Energy & Resources
Mining & Resource Extraction
Identify governing geomechanical laws and extraction dynamics from drilling, sensor, and production data.
One of 34 industries across 8 sectors served by CDE — the Causal Dynamics Engine for Science and Engineering.
The Challenge
Why Mining & Resource Extraction teams still struggle to explain what is happening
Mining operations generate diverse, high-volume data streams (drill performance metrics, geotechnical sensor readings, ore grade assays, blast fragmentation measurements, equipment telemetry, environmental monitoring) that encode the geomechanical, geochemical, and operational physics of extraction systems. Despite extensive instrumentation, companies typically analyze these streams in isolation using domain-specific empirical models that cannot capture interactions between geological conditions, equipment performance, and extraction parameters. The result is suboptimal resource recovery, reactive maintenance, and safety margins set by convention rather than quantified physical understanding.
Geological block models calibrated through geostatistical interpolation and processing models tuned through extended plant trials both require months of specialist effort and produce results that degrade as conditions change. Rock mass behavior under varying stress, water, and temperature follows nonlinear dynamics that empirical classification systems approximate at best. Comminution and flotation exhibit regime-dependent behavior where the governing physics shifts with ore type, feed characteristics, and equipment wear.
The CDE Approach
How CDE closes the explanation gap in mining & resource extraction
CDE takes drill performance logs, geotechnical sensor streams, ore grade assays, and processing plant data, then discovers governing geomechanical relationships across the entire extraction value chain. Rather than treating geological, mechanical, and process data as separate domains, it identifies cross-domain equations: how rock properties determine drill performance, how ore characteristics drive processing behavior, how equipment loading affects wear dynamics. This integrated approach surfaces relationships that siloed analysis misses.
Causal mode identifies root causes of operational anomalies, distinguishing geological factors from equipment issues from operational parameters. Regime classification detects transitions in rock mass behavior, plant dynamics, and equipment condition without manual threshold setting. The Evidence Ledger provides full provenance for every discovered relationship, supporting environmental and safety reporting requirements, with negative controls validating generalization across geological zones.
Discovery Engine
How CDE applies here
Symbolic discovery produces closed-form relationships between drilling parameters and rock properties, ore grade distribution laws, and equipment degradation equations that operations teams can directly act on. Causal mode addresses multi-variable attribution: whether a production shortfall stems from geological variability, equipment wear, or process parameter drift. Neuro-Symbolic mode handles complex geomechanical data, where the engine's internal methods capture geological variability before structure extraction yields interpretable governing laws for mine planning and geotechnical design.
Causal Graphs
Discovers directed causal structure from observational data — identifiable causal graphs, regime classifications, and intervention predictions.
Governing Equations
Extracts compact governing laws grounded in the causal structure — interpretable equations your team can read, verify, and compare against known theory.
Intervention Design
Proposes targeted experiments to resolve ambiguous causal edges — maximizing information gain where the causal structure is still uncertain.
Causal Validation
Negative controls, falsification tests, and identifiability analysis applied to every causal claim before promotion to the evidence ledger.
Typed Scientific Claims
What CDE discovers
Every discovery CDE produces is a typed scientific claim — not a black-box prediction, but a governed, reproducible, auditable piece of scientific knowledge with full provenance.
- Geomechanical governing equations
- Ore grade prediction models
- Equipment degradation laws
- Extraction efficiency dynamics
- Blast fragmentation models
Governed Discovery
Make the finding reviewable
Every discovery CDE produces carries the review context around it: a Truth Dial setting, an evidence entry with replay context, and control results including bootstrap stability, out-of-distribution testing, and feature-shuffle validation.
For mining & resource extraction, that means teams can compare runs, justify decisions, and decide whether a finding is ready for internal use, external review, or regulated submission.
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Put CDE on a real mining & resource extraction problem
Whether you are exploring mining & resource extraction data for the first time or scaling an existing research programme, CDE adapts to your workflow. Bring the dataset, the decision pressure, and the constraints. We will map the right discovery path.