Results & Segmentation

Key findings

• ranking metrics
  • value: npv_mm.
  • scale: reduction_potential_kt and total emissions.
  • risk: regulatory_risk_score.
  • speed: payback_years.
  • internal composites:
    • benefit_score and investment_score used for sensitivity and ordering, with raw fields still visible.
• headline pattern
  • confirms the high benefit zone described in the Problem Framing page.
  • operators with both high intensity and meaningful scale tend to have the strongest combined value and reduction potential.
  • low intensity operators exist at both small and large scales; efficiency is not fixed by size.
  • results align with known benchmark ranges for different facility and asset types.
• intensity and scale
  • intensity spread:
    • lowest operators well below typical benchmark bands.
    • highest operators above 100 kg CO2e per BOE.
  • scale vs intensity:
    • large clean operators and large high intensity operators both exist.
    • quadrants:
      • large and high intensity: largest decarbonization opportunity.
      • large and low intensity: benchmark group.
      • small and high intensity: quick wins, smaller absolute impact.
      • small and low intensity: lowest priority.

Segments and clusters

• segments
  • intensity bands:
    • low, medium, high, very high bands defined on kg CO2e per BOE.
  • scale bands:
    • small, medium, large, major bands defined on annual emissions.
  • archetypes:
    • thermal heavy high intensity.
    • large conventional mid intensity.
    • small but intense.
    • large and efficient.
  • each archetype has:
    • typical intensity band.
    • typical emissions scale.
    • characteristic emission mix (for example processing heavy vs vent heavy).
• cluster outputs
  • each operator assigned to a cluster_id and cluster_label.
  • cluster level stats:
    • average intensity.
    • total emissions.
    • share from venting and flaring.
    • indicative financial metrics.
  • cluster ranking:
    • clusters with high intensity and large vent or flare share rank highest for decarbonization opportunity.
  • emissions decomposition:
    • breakdown by component shows whether an operator is driven by thermal energy use, gas handling, or leak-like behavior.

Risk and scenarios

• baseline and scenarios
  • baseline ranking uses current policy path.
  • alternative scenarios adjust carbon prices and regulatory pressure.
• scenario signals
  • robust targets:
    • minimal rank change across scenarios.
  • price sensitive targets:
    • large moves between baseline and higher price scenario.
  • regulatory sensitive targets:
    • large moves under a high compliance pressure case.
• risk adjustment
  • scores can be adjusted down for:
    • lower data quality.
    • higher model uncertainty.
    • high operational concentration.
  • tail flags mark:
    • top intensity outliers.
    • top emissions outliers.
    • combined cases that may face extra scrutiny.