Mathematics in oil industry Solutions for downstream problems Béla Kelemen MOL Group SCM VP Tamás Kenesei MOL Group SCM Modelling&Support Advisor

2

MOL Group - Integrated company

Refinery Petchem unit

Up

stre

am

Do

wn

stre

am

Gas

Mid

stre

am

REGION EBITDA 2012 DATA 2012

► 647 MMboe SPE 2P reserves ► Over 100% organic reserve replacement ratio in 3 years average

► 115mboepd production* ► Production in 7, exploration in 11 countries

► 5 refineries, 470 thbpd

► 19 Mtpa sales

► 1.700+ filling stations

► 2 petrochemical plants

Previous pipeline developments

MMBF UGS

► Gas Storage capacity: 1.9 bcm

► Gas Transmission:

5.560 km pipeline in

Hungary

* Excluding Syria

Total Revenue 2012:

24.6 USD bn

Market Capitalization:

7.5 USD bn

3

MOL group snapshot

Danube Refinery 162 kbbl/d

10,6 NCI

Crude pipeline 848 km

26 Depots 19 own, 7 rented

Product pipeline 1684 km

5038 RTCs

Bratislava Refinery 122 kbbl/d

11,5 NCI

Rijeka Refinery 90 kbbl/d

9,1 NCI

Mantova Refinery 52 kbbl/d

8,4 NCI

Sisak Refinery 44 kbbl/d

6,1 NCI

TVK 1,4 Mt/y

SPC 0,7 Mt/y

Road tank cars 152

More than 1700 stations

Wholesale activity in 13 countries

1991

2007

2009

2005

2003

4

CEE Arena

Rijeka Mantua

Danube

Bratislava

Sisak

Group refinery

Competing refinery

Swechat

Litvinov Kralupy Ingolstadt

Bayernoil

Gdansk

Plock

Burghausen

Bosanski Brod

Novi Sad Pancevo

Porto Marghera

S.M. Trecate

Sannazaro

Cremona

Busalla

Arpechim

Onesti

Petrotel

Petrobrazi

Rompetrol

5

The size matters……

6

Petroleum supply chain

Refining

Crude Supply

Primary Distribution

Product Depots

Secondary Distribution Market

Crude Depots

►Huge number of data is available at every step

►What is relevant?

►What is important?

►How to get it?

7

Enterprise solutions information flow

Co

mm

on

Data

& V

isu

alisati

on

Schedule Adherence

Plan vs. Actual

Operating Envelope

Operator Efficiency

Co

mm

on

Lim

its &

Bo

un

darie

s

Planning

Scheduling

Business Results

Controls

Procedures

Production

Business

Operating Instructions Operations Monitoring Operations

Procedure Analysis Procedure Execution

Execution Decisions Reviews, Reports

weeks ago days ago hours ago now hours ahead days ahead months ahead

* This slide is based on Paul Brice (Honeywell) Holistic Approach presentation,

Process Control

Yield Accounting

8

Model Building - challenges

Special tasks require special models

PLANNING,

OPTIMIZATION

SCHEDULING

UNIT

OPTIMISATION

PROCESS

CONTROL

REPORTING

corporate

level

plant

level

unit

level

process

level

orders

setpoints

performance

data

►This our scope, the ‚virtual’ world

9

How far do we look?

►week ►Year

►Optimization space

►Uncertainty

Periods Inventory Data

More vs Less Connecting points Realibility

Curse of complexity How to map physical possibilities

Consitency

Business

Plan Forecasts Rolling Plan

► Quarterly practice

► Overlook till the end of the actual year for 7 sites

► Group performance evaluation

►Monthly practice

► 4 months 7 sites plan

► Feedstock selection

► Plant optimization

► Transfer optimization

► Product blending

► Inventory management

►Market allocation

► Basis of real serious business decisions

► Yearly practice

► 12 months 7 sites plan

► Feedstock selection

► Annual budget planning

► Target setting for 3 years

Long Term

Plan

► From 3 to 10 years outlook

► Strategic investment planning

► Supply/demand balance

Rolling Plan

weekly update

► Support execution

► 1 months 7 sites plan

► Fixed closing inventory

► Compared to base RP calculation

How far do we look?

11

What is the objective function?

