One of many downstream use cases. This example focuses on crude acquisition and margin analysis, helping trading and planning teams optimize the spread between feedstock cost and product value.
Crude acquisition decisions involve balancing quality (assay characteristics), logistics (pipeline access, shipping), pricing (differentials, term vs. spot), and refinery capability (unit constraints, product slate targets). Your commercial team processes this information from multiple sources: brokers, market reports, internal planning, and makes decisions under time pressure.
The traders who excel have decades of pattern recognition. When they retire, that intelligence leaves with them.
Traditional approaches were not built for the scale and complexity of modern operations.
Crude netback calculations in Excel don't update with real-time market pricing or refinery yield changes.
By the time broker reports are compiled and analyzed, trading windows have closed.
Crude assays, market pricing, logistics costs, and refinery yields live in separate systems. Connecting them is manual work.
Market relationships (crude differentials, seasonal patterns, grade substitution economics) are known by experienced traders but not codified.
Three layers of intelligence working together: reasoning agents, proactive detection, and multi-agent deliberation.
Agents evaluate crude economics by connecting assay data, current market pricing, logistics costs, and refinery-specific yield predictions. Every analysis runs as SQL against your commercial and operational data.
Every calculation is SQL you can verify. No black box.
Evaluating Q2 Crude Acquisition Options: WCS (Hardisty): $58/bbl, pipeline cost $4.50, yield value $71.20 → Net margin: $8.70/bbl Cold Lake Blend: $61/bbl, pipeline cost $4.50, yield value $72.80 → Net margin: $7.30/bbl Syncrude: $72/bbl, pipeline cost $3.20, yield value $78.40 → Net margin: $3.20/bbl → WCS delivers best margin but requires 95% coker utilization → At current coker rate (88%), blend 75% WCS + 25% Syncrude optimizes net margin: $7.40/bbl
ALERT: WCS-WTI differential widened to -$22/bbl (30-day avg: -$15) Historical pattern: 3 of last 4 widening events >$20 reverted within 2 weeks Cause analysis: Temporary pipeline apportionment increase (Enbridge Line 3) → Opportunity: Lock in term barrels at current differential. Expected reversion value: $3.50/bbl on 30-day forward
The Radar monitors crude differentials, product crack spreads, and market structure for unusual patterns that signal trading opportunities or risks.
The Radar surfaces issues the operator didn't know to look for. Before they become incidents.
Trading, planning, and risk agents reason together on crude acquisition, hedging strategy, and product slate optimization.
The output is grounded in facts (SQL results), not hallucination. Every recommendation carries a full audit trail.
Trading Agent: WCS differential at -$22 is an opportunity. Recommend increasing term commitment Planning Agent: Coker turnaround in Q3 limits heavy crude processing for 45 days. Can't increase term above Q2 Risk Agent: Differential volatility is elevated. Recommend hedging 50% of incremental barrels with basis swaps → Consensus: Increase Q2 WCS term by 5,000 bbl/d at current differential. Hedge 50% with basis swap. Reduce Q3 term to match coker outage.
Lumina addresses the four strategic problems that hold operators back.
Evaluate every crude grade, every day, against current market conditions and refinery-specific economics.
Capture $0.50-2/bbl in margin improvement through optimized crude acquisition and product slate management.
Market relationships, grade economics, and trading heuristics are encoded, not dependent on individual traders' experience.
Every netback calculation, differential analysis, and margin estimate is SQL-verifiable against your commercial and market data.
Specialized AI agents that power this workflow.
Commercial Analyst
Specializes in crude economics, netback analysis, differential monitoring, and grade substitution evaluation.
Market Intelligence
Monitors crack spreads, benchmark correlations, seasonal patterns, and market structure changes.
Data Scientist
Handles market data integration, assay databases, historical pattern analysis, and correlation studies.
This is just one of many use cases
Commercial & market intelligence is one example of how Lumina reasons on operational data. Across Oil & Gas, every domain has use cases where AI agents can add value.
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