Production Data Integration and Automated Allocation
PPM is chemical divided by fluid. If the fluid number is a quarterly average, the PPM is wrong every day. Prodesy imports production volumes from accounting and SCADA and allocates them to every well and treatment point, so treatment accuracy is calculated on real production.
The allocation problem
Treatment sites rarely map one-to-one to wells. A group line treats twelve wells; a satellite handles three; a single well has two injection points. Prodesy holds the well-to-treatment-site mapping and allocates daily oil, gas and water volumes accordingly, so every injection point has the production it actually treats. When the mapping changes, the history is preserved.
Sources supported
- Production accounting exports (daily or monthly, any standard format)
- SCADA historians and data historians (via telemetry integration)
- Field-estimated volumes from Prodesy Mobile where no metered data exists
- Third-party production databases
Embark’s data integration service handles the mapping and transformation; once configured, imports run on schedule without intervention.
What it unlocks
With production allocated, Prodesy calculates actual PPM, cost per BOE and treatment cost by segment automatically (see the cost per BOE guide). In the Canadian producer case study, integrating production data was the step that exposed 300+ PPM variance and $660,000 a month in cost variance. Variance in a separate program fell from 18% to under 5% once volumes were integrated.
Frequently asked questions
How often is production data imported?
Daily is standard; monthly accounting close can be layered on to true-up estimates.
What if our production data is only monthly?
Prodesy allocates the monthly volume across days and replaces it with metered data where available; PPM is calculated on the best data available per point.
Do we need to change our accounting system?
No. Prodesy consumes exports or API feeds from the existing system.
See your chemical program in Prodesy
A 30-minute online demo using your injection points, vendors and lab data. You leave knowing where variance and cost are hiding.
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