Subsurface Capital Intelligence
AI decision-support and enterprise knowledge search for oil and gas extraction optimization, combining subsurface technical data, commercial context, and internal documents to improve capital allocation speed and quality.
The Problem
“Subsurface Capital IQ for faster, higher-quality upstream capital allocation”
Organizations face these key challenges:
Subsurface, production, and commercial data are stored in disconnected systems
Capital decisions rely on manual spreadsheet consolidation and expert interpretation
Internal technical documents are difficult to search semantically
Prior project learnings are not systematically reused
Impact When Solved
The Shift
Human Does
- •Gather subsurface, production, cost, and price inputs from disconnected sources
- •Reconcile assumptions and build opportunity comparisons in spreadsheets and slide decks
- •Search prior reports, reviews, and presentations for relevant historical evidence
- •Review technical and economic tradeoffs and decide which opportunities to advance
Automation
- •Provide basic keyword search across stored documents
- •Return static reports and dashboards from existing systems
- •Support limited rule-based calculations in spreadsheets
Human Does
- •Set screening criteria, risk tolerances, and portfolio priorities
- •Review AI-ranked opportunities and challenge assumptions where needed
- •Approve capital recommendations and scenario choices for advancement
AI Handles
- •Unify technical, production, commercial, and document evidence into opportunity views
- •Answer natural-language questions with source-linked citations and comparable cases
- •Estimate production, decline, cost, and economic outcomes for candidate opportunities
- •Rank opportunities, generate scenario comparisons, and flag assumption changes or risks
Operating Intelligence
How it works
AI runs the first three steps autonomously.
Humans own every decision.
The system gets smarter each cycle.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Assemble Context
Step 2
Analyze
Step 3
Recommend
Step 4
Human Decision
Step 5
Execute
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.
The Loop
6 steps
Assemble Context
Combine the relevant records, signals, and constraints.
Analyze
Evaluate options, risk, and likely outcomes.
Recommend
Present a ranked recommendation with supporting rationale.
Human Decision
A human accepts, edits, or rejects the recommendation.
Authority gates · 1
The system must not approve drilling, workover, or development capital without asset manager or capital committee judgment. [S1]
Why this step is human
The decision carries real-world consequences that require professional judgment and accountability.
Execute
Carry out the approved action in the operating workflow.
Feedback
Outcome data improves future recommendations.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in Subsurface Capital Intelligence implementations:
Key Players
Companies actively working on Subsurface Capital Intelligence solutions:
Real-World Use Cases
AI-assisted subsurface capital allocation decision support
This workflow uses AI to combine underground technical data with business data so energy teams can decide faster where to invest.
AI-enabled subsurface capital allocation decision support
An AI workflow that mixes underground technical data with commercial data to help energy companies decide where to invest money faster and more accurately.
Machine-learning environment provisioning for energy forecasting and planning experiments
Romande Energie can quickly spin up safe copies of its data so teams can test new machine learning ideas without breaking live systems or paying to duplicate data.