Jeff Robson
CEO, Access Analytic
Modeling Business Risks
in the Oil & Gas Industry
Introduction
•
About Jeff:
– Founding Director & Principal Consultant of Access Analytic
– Access Analytic is a West Australian consultancy that provides modelling,
reporting and analysis for medium and large companies to enable them to
improve their financial and operational performance.
– Focus: Australia/Oceania, Asia, Middle East, Africa
– Clients: Chevron, Woodside, BHP Billiton, Petronas, PetroVietnam, NIOC, SOC,
Dragon Oil, Eni, Inpex, Strike Energy, Otto Energy …
– Author of several white papers on Financial Modelling.
– Masters AppFin, F Fin, FAIM, CISA, MS Excel Expert
Introduction
•
•
•
•
Use CD & follow along
Excel versions
Housekeeping: facilities, times, e-mail, ph
Your models
How to get the most
out of this workshop
•
•
•
•
•
•
Take notes
Participate in discussion
Ask questions
Share experiences
Help those around you
Be on time
Workshop Structure
• Focus: practicalities of risk & modelling
• Part 1: Business Risks
– Key risk areas
– Financial modelling process: where to build in risk
– Methods & practical examples for dealing with risk
• Part 2: Model Risks
– Model risk areas
– Practical techniques for addressing model risks
Risk Areas
1. Business
Risk
Risks in the business/project
2. Model Risk
Risks in the financial model
used to assess the project
Part 1
Business Risks in O&G
Project Models
1. Business Risk
How could each of these impact an oil & gas project? Examples?
Economic Sensitivity
High Project Cost
Depleting asset
Political & Regulatory
Suppliers & Buyers
Project
Partners
Technology
Long Timelines
Substitutes
Environmental
O&G Specific Risks
• Specific risks regarding well commerciality:
–
–
–
–
–
–
Oil and gas price trends
Reserves of oil and gas
Distance from markets (particularly for gas)
Size of the market (particularly for gas)
Growth & type of market (particularly for gas)
Prospective production rates & whether stimulation is
required
– Reservoir performance
– Estimated life of reservoir
– Operating cost structure: offshore vs onshore
Financial Models
Inputs
Business Analysis:
risks, context
Scope
Purpose
Audience
Sensitivities
Assumptions, forecasts, base
data (eg historical financials,
economic data)
Outputs &
Logic
Calculations
Forecasts: cash
flow, P&L, B/S
High-level structure
Modules
Detail/Summaries
Charts
Documentation
Error Checking
Discount Rate
Valuation
Analysis &
Interpretation
Models at all Stages
Stage
Typical Projects & Activities
Pre-assessment
• Acquire permits
• Initial studies
Exploration
• Seismic
• Exploration drilling
Feasibility
Assess:
• Lease retention
• Studies (feasibility, commercial, conceptual, economic)
• Appraisal drilling
• Seismic
Select:
• Appraisal drilling
• Studies (feasibility, commercial, conceptual, economic)
Develop:
• Design & development studies
• Final Investment Decision (FID)
Execution
• Development wells
• Infrastructure
Operation
• Operating costs, infill wells, workovers
• Minor capital, infrastructure, purchases
• Corporate admin, venture management
Rehabilitation
• Rehabilitate
Sample Financial
Models
Model Types
Economic
Business Planning
Uses
Strategic planning,
project evaluation
Budgeting, forecasting
Timeframe
Long term
(5-30 yrs)
Short term
(1-2 yrs)
Detail
Low
High
Assumptions
Many broad, high-level
assumptions
Less assumptions, more
historical-based
forecasts
Accuracy
Lower
Higher
Scenario analysis
Many scenarios
Fewer
Key Issue in O&G Models:
• Uncertainty:
– Reserves
– Prices
– Production
– Project life
– Exchange rates
– Costs
• How do you allow for this?
Allowing for Business Risk
1. Sensitivities
2. Scenarios
3. Monte Carlo Simulation
1.1 Sensitivity Analysis
• What is sensitivity analysis?
– Analysis of model under different scenario(s)
– What-if, break-even analysis
• Purpose of sensitivity analysis?
–
–
–
–
Allow for uncertainty
What are the key drivers?
What if we’re wrong on one or more assumptions?
