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Risk management on a large topsides design project

Peter Astley

About myself

� Retired after 28 years cost engineering & project management with

Amec

� Six platform design projects, three refinery projects

� Currently short course lecturing for Cranfield University

� Active FIMechE, FACostE

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Purpose

� Explain how I have used risk management on large topsides design projects

� Discuss what lessons I have learned

� Stimulate future process improvement

Britannia platform

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P20

P50

P80

not to exceed cost

pro

babili

ty

final cost (1998)

Sanction estimate (1994)

variance decreases as risks are resolved

Britannia cost risk history

ICEC ICEC RoitterdamRoitterdam 19981998

Britannia topsides risk drivers

� Alliance working

� Cost

� Schedule

� Weight

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Lessons learned

� Risk management is an essential cost control tool

� Use of different probability levels:

� stretched targets 20%

� budgets 50%

� corporate reporting 80%

� contingency management

� Risk management increases buy-in from project participants

� It is valid to change quantitative results to match intuitive

expectations

Amec´s adoption of risk management

� Focus on qualitative risk management process

� Risk matrix and risk register

� Company-wide training programme

� Facilitated brainstorming sessions

� Required for tenders and in-house project reporting

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Amec´s risk driver

� Low margins/high risks in UK civil/construction contracting

� December 2007 Amec joined FTSE 100

� Oil & gas equipment & services sector

� Vision: to be the leading supplier of high-value consultancy,

engineering and project management services to the world’s

natural resources, nuclear, clean energy, water and environmental

sectors.

1010

Identify Identify

objectivesobjectives

DefineDefine

rolesroles

andand

responsibilitiesresponsibilities

Identify Identify

risksrisks

Assess Assess

and rankand rank

Plan Plan

responseresponse ExecuteExecute

Monitor Monitor

and and

explainexplain

Management of any Management of any uncertainuncertain event that might event that might affectaffect

thethe achievement achievement of our of our objectivesobjectives

Risk management process

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Sakhalin development facilities

Different islands

5050°° NN

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SEIC milestones

1991 Consortium formed of Marathon. McDermott, Mitsui, RF

1994 Production sharing agreement signed

1999 PA-A (Molitpak) installed

2000 Marathon traded its share with Shell

2001 Amec started design

2005 Environmental issues force sale of 50% share to Gazprom

2006 Lun-A (Lunskoye) installed

2007 Piltun drilling operational

2009 First LNG delivered

Risk drivers (revised)

� Arctic conditions

� winterisation

� safety

� wave height

� weather window

� Earthquake zone

� structural design

� pendulum bearings

� Project size

� resources

� management

� Schedule expectations

� rework

� Gas sales price

� Russian influence

� TEOC

� Russian content

� production sharing

agreement

� Change control

� client change

� conceptual design

� steel to concrete jacket

� Korean fabricator

� no topsides experience

� design support resources

� design construction overlap

� culture & communication

� Environmental protection

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Amec bid/execution strategy

� Select team known to Marathon & Shell

� Subcontract Jacket design to TriOcean

� Subcontract Quarters design to Rubin ( St Petersburg)

� Use existing Amec Environmental consultant in Moscow

2007

DEFINITION ENGINEERING

PSTS, TEOC

20052002 2003 2004 2006

DETAILED DESIGN &

PROCUREMENT

2001

1ST OIL PRODUCED

1ST GAS TO EXPORT

DECK INSTALLATION MATING &

HOOK-UP

TOPSIDES

FABRICATION/LOADOUT

Sakhalin early high level schedule

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Lunskoye transportation

Lunskoye installed winter 2007

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1010

Piltun February 2009

Sakhalin production capacity

Production capacity cu m/day

Gas Cond Oil

PA-A 1.7 m 14 000

PA-B 2.6 m 11 000

Lun-A 50 m 7 900 2 500

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Qualitative risk score table

Probability

Score

(P)

Impact

Score (I) Design Cost Schedule

A Not very likely

0-20%

1 Accommodate

with no

significant effect

<£50,000 <2 weeks

B Unlikely

21-40%

2 Minor

consequential

effects

<£500,000 <1 month

C 50/50

41-60%

3 Multi-discipline

change/

rework

<£1

million

<3 month

D Likely

61-80%

4 Major abortive

work

<£2

million

<6 month

E Highly likely

81-100%

5 Major design

change

<£5

million

<6 month

Risk matrix

55 2626 66 11

27,27,

2828

18, 18,

1919

22 2222 2121 2020

23237724,24,

2525

161619, 19,

1515

1010 12,12,

1313

331111 99

3030 44 1717 2929 88E E

D D

CC

BB

A A

1 2 3 4 51 2 3 4 5

ProbabilityProbability

PP

Impact IImpact I

1717 Risk registerRisk register

numbernumber

Do not multiply P x I

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Risk drivers (used)

DD Detail design change

FC Fabrication contractor

FE FEED carry over

FU Functional change

GS Gravity base structure (GBS)

HU Hook up & commissioning

IS Instrument control & safety system

IC Installation contractor

LC Local content/approval

OM Load out/transportation grillage

OT Operations/maintenance

PR Other parties (not GBS)

SC Schedule risk

WI Winterisation

WT Weight engineering

Mitigation strategies

T Transfer

A Accept

M Mitigate

C Use contingency

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Simple risk register

Risk

No.

Risk

Driver

Risk Statement Mit.

Strat

Prob Impact Action

by

17 KF If vendor data from

fabricator is late then there

will be delays to design

schedule which will

subsequently affect

fabrication

C 5 3 SR

Risk categories

� Technical risks & design assumptions

� Cost/price/profit, finance/cash flow

� Contractual risks (form of contract, liabilities)

� Schedule

� HSE

� Legislation

� Reputation

� Stakeholders

� Interfaces

� Supply chain

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Risk management levels

00 PP 100100 MinMin MaxMaxMostMost

LikelyLikely

00 100100

PPAA--EE

II11--55

RR

Level 1 (Qualitative) Level 1 (Qualitative) Risk register Risk register

Level 2 (Quantitative) Level 2 (Quantitative) Monte Carlo AnalysisMonte Carlo Analysis

ICEC Ljubljana 2006ICEC Ljubljana 2006

Quantitative risk forecasting

� Base line forecast

� Select from risk register all risks with impact > 3

� Interview lead engineers ( 12 disciplines) . What uncertainties will

affect your forecast to complete?

� What is the probability of occurrence (including P=1)?

� What is the best case, worst case, most likely?

� Run Monte Carlo analysis

� Discuss results and rerun

� Check against resources and planned completion date.

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Lessons learned

+

� Involve the project team

� Consider all high impact risks

� Asking the 3 point question

� Cost engineering tool

� Use for contingency management

� Use stretched targets

∆

� Consistency across project WBS

� Improve cost driver identification

� Better risk correlation

� Better estimation of probability

� Consider systemic risk

� Opportunity management

� Don´t use risk as an excuse

Risk management, art or science?

People

Communication

Persuasion

Facilitation

Logic

Data collection

Measurement

Analysis

Vision

Professionalism

Leadership

Creativity

Organisation

Policies

Procedures

Coding structures

Art Science

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Questions & discussion