The Reserves Trap in Diligence: Why "AI" Type Curves Inflate the EUR You're Buying
When a private-equity fund or a capital partner buys an oil and gas asset, what they're really buying is a number: the estimated
When a private-equity fund or a capital partner buys an oil and gas asset, what they're really buying is a number: the estimated
Ask a room of non-engineers what determines how much oil a field will produce and they'll say something about the size of the
There is a specific, well-documented way to make an oil or gas well look more valuable than it is, and it hides inside one innocent-looking
"Petroleum engineer" is one job title covering sub-disciplines that share a hallway and almost nothing else about their day. This is the one
Reservoir engineering forecasts the asset. Reservoir simulation builds the physics model the forecast is argued against. They sound like the same job — outsiders, and plenty
Decline-curve analysis is the load-bearing first step of almost every reserves number. We rebuilt the hard part to run entirely in the browser — matching Equinor's open-source math to 0.02 ppm, with no server and no data upload.
Three modules, sharing a Postgres backbone: ingestion, model/forecast, reporting+audit. Buildable in 4-8 weeks on $40-80/month infrastructure. The open-source replacement for the enterprise reserves stack at the bottom of the market.
Two recent reference architectures from the published literature: Equinor's Johan Sverdrup digital twin and SLB+ONGC's 2025 agentic AI framework for large-scale well modeling. Both describe the same architectural pattern.
Small E&P operators and family offices are running 2026 capital on 1990s workflows. The 2024-26 reservoir engineering literature has converged on the diagnosis: the gap is in workflow infrastructure, not algorithms.
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