Run
Engines
Physics-aware applications perform defined geoscience tasks with transparent configuration and complete scientific evidence.
Methods · physics · full QC
LithoSightDiscuss a pilot Geoscience engines that learn from experts
A new type of foundation modelfor geoscience.
LithoSight captures expert judgment, learns from it, and returns that expertise to every asset through physics-based AI engines.
Physics-based AI · Full QC · Expert control · Private deployment
EnginesFoundryFoundation modelIntelligence platform
01 / The constraint
Expert capacity sets the pace.
More compute accelerates runs. Experts still decide which results to trust. When the reasoning disappears at project close, the next asset starts again.
A trusted interpretationis a sequence of expert choices
01Inputs
02Options
03Iterations
04Expert action
05QC
06Accepted result
Inputs preserved
Context, alternatives and reasoning usually lost
Result preservedOne expert review creates a trusted result.
Captured properly, it also teaches future projects.
02 / The LithoSight system
From workflow to reusable expertise.
Foundry is where we build the intelligence. The foundation model and engines are how clients use it.
Capture
Foundry
Experts inspect results, compare alternatives, correct the work, and record why a result should be trusted.
Context · correction · reasoning
Learn
Foundation model
The model learns from reviewed examples and is evaluated on wells and geological settings it has not seen before.
Reviewed examples · held-out tests
Return
Intelligence platform
Validated model guidance returns through the engines, making captured expertise available to future projects.
Validated guidance · every asset
Run engines across wells.
Capture inputs, results, corrections, and reasoning.
Link reviews to context.
Retain scientific outcomes, QC, and provenance.
Test beyond the training set.
Measure transfer on unseen wells and geological settings.
Validated model guidance returns to the engines.
03 / What we have built
Seismic calibration redesigned.
TieSight combines physics-based AI, automated calibration, and complete QC. Foundry keeps the scientific evidence and expert decision linked so the feedback can become learning evidence.
Working nowTieSight calibration engine + Foundry expert review
Building nowFoundation Model V0.1 across broader geological settings
Bauer · Expert calibration review Working Foundry interface
Foundation Model ProgrammeGoverned evidence
Bauer · Full calibration QCEvidence before opinion
04 / What we have proven
The model learned to calibrate like an expert.
Expert feedback trained a model that improved calibration on wells excluded from its training. These Bauer results are the first proof that reviewed evidence can guide future work.
Lower error against expert corrections
Median RMSE reduction on wells excluded from training.
Of eligible wells improved
Measured on wells with expert correction targets.
Lower mismatch with observed seismic
Median RMSE reduction on held-out wells.
Evidence boundary
Bauer proof of concept · held-out-well evaluation · calibration only. Broader geological transfer remains the next validation step.
05 / Foundation model value
Change the economics of subsurface decisions.
Make advanced workflows easier to repeat, expert judgment easier to retain, and scientific quality easier to govern across a portfolio.
01Operation
More projects
Extend advanced geoscience workflows across more wells and assets without making scarce expert time the limiting factor.
02Speed
Faster decisions
Keep portfolios current and become ready for short decision windows when new data, opportunities, or risks emerge.
03People
Expertise retained
Preserve the context, corrections, and reasoning that usually disappear when experts move or projects close.
04Governance
Portfolio-wide QC
Apply one evidence standard across projects while keeping uncertainty visible and expert accountability intact.
Net effectBetter wells, faster decisions, retained expertise, and one consistent evidence standard across the portfolio.
Work with LithoSight
One company. Two ways to create value.
Test the intelligence system with us—or bring a defined geoscience challenge and use our in-house technology today.
Build the foundation with us
Run a LithoSight engine on your data, capture expert feedback in Foundry, and test transfer against explicit success criteria.
- Start with one asset and one decision
- Validate on held-out wells or settings
- Shape governance and private deployment
Solve a project now
LithoSight geoscientists use our in-house Interpret and Predict technologies to deliver a scoped technical result.
- Well-to-seismic calibration
- Fracture and thin-bed analysis
- Property and lithology prediction
06 / Modular expansion
Start with calibration. Expand across the subsurface.
TieSight is the first engine—not the final product. Foundry creates a common way to capture judgment across adjacent workflows while preserving each method’s scientific core.
Available engine
TieSight
Physics-based seismic-to-well calibration with automated candidate search, transparent configuration, expert review, and full QC.
Next engine
Seismic interpretation
Resolve ambiguous events, correct horizons and faults, and capture the evidence and uncertainty behind each interpretation.
Shared intelligence
Velocity modelling / FWI
Evaluate starting models, review convergence, investigate unreliable updates, and reuse trusted calibration evidence.
Shared intelligence
Seismic inversion
Choose constraints, test consistency with wells, and keep geological plausibility and expert acceptance explicit.
Modular expansion
Petrophysical properties
Extend the same governed approach to porosity, facies, TOC, net-to-gross, saturation, and permeability.
One foundation guides every engine.Every reviewed workflow strengthens the evidence base.
07 / Pilot path
Test the system on a real asset.
Start with a defined calibration problem, keep the validation boundary explicit, and scale only when the evidence supports it.
Frame
Select the asset, data, expert reviewers, and success criteria.
Run
Use TieSight across wells with complete configuration and QC.
Review
Capture expert decisions and evaluate honestly on held-out data.
Scale
Expand across wells, basins, or engines when transfer is proven.
Operators · Design partners · Applied projects
Put your data in front of the engines.
Prove the workflow on one asset—and shape what the foundation learns next.
Discuss a pilot