Build sub-surface development scenarios
How build sub-surface development scenarios are reshaped as AGI capability advances.
The bottom line
Roughly 85% of the work in Build sub-surface development scenarios is information-shaped — already within reach of AI delivery. The question here is not whether it shifts, but which tasks go first and who staffs the residual.
Why: With no seeded child occupations, the scalar is derived from the process name and its industry anchor in upstream petroleum. 'Building sub-surface development scenarios' refers to reservoir modeling, geoscientific data analysis, and simulation—highly computer-based knowledge work that operates entirely in the digital realm before any physical drilling occurs.
grounded in the economy graph · digital scalar 0.85 · digital
Business-as-Code
Read as an executable program — the work decomposed into Code, Generative, Agentic, and Human.
Build sub-surface development scenarios sits inside a larger value-flow — 1 parent structure it composes into. The hierarchy is grounding, not the story: it tells you which aggregate exposure Build sub-surface development scenarios inherits.
The problems this exposes
Node-intrinsic problems read straight off the graph (exposesProblem) — the evergreen wedges a builder could take into this space.
Where Build sub-surface development scenarios sits
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How the work flows
Trigger: Approval of a characterized geological model for a newly discovered or appraised reservoir initiates scenario building.
- Ingest geological and reservoir characterization models
- Define reservoir depletion and recovery strategies
- Design well trajectories and subsurface completion parameters
- Simulate fluid flow and generate production forecasts
- Estimate capital and operational costs for each scenario
- Evaluate scenarios against economic constraints and risk factors
Outcome: Multiple viable sub-surface development scenarios with associated production forecasts and economic models are ready for final selection.