Sigmafine Providing Reconciled Data to the Business

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 2 The Data Fog Need for better information and faster access –Flood of data Poor data quality - loss of confidence in reported results –Data does not balance –Manipulation by different groups Direct financial impact –Custody transfer errors go undetected –Plant operation is sub-optimal ? Info Data Fog

Measurement Error  Total   Gross   Bias   Random All measurement has error

Typical Meter Errors TypeError range Orifice0.9 – 20% Turbine0.5 – 10% Ultrasonic0.5 – 20% Mass %

Typical Inventory Measurement Errors 1.Movement (diaphraming) of the Tank Bottom 2.Incrustation of the Tank Shell with Waxy or Viscous Oils 3.Change in the Weight of the Floating Roof 4.Inadequate Settling Time after an Oil Transfer 5.Tank Calibration (Strapping Table) Accuracy 6.Errors in Determining the Average Oil Temperature 7.Thermal Expansion of Manual Gauging Tapes 8.Thermal Expansion of the Tank Diameter 9.Vertical Movement of the Reference Gauge Point or the Gauging Well Caused by Temperature Variation 10.Vertical Movement of the Reference Gauge Point or the Gauging Well Caused by Tank Filling 11.Vertical Movement of the Bottom Datum Plate Well Caused by Tank Filling 12.Calibration Accuracy of Manual Gauging Tapes 13.Inherent Accuracy of the Automatic Tank Gauge 14.Hydrostatic Tank Gauge Pressure Transmitter Accuracy 15.Density Stratification in Tanks using Hydrostatic Tank Gauges 16.Non-representative Samples 17.Faulty Laboratory Analysis of Tank Samples 18.Human Error in Gauging Procedures 19.Misreading Gauging Tapes 20.Gauging Tape Transcription Errors

So Is Your Data Credible?

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 7 Lifting the Data Fog - Sigmafine Global balance across the whole complex Validated data for ERP Agreement on the reconciled and balanced data Detect measurement problems Info Data

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 8 Sigmafine In use since 1994 –In use at over 200 sites world wide – oil, chemicals, metals & mining and refining, gas production, water utilities Tool for Production Accounting and Engineering Applications Data Unification and Validation Tool Measurement Audit Tool Plug In for Analysis Framework

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 9 Sigmafine Balance Gross Error Detection Weighted Least Squares Data Reconciliation –Redundant measurements –Measurement accuracy –Calculates “soft sensors” accurately –Minimization of total error

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 10 Reconciliation – What is it? Uncertainty := (Bias 2 + Precision 2 ) 0.5

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 11 The Reconciliation Process

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 12 Customer Benefits Monitor and reduce meter maintenance Measurement stewardship Verify custody transfer Monitor plant performance Identify operations problems Loss identification and tracking Plan versus reconciled comparison

May Jul Sep Nov Jan Mar May Jul % Bad Meters Reduce Meter Maintenance

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 14 Measurement Stewardship Bias Meter Error Drift

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved Day of the Month Daily “profit/loss” in $ over one month Bias $/day Verify Custody Transfer

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 16 Monitor Plant Performance Running Plan KPIs current/shift/running plan reconciled vs. theoretical yields

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 17 Identify Operational Problems 14,000 bbl/month product loss identified Purchased feed stream purity significantly lower Track and quantify slops Savings over 10 cents/bbl ($4 million)

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 18 Reduce Losses “We used to close the Metallurgical Mass Balance once a month. We have integrated the PI Systems at the Concentrator, Smelter, Oxide Plants and Refinery with Sigmafine. We close the division balance once a week. The 4 Plant managers are informed daily of the metallurgical accounting. We implemented a real time gross error detection and reduced metal losses in tails and slags...” Leonel Mundaca CODELCO NORTE OSIsoft Users Conference San Francisco May 13, 2004

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 19 Reconciled vs. theoretical yields Reconciled Yields Theoretical Yields Production Plan

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 20 Model DMAs Leak detection Monitor and reduce meter maintenance Hard Facts –Water loss of 10% considered good –Best 5% to worst 78% Sigmafine in Water Example

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 21 balance area Using Sigmafine

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 22 Build up your balances from small local zones through district to division and company wide balances or vice versa Everyone can access a standard updated network and can alter their own local copy for test runs, feasibility studies, investment decisions etc

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 23 IWWA Water Balance

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 24 Amount of Leakage

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 25 DMA in Sigmafine

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 26 Analyzing DMA with Sigmafine

Copyright © 2007 OSIsoft, Inc. Company Confidential. All rights reserved. 27 Viewing Results in ProcessBook

Sigmafine Providing Reconciled Data to the Business