Oil And Gas Supply Chain Global Competitiveness: A Country In The Balance

Transcription

1 Oil And Gas Supply Chain Global Competitiveness: A Country In The Balance Abstract Ecopetrol S.A., the state oil company of Colombia and fourth largest oil company in Latin America, undertook a major initiative to enhance its competitiveness in international markets. This initiative involved a major rework of its business and financial systems to take advantage of best practices in the industry. One of the key strategies was to put in place a Volumetric system to be the single source of validated volumetric information across the entire supply chain. The steps taken by Ecopetrol have already improved its knowledge of the state of the business, enabled tighter control of purchases, more effective optimization of inventories an d an enhanced ability to deal with external entities. Further benefits are anticipated as the systems become more closely integrated into core business processes.

2 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 2 Table of Contents Abstract...1 Business Environment...4 Challenges...4 The Project...5 Architecture...5 Data Quality...6 Consolidation...7 Data Consolidation Consistent References and Terminology...7 Balancing...8 Property Estimation...8 Conciliation...8 Tracking...8 Ownership Over/Under...9 Data Reconciliation...9 Integration with Financial...10 Summary...10 Project Lessons...11

3 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 3 Table of Figures Figure 1 Sensor Project Details...4 Figure 2 Data Challenges...5 Figure 3 System Architecture...6 Figure 4 Operational Facilities...7 Figure 5 Tracking...9

4 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 4 Business Environment Ecopetrol S.A. is the principal petroleum company of Colombia and the fourth largest in Latin America. It was founded in 1951 as a state owned corporation, but in 2003 it become a publicly held company, still 100% state owned, but managed as an independent corporation. This change released Ecopetrol from the responsibility of managing the oil reserves. ANH (National Hydrocarbons Agency) is now responsible for this function. With its new found autonomy, Ecopetrol accelerated its exploration activities and undertook several initiatives to increase its competitiveness in world markets. One of these initiatives was the SENSOR project. SENSOR s objectives were to improve the management of the business by ensuring decisions were based on a single, reliable, ti mely and complete set of information. Its scope covered financial and operational data from exploration through transportation, re fining, and distribution. It was the largest ERP implementation and integration project ever in Colombia. Crude and Gas Production 12,000 wells 250 fields 260 Facilities Transportation 56 Pipeline Systems 116 Line Segments 70 Custody Transfer Points 129 Stations 16 Trucking Lines Tanks and Pools 630 Product Tanks 315 Crude Tanks 934 Product Pools Refineries Materials 2 Major Minor Crudes, 96 Gases and Processing Products Units Figure 1 Sensor Project Details Challenges Data in the supply chain are a combination of instrument measurements, laboratory measurements, material transactions, inventories, ownership transactions and events. These data are measured and reported separately from tho usands of locations but together they provide a coordinated picture of the business transactions and material positions. Inaccuracies, inconsistencies or incompleteness of any of these components can cause significant data damage, impacting the ability to assess operations and subsequently impacting the confidence and credibility of numbers in the financial systems. Procedures put in place to mitigate this data damage result i n a lot of tedious manual work that slows down the financial feedback cycle. One of Ecopetrol s major concerns was with identification of losses in the supply chain. These losses were because of a variety o f reasons, several of which were related to terrorist activity in the country, but these losses could run up to 6% of production. Ecopetrol operated as a wholesaler allowing its pipelines to be used by many partners. As a result, knowledge of what material was in the supply chain, who owned it, and the quality, quantity and value of the material, was key to running the business.

5 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 5 The Project The SENSOR project went out to bid with an ambitious scope: Implement an Integrated Financial Accounting and Support Solution (SIFCA), a Business Intelligence Solution (SINE), and a Volumetric Information Solution (SIV); integrated amongst themselves and with the business operations systems of ECOPETROL (SON), through an Application Integration Architecture (EAI). Additional declared objectives were: Implement industry best practices Ensure consistency of data and integrity of information Review business processes, identify organizational barriers, redefine roles and responsibilities Review and analyze planning cycle processes This project was to run in parallel with various other initiatives within Ecopetrol to improve business systems feeding key production information. Figure 2 Data Challenges Architecture The major components of the project were SIFCA Financial Accounting SINE Business Intelligence SIV Volumetric Data System EAI Messaging Integration SEGA Security Applications Change Management

