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Composition Tracking
Relationship of Composition
Tracking to Data Reconciliation








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In general, composition tracking won’t run properly without balanced volume movement data. The question arises: Does Inlibra Composition Tracking require Inlibra Data Reconciliation to be run beforehand or afterwards? The answer varies by industry.

If your industry normally requires a volume balance for the plant, the steps are:
Step 1: Execute Data Reconciliation to perform a volume balance on the plant.
Step 2: Execute Composition Tracking.

If your industry normally performs a mass balance, the steps are:
Step 1: Execute Composition Tracking. This automatically invokes a volume balance algorithm on the feedstock tank farm(s).
Step 2: Execute Data Reconciliation for mass balance. The mass balance is dependent on accurate densities made available after Step 1 (CT).

Mass balances are the only possible accurate balance for operations that create products with densities radically different from the feedstocks. CT provides accurate density on feedstocks for mass balances.

Inlibra CT automatically calculates the composition and quality of mixtures in a set of offsite feedstock receipt and storage facilities (a tank farm) based on starting tank compositions and qualities, the introduction of material of known composition and quality into the tank farm, and a knowledge of total quantities moving within the system or entering/leaving the system. You need a material balance before a meaningful composition tracking can be performed.

Inlibra CT improves the accuracy of predicting and tracking the composition and quality inside a tank farm when these data cannot be explicitly measured.

Inlibra CT performs sequentially. Feedstock receipts are the starting point for tracking, and the composition/quality is calculated as the oil movements propagate through the tank farm. Tanks can be modeled as well mixed, FIFO, or LIFO.

Inlibra CT Model Focus
Figure 1 – Inlibra CT Model Focus


Inlibra calculates the quality of each tank.
Figure 2 - Inlibra calculates the quality of each tank.


Inlibra CT calculates the feedstock composition of each tank.
Figure 3 - Inlibra CT calculates the feedstock composition of each tank.


Inlibra CT calculates the feedstock composition distribution and  quality of the feed stream.
Figure 4 - Inlibra CT calculates the feedstock composition distribution and
quality of the feed stream.

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Functionally, Composition Tracking consists of two steps: data reconciliation and tracking simulation.

The function of data reconciliation is to adjust the feedstock quantity data over a finite time horizon using minimization of the sum of squares of measured values minus reconciled values so that the material balance is achieved. Data reconciliation provides more accurate, reliable and consistent feedstock quantity data for a tank farm than can normally be achieved by direct readings from measurements.

After achieving accurate feedstock quantity data by data reconciliation, the tracking simulation module can use the reconciled movement and inventory data to calculate the composition and quality of feedstock tanks and streams within the tank farm.

Normally in a refinery, the manual calculation of quality and composition in tank farms is inaccurate or mismatched due to:

logo bug  Wrongly specified feedstock oil movement data.

logo bug  Gross errors in gauging measurements or manual inputs.

logo bug  Inaccurate quantity data for feedstock oil movement and tank inventory.

logo bug  Calculation errors in material balance with mass or volume.

logo bug  Inaccurate feedstock composition tracking logic.

Inlibra CT can easily check for these discrepancies and automatically find the most accurate composition and quality data with a state-of-the-art, mathematical tracking technique -- which cannot be achieved by manual calculation.

The Inlibra CT processing steps
Figure 5 - The Inlibra CT processing steps

The first step is to get input data, as shown below, for tracking. The static input data are already configured in the Inlibra CT; the variable data such as feed stock receipts, tank movements and tank inventory are imported from external systems.

Static Data Variable Data
Feedstock Offsite Line Drawing Feedstock Receipt Data
- Feedstock Grades, Start Time, End time
- Tank Assignment
- Movement Rate (optional)
Tank Specification Movement Data
- From Tank, To Tank
- Start Time, End time
- Movement Rate (optional)
Line Fill Size Tank Inventory Data
- 24:00 Net Volume
- Inventory Data for Each Tank
  in Each Time Slice
Feedstock Grades, API

Water Drain Data (optional)
Figure 6 – Input data obtained for composition tracking

Inlibra validates the retrieved data. Inlibra CT performs data reconciliation to generate reconciled values that meet the requirements of the material balance. Inlibra CT’s tracking simulation uses the reconciled values to calculate the compositions and qualities in each tank and stream.

In crude oil refineries, Inlibra CT offers the only reliable means to accurately track actual and expected yields as well as the properties of each cut in the crude distillation unit. It does so by interfacing with external crude assay systems.

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Composition Tracking
   Introduction >
   Relationship of CT to DR >
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Stockpile Tracker
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