Transcript Uncertainty management in Statoil (Risk and opportunity

Uncertainty management in Statoil
(Risk and opportunity management)
NSP
18 September 2001
Requirements for uncertainty management in
development projects
•
AR005 - Project development in Statoil
•
Classification requirements for cost estimates and schedules
Practical guidance document
Recommended practices for uncertainty management in development projects
Presentation content
•
Uncertainty management trough project phases and decision gates
•
The qualitative uncertainty management process
•
The quantitative uncertainty management process
•
Presentation to management at decision gates
•
Findings and recommendations
Uncertainty management trough project
phases and decision gates
Project Development Process
Business
opportunity/
Exploration
Operations
Project Planning
Feasibility
DG0
(BoM)
DG1
(BoK)
Concept
DG2
(BoV)
Project Execution
Pre-engineering
Detail engineering
Construction
DG3
(BoG)
DG 0: Decision to start feasibility studies (BoM).
DG 1: Decision to start planning (BoK).
DG 2: Provisional project sanction (BoV).
DG 3: Project sanction (BoG).
DG 4: Start operations (BoD).
Testing and
commissioning
DG4
(BoD)
The qualitative uncertainty management
process
Tools :
Uncertainty
identification
Lotus Notes
PIMS
Uncertainty
response
control
Continuous
process
Uncertainty
assessment
Uncertainty
identification
Uncertainty
response
action
Uncertainty
assessment
Uncertainty
response actions
Uncertainty
response control
1.
Identify uncertainties
2.
Analyse uncertainties
3.
Prioritise/rank
uncertainties
4.
Develop an uncertainty
response
5.
Implement uncertainty
strategy
6.
Evaluate results
7.
Document uncertainty
results
New or
unknown
uncertainties
Periodic
review
Presentation to management at decision
gates (I)
Project uncertainty - Top 10 risks
Risk mapping - June 2001
Manageability
:
11
Low
Gas allocation
10
HPHT Drilling and completion
8
<--Negative Impact-->
Medium low
Gas Swing Services
9
Technology qualif. programs
7
Medium
high
High
Sand Control
Depth conversion uncertainty
6 QA for well equipment and services
5
Medium
Rig availability and cost
Movement from last period:
Well productivity in upper formation
4
Criticality
:
Segmentation
3
High
2
Medium
1
Low
0
0,0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1,0
<--Probability-->
Responsible : John Doe
Consequence : Consequence with NPV
Criticality : Potential to become "Show stoppers"
manageability and criticality
Manageability : Potential for management via the project team or through contractors
Probability : Probability for deviations reflected in consequence,
The quantitative uncertainty management
process
•
•
•
•
•
The quantitative uncertainty management process consists of performing
uncertainty analysis on the value chain.
A value chain includes all the variables that affect the cash flow.
Each uncertainty in the value chain is described with a probability
distribution and linked to the economical model.
Dependencies between variables are taken into account.
Uncertainty in project economy is calculated through Monte-Carlo
simulations.
Principle poster of the value chain analysis
Project framework
Results, uncertainties
and dependencies from
specialist tools are
modelled in Excel
spreadsheet
y
0
Uncertainty in reservoir and geology
Dependencies
Uncertainty in drilling and well
SCORE
Partly
x
Uncertainty in investment and
operational cost
Information
Production
Investment (CAPEX)
Drilling (DRILLEX)
Operational cost (OPEX)
Removal
Specialist tools
Expenditures Revenue
Statoil's economy model (Excel spreadsheet)
Presentation to management at decision
gates (II)
Mean NPV versus standard deviation
NPV after tax
350.00
Scenario 3
1.000
Mean NPV, million $
NPV (4)
NPV (5)
250.00
NPV (2)
NPV (7)
NPV (6)
Cumulative
probability
NPV (3)
300.00
.750
P90 = 410
.500
Mean= 291.91
.250
P10 = 153
200.00
.000
0.00
150.00
150.00
300.00
450.00
600.00
NPV, million $
Sensitivity on NPV
Scenario 3
100.00
STOIIP
NPV (1)
50.00
0.00
0.00
50.00
100.00
150.00
Standard deviation, million $
The numbers in brackets correspond to different scenarios
89.3%
Well rate
7.1%
Well cost
2.4%
Recovery
1.1%
200.00
0%
25%
50%
75%
Percentage contribution to variance in NPV
100%
Qualitative vs. quantitative uncertainty
management
Project Development Process
Business
opportunity/
Exploration
Operations
Project Planning
Feasibility
Concept
Project Execution
Pre-engineering
Detail engineering
Construction
Testing and
commissioning
Continues
process
DG1
(BoK)
DG0
(BoM)
DG2
(BoV)
DG3
(BoG)
DG4
(BoD)
Project framework
Results, uncertainties
and dependencies from
specialist tools are
modelled in Excel
spreadsheet
y
0
Uncertainty in reservoir and geology
Dependencies
Uncertainty in drilling and well
SCORE
Partly
Information flow
x
Uncertainty in investment and
operational cost
Information
Production
Investment (CAPEX)
Drilling (DRILLEX)
Operational cost (OPEX)
Removal
Specialist tools
Expenditures Revenue
Statoil's economy model (Excel spreadsheet)
Uncertainty management is a continues process through
all decision gates and project phases
Quantitative value chain analysis is mainly performed at
important decision gates.
Project ranking and portfolio management
Findings and recommendations
The qualitative uncertainty management process
•
•
•
•
•
•
•
The project management team must have ownership and actively support the
uncertainty management process
Uncertainty management must be established as a continuous process integrated in
project management
Uncertainty management must be delegated to the line of responsibility
High focus and effort should be given to the implementation phase. A person
responsible for facilitating the process should be appointed to secure sufficient
attention
Uncertainty management must be on the agenda in regular meetings
Uncertainty management must focus on the total value chain and the lifetime
perspective to secure an overall management of risks and opportunities
A practical detailing and structure is needed in order to reduce the number of
uncertainties
•
uncertainty management must be supported by efficient methods and tools.
•
Experience transfer from other projects is important
Findings and recommendations
The quantitative uncertainty management process
•
Keep the analysis simple
•
Treat uncertainties on an aggregated level
•
One person must be appointed to coordinate the process
•
Challenge the input from the different disciplines and search for dependencies
•
•
Make sure that the input corresponds to the uncertainty suppliers view (everybody is
not familiar with statistics and statistical definitions)
Present the results from the analysis to the project and explain in simple terms the
value chain and the effect of each input on the totality as a quality assurance of the
model
•
Get a second opinion on the model to avoid effects of subjective interpretations
•
Use benchmarking to quality assure the results