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 and an enhanced ability to deal with external entities. Further

benefits are anticipated as the systems become more closely integrated into core business processes.

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

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

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.

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 thousands 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.

• Refineries

• 2 Major

• 4 Minor

• 96 Processing Units

• 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

• Materials

• 1800 Crudes, Gases and Products

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

Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 6

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 organizat ional

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

Resolution

(Matrikon)

SIV Volumetric

Database

(IBM

MQSeries)

EAI

Messaging

&

Translation

SINE (SAP)

Business

Warehouse

(IBM

MQSeries)

Business

Spreadsheets

(Ecopetrol)

SIFCA (SAP)

Financials

RIS GCB

Refinery

RIS GRC

Refinery

BDP

Well Prodn

SINOPER

Pipeline

GMS

Gas Mgmt

EAI

Messaging

&

Translation

Web

Visualization

ELLIPSE

(Mincom)

SON Business

Systems

(Ecopetrol)

LITE

Imp/Export

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.

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 processing.

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.

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. I t 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

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

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 accord ing 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.

Oil And Gas Supply Chain Global Competitiveness: A Country in the Balance 12

For more information:

For more information about Production

Intelligence visit our website

www.honeywell.com/ps or contact your

Honeywell account manager.

www.matrikon.com

mpi@matrikon.com

Honeywell Process Solutions

1250 West Sam Houston Parkway South

Houston, TX 77042

Lovelace Road, Southern Industrial Estate

Bracknell, Berkshire, England RG12 8WD

Shanghai City Centre, 100 Junyi Road

Shanghai, China 20051

www.honeywell.com/ps

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

WP 942

July 2011

© 2011 Honeywell Internati onal Inc.