Expert insights on data strategy
A tag census found roughly 70% of SCADA tags belong to facilities, not wells. If you scope and price per well, you have costed a third of the job.
LLM extraction pipelines fail quietly, not loudly. Here's how to catch AI pipeline drift with ground truth sets, regression suites, and distribution monitoring.
Emissions reporting gets treated as a spreadsheet task. It's a data engineering problem: flare data, allocation, and an equipment inventory nobody cleaned.
Most operators have well data. Very few have a well data product. The difference is owners, consumers, freshness SLOs, and a contract, not a platform.
"Digital twin" covers everything from a well record to a physics simulation. Here's an honest four-level spectrum and where a mid-size operator should stop.
Moving fast has real value, especially in upstream. But there's a predictable inflection point where the systems built for speed become the thing slowing you down. The earlier you build with handoff in mind, the cheaper the inflection is. Here's what 'built for handoff' actually means and how AI-assisted development changes the calculus.
Most SCADA ingestion programs fail because they try to boil the ocean. A phased approach that proves a repeatable pattern on the cleanest asset first is almost always faster end-to-end. Here's a realistic sequencing guide for someone who has been told they own SCADA ingestion and is trying to figure out where to start.
Every acquisition comes with somebody else's SCADA stack. After enough deals you have eight to twelve platforms, no common namespace, and a field team that lives in browser tabs. The real cost isn't licensing, it's the analytics you can't run and the integrations you keep rebuilding. Here's why and what to do about it without replacing the SCADA vendors.
Autonomous systems in oil and gas only deliver their full value when they're built on clean, standardized data. Operators treating data standardization as a core competitive capability, not an afterthought, get measurably better results from automated drilling, predictive maintenance, and remote field operations.
Every PPDM project eventually asks which database to build on. The answer is mostly driven by practical constraints, not religious preference. Here's the decision framework: when SQL Server is the right call, when PostgreSQL makes more sense, and where DuckDB fits in the stack.
Most mid-size operators don't have a dedicated data team and don't have the budget to build one. That doesn't mean governance has to wait. Here's the minimum viable version: five domains, five owners, five pages, and the discipline to keep them current.
Land and production almost never agree on the first try, and the reconciliation eats more analyst time than any other problem in upstream data. Here's why it's genuinely hard, where the disagreements come from, and how to actually solve it instead of papering over it every month.