Determine range of likely values
• Output examples: “spider” charts, tables
1.2 Scenario Analysis
• Examine model results using different sets
of inputs
• Sensitivity: 1 input > 1 output
– Often symmetrical around a base value
• Scenario: multiple inputs & outputs
– Choose input values
• Outputs: tornado charts, waterfall charts,
tables
1.3 Monte Carlo
• Used in finance to value & analyse:
– Financial models
– Portfolios, investments, complex instruments etc
• Method to simulate sources of uncertainty that
affect inputs, & calculate the likely output range
• Multiple sources of uncertainty
• Estimate the range of numbers expected but not
the exact number
• Can be done in Excel. Often use an add-in such as
“Crystal Ball” or “@Risk” instead.
Monte Carlo Simulations
• Practical steps:
–
–
–
–
Construct financial model as normal
Identify variables impacted by uncertainty
Calculate or estimate the expected range of values
Generate large number of random values in a specific
distribution
– Run multiple simulations and record the results.
– Normal distribution: Excel
– Other distributions: Monte Carlo add-in
Non-normal Distributions
• Not all variables are normally distributed:
– Positively skewed: won’t be below a specified
minimum, but unlimited upside e.g. oil price, property
prices, stock prices
– Uniform: all values in the range are equally likely e.g.
heads or tails
– Triangular: values near the most likely are more likely
• Examine historical data or best estimates to
decide
Example: 1 Variable
Variable
e.g. oil price
Model Result Distribution
(depending on model’s calculations)
Example: Multi-variable
Inflation (narrow)
Oil price (normal)
Exchange rate (wide)
Model Result Distribution
Summary
Focus
Measure
Charts
Excel features
Result
Question(s)
Answered
Sensitivity
Scenario
Monte Carlo
1 input
1+ inputs
1+ inputs
1 output
1+ outputs
1 outputs
Spider chart
Tornado chart
Column or XY Scatter
Data tables, Goal
Seek, Solver
Data tables
Data tables
Discrete values
Discrete values
Range of values
What impact does a
variable have on the
result? What-if? What
is break-even?
What are the key
outputs in different
scenarios? How are the
key outputs affected by
changes in the inputs?
Taking into account the
different amounts of
variation in the inputs,
what is the likely range of
the key output?
Practical Examples
Part 2
Model Risks in O&G
Project Models
2. Model Risks
• The Maelstrom
Model Risks?
• TransAlta Corporation $24m write-off due
to spreadsheet error
• Magellan Fund $2.6b spreadsheet error
• Reinhart & Rogoff European debt paper
• JP Morgan London: $3.1b trading risk error
• Access Analytic client: $800m error
• 80-90% of large models contain error(s)
Risks can be Obscure
• What is this a picture of?
Assessing Model Risk
• Inherent Risk factors:
–
–
–
–
–
–
–
–
–
–
Model or results will be used by many people
Model has existed for a long period of time
Model deals with a complex area of business
Model or results will be used by senior management
Model has been designed or modified by >1 person
Model or results will be used for legal compliance
Model has a financial impact
Model or results will be published externally
Model has been changed many times
Model is a template for other users
• Free model risk assessment tool:
http://www.accessanalytic.com.au/SpreadsheetAuditing.html
Mitigating Risk with
Automated Testing Tools
• Purpose:
–
–
–
–
Assist a knowledgeable reviewer to identify risks
Automate simple checks
Identify risk areas
Grammar check
• Limitations
– Can’t understand business logic
– Verbose output
– Some tools require well-structured models
Automated Tools
• Spreadsheet Detective
www.spreadsheetdetective.com
• Spreadsheet Professional
www.spreadsheetinnovations.com
• Operis Analysis Kit (OAK)
www.operis.com/oak.htm
• BPM Toolbox www.bpmglobal.com
• XDrill www.sheetware.com
• XL Analyst www.XLanalyst.co.uk
Practical Example
• Spreadsheet Detective
On Your CD
• Exercises & suggested solutions
• Financial modelling templates
• Useful add-ins:
–
–
–
–
–
Spreadsheet Detective: auditing software (demo)
Invest for Excel: financial modelling software (demo)
BPM Traverse: tracking long formulas (free)
FindLinks: to find hidden workbook links (free)
Password Remover: workbook/worksheet passwords
• White papers & other useful guides
• Case studies
Thank you
•
•
•
•
Thank you for attending!
All answers are on your CD
Please complete your evaluation forms
Feel free to contact me if you have any questions
about financial modelling:
P +61 8 6210 8500
E jrobson@accessanalytic.com.au
W www.acessanalytic.com.au
facebook.com/accessanalytic
au.linkedin.com/in/jeffrobson
Twitter @AAnalytic