►Profit maximum ►Energy minimum

►Wide range in product yield

►Wide sales demand range

►Wide crude slate

►Sophisticated energy modell is needed

►Product yields

12

Basic financial driver of refinery

GPW (Gross Product Worth) is the

value of products obtained from the

particular crude processed in your

refinery

* Fix and variable costs, losses not included 12

13

Basic financial driver of refinery

Urals 108 USD/bbl

1 tons 788 USD

Crude

Mogas 22% 209

Naphtha 8% 75

Diesel 38% 378

0.1 gasoil 2% 19

HFO 19% 111

Kerosene 2% 20

* Fix and variable costs, losses not included

GPW

Crude price: 788 USD/t GPW: 812 USD/t

Refinery Margin: 24 USD/t

Mogas Kerosene Naphtha Diesel 0.1 gasoil HFO

USD/t 948 1010 938 994 935 584

13

812

14

Shutdown in diesel desulphurisation plant

Urals 108 USD/bbl

1 tons 788 USD

Crude

Mogas 22% 209

Naphtha 8% 75

Diesel 30% 298

0.1 gasoil 10% 93,5

HFO 19% 111

Kerosene 2% 20

* Fix and variable costs, losses not included

GPW

Crude price: 788 USD/t GPW: 806 USD/t

Refinery Margin: 18 USD/t

Mogas Kerosene Naphtha Diesel 0.1 gasoil HFO

USD/t 948 1010 938 994 935 584

14

806

15

No demand on mogas market – sales droop

Urals 108 USD/bbl

1 tons 788 USD

Crude

Mogas 17% 161

Naphtha 8% 75

Diesel 30% 378

0.1 gasoil 10% 19

HFO 19% 111

Kerosene 2% 20

* Fix and variable costs, losses not included

GPW

Crude price: 788 USD/t GPW: 764 USD/t

Refinery Margin: -24 USD/t

Mogas Kerosene Naphtha Diesel 0.1 gasoil HFO

USD/t 948 1010 938 994 935 584

15

764

16

Succesful mogas sales, but lower price

Urals 108 USD/bbl

1 tons 788 USD

Crude

Mogas 17% 161

Naphtha 8% 75

Diesel 38% 378

0.1 gasoil 2% 19

HFO 19% 111

Kerosene 2% 20

* Fix and variable costs, losses not included

GPW

Crude price: 788 USD/t GPW: 809 USD/t

Refinery Margin: 21 USD/t

Mogas Kerosene Naphtha Diesel 0.1 gasoil HFO

USD/t 948 1010 938 994 935 584

900

16

809

Mogas 5% 45

17

Decision points in the refinery

How to operate the

units?

18

Decision points in the refinery

Inland

refinery Multiplant

Seaside

Refinery

►Stable product price (same price of every tons)

►Different crudes are available

►Number of crude is limited

►product prices change by increasing logistic cost

►One market point supplied from more Refinery

►Different Refinery gate prices

Determine the last tons crude which can be processed with profit

Must be focused on

Logistic system

Accuracy of processing

Logistic cost

Harmonization of refineries

Crude

selection

19

Decision points on the market

►Harmonization among different product lines

►Represented transform possibilities between different product lines

►Wide sales range

►Harmonized prices (based on same crude price)

►Price prediction

-300

-200

-100

0

100

200

300

400

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.07

.30

PREM UNL 10PPM FOB ROTT DIESEL 10PPM FOB ROTT

FUEL OIL 1.0 PCT FOB ROTT

How to handle

uncertainty

Vágási pontok

Pannon Egyetem

How deeply detailed is a good model?

21

Dilemmas for model building...

Solvability

Maintenance

Complexity

Reliability

1 100 1

100

1

► Fast

► Complex

► Reliable

► Maintainable

► Rewarding

► Specifiable

► Measurable

Trade-offs to decide Target setting Issues and problems

Market size

Model size

Business Process

Data consistency

Workflow

Calculation Time

End user’s needs

Modelling directives

Should be…

22

From reality to a good modell

Crude assay

expert

Technologist

Modeller

Scheduler Operational

expert

Blending

expert

Who is needed to put it together? Harmonization/standardization

► Set the model granularity

► Set the real flexibilities

► Harmonization of sites

► Group level transfers

► Joint portfolio

► Cross country supplies

"as the complexity of a system increases our ability to make precise and yet significant statements about its behavior diminishes until a threshold is reached beyond which precision and significance (or relevance) become almost mutually exclusive characteristics.„

L. A. Zadeh 1973

Input data (buy, sell, caps, pinv, market structure)

Model Core (refineries)

Demand driven

Structural issues

23

Translating reality into the language of Math

Actual data ORION data

PIMS data

ORION data:

Operative Rolling Plan

PIMS Data:

Actual data:

► Monthly average data

► Annual Refreshed by PE

► Can be Fine tuned temporarily before calculation

► Feasibility check of RP calculation

► Calculated with real yields

► PIMS result checked by ORION data (can be modified!)

► Solution between PIMS and ORION calculation

► Must be executed

► Fine tuned every month

► Can be modified during month

► More operational mode

► Measured every day

► Continuously controlled

24

How does PIMS work?

VALIDATION &

MATRIX GENERATION

DATA

MANAGER MENUS

SOLUTION

REPORTS RECURSION OPTIMIZATION

PIMS LOTUS/EXCEL

Non-Converged

PIMS

Xpress.mp PIMS PIMS

25

Conclusions

Math.. Business processes

To deliver such a modell which can be a bridge between science and business. Main aim is the decision support and the tools

should serve this aim.

Backup

27

SCM Philosophy and Organizational model

Production Downstream Supply and

Sales Retail

Downstream Development

Supply Chain Management

Downstream Downstream

support

Planning & Optimization

Distribution & Scheduling ►How to integrate vertical structures

(and mentalities) to achieve truly lateral SCM behavior to maximize results?

Planning Modelling Performance monitoring

Supply chain Integration

Product Line

Process

28

The magic triangle - from idea to execution

People

Process

Tools

Process ► Horizontal processes, vertical organization

► Planning – Distribution & Scheduling - Execution

Tools ► Technology should serve people – not the other

way around!

► Aspen is the backbone

People ►Well informed , highly knowledgeable and

experienced

► Training professional knowledge, attitude & behavior

Three pillars must be in balance while customers are in focus

3 pillars