6 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 6 SON Business Systems (Ecopetrol) BDP Well Prodn RIS GCB Refinery SINOPER Pipeline RIS GRC Refinery GMS Gas Mgmt EAI Messaging & Translation Business Spreadsheets (Ecopetrol) SIV Volumetric Database Resolution (Matrikon) Web Visualization EAI Messaging & Translation SIFCA (SAP) Financials SINE (SAP) Business Warehouse ELLIPSE (Mincom) LITE Imp/Export (IBM MQSeries) (IBM MQSeries) Figure 3 System Architecture At the core was the SIV volumetric system. Its responsibilities were to be the single source of all volumetric information for Ecopetrol. In addition, its mandate was to: Be an integrated solution that will allow consolidation, reconciliation, balancing and tracking of volumetric information, identifying the best industry practices in these processes. To deliver quality volumetric information for closing Ecopetrol financial balances to SIFCA (ERP) To deliver quality volumetric information for the evaluation of performance indicators in SINE (BI) To reduce project risk, standard products were selected for all components, including the volumetric system. Data Quality One of the key objectives of the project was to improve data quality. The strategy for doing this revolved around the SIV vol umetric system. The SIV system had the ability to receive information from all of the Ecopetrol business systems and spreadsheets and store it in a single repository database. Once in this repository, data could be analyzed across business systems and across organizational boundaries using a set of data quality tools. Feedback could be sent to the source systems, when required, to correct the raw values. Once a set of information had been consolidated and verified, it could then be mapped to financial cost centers and codes and transmitted directly to the financial system. The data quality toolset employed was very extensive and involved: consolidation: aggregation and consolidation of information balancing: generation of mass, volume and energy(gas) balances property estimation: providing estimates of qualities where not available conciliation: negotiated or rule based agreement of values at organizational boundaries. reconciliation: statistical identification of measurement and metering problems tracking: prediction of batch qualities and compositions ownership: tracking of actual and over/under material ownerships

7 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 7 One of the major benefits of this approach was that data quality could be enhanced without requiring operational changes or a dditional investment in metering. The project did uncover some major deficiencies; some of these were corrected but others were left to be managed or estimated by the system. Consolidation The SIV volumetric system received approximately 30,000 messages per day in XML from the SON business systems covering: production: actual and planned inventories: tank, facility, pipeline, station qualities: crudes, gases, products ownership: crudes, gases, products royalties reserves truck, ship, pipeline movements It received automated management of change messages. Examples include: new products new units, tanks, areas name changes from the SIFCA financial system purchase orders cost centers product catalog changes It is important to note that any changes in values submitted from the source systems were tracked in audit history logs in the volumetric database. Figure 4 Operational Facilities Data Consolidation Consistent references and terminology Data from each system are carefully characterized so they can be combined and aggregated appropriately into the total volu metric knowledge base. Characterization is important. Without exact knowledge of the origin, timing, applicability, units of measure and change history of a value its usage in further calculations or aggregations could be in error.

8 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 8 For example, to compare the planned quantity of low sulfur crude oil in MMBLS that must be transferred from a terminal in a month to the actual quantity of various crudes in BLS shipped daily from various tanks at the terminal requires several levels of proc essing. Transactions at the tank level need to be aggregated to the terminal. Transactions at the individual crude level need to be aggregated to crude categories, and daily transactions need to be summed for the month converting the units of measure. This can only be done if every data value is completely understood. The volumetric system included geographic, organizational, and operational hierarchies in order to be able to perform the agg regations in all dimensions required. It included full units of measure conversion and understood handling of data from multiple time periods and time zones. It also included a complete representation of the product hierarchy to enable roll -ups of materials into summary categories. Balancing Balancing was used as the first data quality filter. Exception reports by business area or pipeline system could quickly identify all nodes with balance problems. Additional drill-down could then be done to look at reported movements, inventories or qualities. These balances could be done in volume, mass or energy (for gas). Property Estimation It is important to note that the volumetric system had to live with the realities of data as provided and make the best of it. This means that if a movement or inventory was not provided with appropriate quality information the system had to be able to obtain a best estimate. This was especially important for material gravities used for mass balancing. So for example the gravity of a material movement could come from: an analysis of the material being moved (lab analysis) an analysis of the material at the source (lab analysis on the tank) a blended gravity from the gravities of the batches in the movement a blended gravity derived from the assay gravities for components in the material composition calculated for the movement by tracking an assay gravity estimate for the specified movement commodity This property estimation precedence methodology was implemented in the volumetric database and was available for use on all streams and by all reporting, balancing or other analysis tools. Conciliation Collection of data from many business systems meant that there were many locations where effectively two sets of values existed for the same material transaction. The two values were independently measured by the two different organizations. One technique to resolve differences involved the application of some business rules, from a simple directive to always use one value to a calculated intermediate position evaluated considering relative accuracies of metering techniques. Any conciliation adjustments made were tracked over time to identify inherent biases in the measurements.

