granularity than manual interpretation, recovering vugs missed by experts and delivering per-vug geometry at 0.1 m resolution across 200+ m of Middle East carbonate borehole image logs.
Tannistha MaitiTannistha MaitiSenior AI Researcher
Case study|7 min read
Case study/Computer Vision

Deep Learning for Fracture Detection in Borehole Images

A DETR-based model achieved 85% sensitivity for fracture detection in Middle East carbonate plays, cutting manual interpretation to validator-ready output.
Tannistha MaitiTannistha MaitiSenior AI Researcher
Case study|7 min read
Whitepaper/AI

Why General LLMs Fail at the Wellbore: The Case for Domain-Native AI in Petroleum Geomechanics

General-purpose LLMs like Copilot scored 25% on a controlled petroleum geomechanics benchmark, fabricating numbers in two-thirds of data-grounded queries. Domain-native AI architectures — built SQL-first, module-scoped, and refusal-aware — scored 95.8%. This whitepaper presents the benchmark, the failure modes, and the engineering principles that close the gap.
The EarthScan TeamThe EarthScan TeamResearch, engineering, and field
Whitepaper|19 min read
Stay ahead

EarthScan insights, in your inbox.

Field-tested research on subsurface and energy-transition AI. About twice a month. No noise.

We use your email only for this newsletter. Unsubscribe anytime Privacy.