AI-powered exploration intelligence
Transform seismic uncertainty into investment-grade exploration opportunities through physics-guided prospect validation and machine learning.
Our proprietary workflow reveals direct hydrocarbon indicators (DHI) in invisible reservoirs, the low-amplitude targets that conventional screening overlooks. It works at depths up to 8,000 m, on 3D, 2D and multi-client seismic data. No other team or company offers this capability.
Trusted science. Practical decisions.
Physics-based
Every result is anchored in rock physics and AVO (amplitude versus offset) theory before any model is trained.
AI-enhanced
Machine learning screens large volumes for the subtle signatures an interpreter cannot scan by hand.
DHI validated
Each lead is checked against its direct hydrocarbon indicator elements and given a confidence score.
Prospect ranked
Validated opportunities are ranked with probabilistic risk, ready for a portfolio decision.
CoreFlowDDAV™ exploration intelligence, end to end
CoreFlowDDAV™ (Deep Detect AVO Validation) is built to find what conventional screening leaves behind: invisible reservoirs and their DHI elements.
How our workflow differs
| Conventional screening | CoreFlowDDAV™ | |
|---|---|---|
| What it looks for | High-impedance, bright-amplitude opportunities. These carry more risk: they are often water-wet or low-quality reservoir. | Invisible reservoirs: low-amplitude targets, extracted together with their DHI elements. |
| Depth | DHI confidence falls away as amplitude weakens with depth. | Engineered for targets up to 8,000 m. |
| Seismic data | Usually limited to 3D volumes. | 3D and 2D seismic, including multi-client surveys. |
| Rock type | Mostly clastic amplitude plays. | Clastic basins with CoreFlowDDAV™; carbonate basins with CoreFlowCDAV. |
| Regional scale | Prospect-by-prospect interpretation. | Fast DHI extraction across regional data: 10,000 km² within two months. |
| What you receive | An amplitude anomaly map. | A physics-anchored DHI confidence score and a ranked prospect list. |
Our innovative workflows and where each is used
CoreFlowDDAV™
Physics-guided AVO and DHI screening for deep clastic targets, with a quantified DHI confidence score.
Use it to find invisible, low-amplitude reservoirs down to 8,000 m on 3D and 2D seismic.
CoreFlowCDAV
DHI and fracture-indicator screening built for the carbonate domain, to 8,000 m.
Use it to detect DHI in porous carbonate capped by tight carbonate, and to separate hydrocarbon-bearing from water-bearing carbonate.
CoreFlowDI
Gradient-boosted machine learning that extracts facies and fluid signatures from the seismic.
Use it to define sweet-spot areas once CoreFlowDDAV™ screening has located the opportunity.
CoreFlowDR
A reduced-input route for surveys where the far-angle stack is unavailable.
Use it to screen legacy or incomplete data; it delivers about 60% of CoreFlowDDAV™'s DHI opportunity identification.
Stochastic Multi-Scenario Engine
Probabilistic simulation of AVO and elastic response across many rock and fluid scenarios.
Use it to quantify how far the hydrocarbon case can be told apart from brine before committing to a well.
Regional DHI extraction
CoreFlowDDAV™ run at regional scale: 10,000 km² within two months.
Use it to screen licence rounds, regional 2D grids and multi-client seismic libraries for DHI leads.
Why CoreFlowMC
Reduce exploration risk
Physics-anchored validation before capital is committed.
Identify subtle opportunities
Invisible reservoirs that amplitude-led screening passes over.
Increase prospect confidence
A quantified DHI confidence score for every lead.
Accelerate decision making
Ranked prospects with the evidence attached.
Deep reach
DHI detection for targets up to 8,000 m, in clastic and carbonate basins.
Works on the data you have
The same workflow runs on 3D volumes and 2D lines, including multi-client seismic.
Fast DHI extraction for regional data
Regional screening completed within two months.
Validation & recognition
Energy Award winner
Back-to-back wins in 2025 and 2026.
International peer-reviewed publications
Many papers published in international peer-reviewed journals.
Industry validation projects
Blind-tested well predictions.
Online toolbox
32 subsurface tools that run in your browser, from rock physics to well planning.
Rock physics and fluids
Fluid Properties Calculator Gassmann Fluid Substitution (deterministic) Stochastic Fluid Substitution Shear Velocity Estimator and Elastic Log QC Rock Physics Template PlotterAVO and DHI
AVO Modeller and Class Identifier Tuning and Wedge Calculator Seismic Net Pay Estimator (Connolly) Invisible Reservoir Detectability Screener DHI Evidence Checklist Low-Saturation Gas Sensitivity Extended Elastic Impedance ExplorerSeismic data quality and imaging
Resolution and Fresnel Zone Calculator Angle Range and AVO Data Adequacy Check Polarity and Phase Helper Imaging Problem DiagnosticDepth, volumes, risk and value
Depth Conversion and Depth Uncertainty Deterministic Volumetrics Stochastic Volumetrics (Monte Carlo) Geological Chance of Success Calculator Prospect EMV and Value of InformationPetrophysics and problem diagnostics
Log Net Pay and Cut-off Sensitivity Carbonate Pore-Type Screener Fracture Indicator and Azimuthal AVO Feasibility Volcanic Ash and Volcanics IndicatorMarkets we serve
Case studies
Deep Miocene, offshore Nile Delta
AVO Class II soft-kick detection for deep Miocene targets, using rock physics modelling and stochastic simulation across cap-rock scenarios.
Low-amplitude prospect identification
Spectral decomposition, AVO classification and a neural network used to detect low-amplitude gas sands.
Prospect ranking and risk reduction
An integrated AVO and machine learning framework, validated by matching forward-modelled and machine-learning gas sand probability cubes.
Investor profile
Ready to de-risk your next prospect?
Start with one prospect or one regional dataset.