9 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 9 Tracking A batch tracking analysis was executed on the provided information to calculate quantities qualities compositions ownership at every location, for every material movement and continuously over time. This analysis followed material along the supply chain from inventory locations through transportation systems to distribution. At each location compositions, physical qualities and quantities were calculated for comparison to measured qualities and quantities. The analysis used a batch concept but did not require formal declaration of batches from the supplying data systems. However, where formal batches were available it would use them. Figure 5 Tracking The results were significant, providing predictions of qualities and quantities at any time and for any location in the supply chain. It determines the mix of crudes in feed tanks to the refinery. It determined composition of sales gas. It could predict blended physical properties such as crude sulfur or gasoline octane. Material with more accurate quality specifications is more valuable

10 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 10 Ownership Over/Under Ecopetrol has to manage many relationships with partners and the government. The material ownership transactions that occur in the supply chain were quite complex but needed to be modeled so that the predicted results would be of sufficient quality to be usable. The tracking tools followed the material and accounted for: blending of ownership automatic purchase transactions borrowing of material repayment of material debit and credit balances when overages or shortages occur royalty transactions The result was good predictions of ownership of material at all points in the supply chain, (including calculation of ownership of loss and imbalance flows). It enabled Ecopetrol to more effectively interact with partners and the government. Data Reconciliation Data reconciliation was the last of the data quality tools. It read the repository database to derive its material balance model equations and obtain its measurement data, then applied statistical methods to generate a complete and consistent mass balances across the entire supply chain flowsheet. Every measurement of inventory and flow was adjusted, subject to applied constraints, to produce a completely balanced result. The adjustments to each specific measurement that had to be made to get a balance were compared to their accuracy tolerance. This relative measure showed which values were statistically in error and needed to be looked at. Data Reconciliation could pinpoint specific measurements in error, provide estimates for unknown flows and provide accuracy s tatistics on measurements and balances. Integration with Financial The financial model of a business does not necessarily match the physical model. Information has to be transformed for transmission. The volumetric system was responsible for managing these transformations since it understood the operational world and also was configured with all of the financial cost centers, warehouses and statistic codes so that it could map the operational information into appropriate financial buckets. Other challenges were discovered once information began to flow to Financial. It became obvious that data to the financial system had to be sent completely balanced. The operational perspective of within a few percent did not translate well to the financial world. Transactions had to be sent to financial in a chronological and supply chain order to prevent even temporary negative invento ry situations in the financial accounts. Also, repetitive submission of values to financial would get interpreted as incremental additions to an account not as replacement values. Summary Competitiveness of any manufacturing business involves the need to effectively manage the raw material supply; the ability to optimize processing of the raw materials to produce high quality products and the capability to efficiently distribute the products minimizing costs along the way. When the business is in Oil and Gas and involves exploration, transportation, refining and distribution for an entire country the challenges become quite large, but the basic strategy still applies. In order to improve any business, you have to be able to measure where you are and be able to monito r key factors that influence your performance. The faster you can make these evaluations the faster you can make corrections and the better you can maintain an optimum path. What this means is a that any program to improve competitiveness must involve

11 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 11 ensuring access to reliable, timely and complete information on all aspects of the business providing the tools for rapid analysis and reporting automated delivery to financials The project as a whole has resulted in detection of opportunities to improve the recording and quality of information in the operation of the businesses better control and improved value of inventories better knowledge of the business greater control of product purchases improved control of royalties information verification for business partners Project Lessons Step one is to clearly understand the entire business process and its information flows, not to begin from a list of requirem ents. With a large project across many business areas, segregating the project teams according to functional areas can be a mistake. It is important that there be a clear understanding of how information is going to be used across the organization, not just wha t information has to be provided from one functional group to another. Most problems in integration resulted from differences in interpretation of the information not in the transmission. Do not work from a list of requirements but from a detailed description of the required business process. Ensure all project teams understand the entire process. Understand the expected results from the process. Clearly define a set of data for exhaustive integration testing, in addition to the test procedures. Define clear roles to ensure the integrity of information between solutions. Build solutions with a team of consultants and functional employees of the company working together as business partners where everyone contributes with complete knowledge of the process.

12 Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 12 Maria Victoria Riaño Salgar Project Manager, Ecopetrol Andrew Nelson Resolution Product Manager, Matrikon Presented at the National Petrochemical & Refiners Association Q&A and Technology Forum Phoenix, Arizona October 8 to 11, 2006 For more information: For more information about Production Intelligence visit our website or contact your Honeywell account manager. mpi@matrikon.com Honeywell Process Solutions 1250 West Sam Houston Parkway South Houston, TX Lovelace Road, Southern Industrial Estate Bracknell, Berkshire, England RG12 8WD Shanghai City Centre, 100 Junyi Road Shanghai, China WP 942 July Honeywell Internati onal Inc.