Subsurface Capital Forecaster
AI-assisted price forecasting and capital prioritization for subsurface exploration and development opportunities, combining technical and commercial signals to guide energy investment decisions.
The Problem
“Prioritize subsurface exploration and development capital with AI-driven decision intelligence”
Organizations face these key challenges:
Subsurface and commercial data are stored in disconnected systems
Opportunity ranking relies heavily on expert judgment and manual spreadsheets
Uncertainty is handled inconsistently across teams and assets
Portfolio reviews are too slow to react to market changes
Impact When Solved
The Shift
Human Does
- •Collect subsurface, cost, and market inputs from disconnected sources
- •Review prospects through expert interpretation and spreadsheet-based economics
- •Debate rankings and capital priorities in portfolio review meetings
- •Select funding actions and stage-gate decisions based on deterministic scenarios
Automation
- •No meaningful AI support in the legacy workflow
- •Provide limited spreadsheet calculations for scenario comparisons
- •Generate static charts and committee presentation outputs
Human Does
- •Set portfolio objectives, risk tolerance, and capital allocation constraints
- •Review AI-ranked opportunities and approve funding or deferral decisions
- •Investigate exceptions, low-confidence forecasts, and strategic overrides
AI Handles
- •Unify technical and commercial signals into standardized opportunity assessments
- •Forecast probabilistic value, success likelihood, and downside risk for each opportunity
- •Continuously re-rank opportunities as subsurface, cost, or price assumptions change
- •Generate scenario comparisons, investment summaries, and capital prioritization recommendations
Operating Intelligence
How Subsurface Capital Forecaster runs once it is live
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 funding, deferral, or portfolio reallocation without a portfolio review committee decision [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 Forecaster implementations:
Key Players
Companies actively working on Subsurface Capital Forecaster solutions: