The Production accounting application performs reconciliation of the measured raw data and provides accurate data for daily production accounting and performance reporting. It provides reconciled data for daily, weekly and monthly reporting and provides key inputs for fiscal / revenue accounting. It also provides other tangible and none tangible benefits such as loss minimization, Quality giveaway minimization etc.
A typical business process of downstream oil accounting
can be described as follows:
Import of data into production accounting tool
Rigorous and comprehensive oil accounting analysis needs data in-flow from various sources such as process flows from data historian, densities and calorific values from LIMS, inventories from tank gauging system, oil movements logged in manually by field operators or flowing automatically from an OMS system, related information from other solutions such as planning & scheduling, process simulation and rigorous unit models, energy metering systems, business systems (ERP) etc. Preliminary data validation is done to check information for its completeness
Gross Error Detection and Mitigation
Gross errors such as those created due to missing movements (receipts, shipments, tank-to-tank transfers etc.), incorrect mapping of source/destination to an event and automated/manual data entry errors are first detected and mitigated before any further action
Reconcile Plant Information
It is basically a process of minimizing the residual error at the process nodes originating from uncertainties in metered values, volume expansion factors and densities through usage of advanced mathematical error-distribution techniques. The actual plant operational data including production, blending and tank farm movements, product qualities, energy consumption etc. are validated and reconciled in production accounting module to eventually yield “balanced” production statistics before being sent for calculation of Key Performance Indicators (KPIs).
Publish Reconciled Yield data and KPIs
The calculated KPIs based on validated data are monitored against set targets for the day which were received from planning, scheduling and from standard operating targets (refinery data book) provided by unit models. Typical KPIs are set against parameters such as specific energy consumption, gross refinery margin, Unit margins for each process unit, capacity utilization of process units, environment KPIs to name a few.
These consolidated and reconciled KPIs are used across the organization for performance assessment
and decision making.
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