Daily production volume (boe/d)
Ridgeline Production Ltd.
Scored from your answers. Not a comparison with other companies.
Your answers show several gaps that an AI tool would inherit from this number.
Connect a forecasting model or an AI assistant to your production data today and it learns from, or answers with, whichever of your four to six systems it is pointed at. Ask it for last week's volume and the field version and the accounting version give two different answers, each stated with the same confidence. You told us your 2025 forecasting pilot spent most of its time cleaning volumes. This is that same problem.
The definition exists. Nothing enforces it between monthly reviews.
You have a written definition and someone who owns it, but field ops and finance each keep their own version, and the only check is the monthly ops review. So when the SCADA historian change broke the meter-to-well mapping, nothing could catch it until the next review, and it ran for a month. The four to ten days before people trust the number is the reconciling happening after the fact.
Pick five wells and pull last month's volume for each from the SCADA historian and from production accounting. Put them side by side.
For any well where the two differ, find out which system the 2025 forecasting pilot was trained on. That tells you which version a model would learn.
List every place the final number lives today and note which one people quote in meetings.
When the field number and the accounting number disagree, which one wins, and is that written down?
Who finds out when a meter is remapped or a new system is connected, and how quickly?
To have one agreed number by day two of the month, which step would we have to stop doing by hand?
This page looks at one number and twelve questions about how it gets made. A Structured Review looks across all five readiness areas (strategy, data, systems, governance and change) with your leadership team in half a day.
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