Oil & Gas Valuation Methods with a focus on Monte Carlo Analysis - PowerPoint PPT Presentation

Oil & Gas Valuation Methods with a focus on Monte Carlo Analysis Calgary October 4, 2012 Presented by: Justin Anderson, MSc., CFA 1

Justin Anderson’s Bio & Genesis of Xedge Research 1997 History of Xedge Research High School Graduation 1998 Programming – MIT: Research used general-equilibrium macroeconomic modelling. Firmed up Diploma programming knowledge already acquired at CDI. Thesis and research on the energy industry – Thesis title: “Impact of CO2 Legislation on Canada and Alberta’s Oil Sands”. 1999 – Waybe: Improved programming skill-set necessary for the eventual stream-lining of Xedge Research. 2000 – McKinsey: Developed basic understanding of running Monte Carlo simulations on Teaching English exploration portfolios. Significant focus on independent oil & gas companies with and learning Russian in Russia Colombian assets - especially Talisman Energy. 2001 – BMO : Built deeper international oil & gas industry connections and energy market expertise. – Xedge: Founded Xedge with the goal to produce superior technical research with the 2002 BSc Degree in constraints of rapid coverage capability on many names. Mechanical Engineering – Hired by Salman Partners Inc . as an Oil & Gas Research Analyst to produce BA Degree in Russian independent research reports using Xedge-developed methodology. 2003 Studies 2004 Founded waybe.ca Founded Xedge while at MIT Research 2005 2006 2007 2008 2009 2010 2011 2012 Oil & Gas Masters in Aeronautics with Oil & Gas Business Analyst Oil & Gas Investment Banker Research Economics focus 2 Analyst

Expected Presentation Outline Time (mins) 5 Standard Methods to Value Oil & Gas Companies 15 Using Monte Carlo to Value Oil & Gas Companies 5 Sample Valuation of an Oil & Gas Company Q & A 3

Primary Valuation Methodologies in Oil & Gas Trading Transaction Share EV* EV / EV / EV / Share EV* EV / EV / EV / Company Price (Smm) Funds Flow Prod. 2P Res. Company Price (Smm) Funds Flow Prod. 2P Res. Pacific Rubiales Energy $24.68 $8,187 5.3x $75,042 $16.72 PetroMagdalena (prior to bid) $1.25 $263 5.3x $68,434 $11 Gran Tierra Energy $5.19 $1,299 4.5x $61,988 $21.01 PetroMagdalena (bid) $1.60 $332 6.4x $86,392 $13 Parex Resources $4.85 $605 2.5x $58,216 $56.61 Multiples C&C Energia $6.55 $380 2.5x $36,161 $20.65 Canacol Energy $0.48 $293 2.8x $21,678 $29.65 Petrodorado Energy $0.17 $40 nmf nmf $75.66 PetroNova $0.42 $54 nmf nmf nmf Sintana Energy $0.13 $27 nmf nmf nmf ArPetrol $0.02 $7 nmf $26,728 $0.83 Peer Group Average 3.5x $46,635 $32 *EV = Enterprise Value = (Shares Outstanding x Share Price) + Value of Debt Peer Group Multiples Transaction Multiples Deterministic FF Ratio EV / EV / FF Ratio EV / EV / (EV/FF) (3) (EV/FF) (3) DCF Prod. 2P Reserves Prod. 2P Reserves 3.5x $46,635 $32 6.4x $86,392 $13 SPE Company Metrics SPE Company Metrics ** Funds Production 2P Reserves Funds Production 2P Reserves Flow ($mm) (bbl/d) (mmbbl) Flow ($mm) (bbl/d) (mmbbl) 25,000 50 25,000 50 400 400 Implied Valuation of SPE Implied Valuation of SPE EV EV EV EV EV EV ($mm) ($mm) ($mm) ($mm) ($mm) ($mm) $1,400 $1,166 $1,600 $2,560 $2,160 $650 Valuation of SPE (based on Trading Multiples) Valuation of SPE (based on Trading Multiples) Current Share Implied EV Implied Market Implied Share Undervauled/ Current Share Implied EV Implied Market Implied Share Undervauled/ Price ($mm) Cap ($mm) Price ($mm) Overvalued Price ($mm) Cap ($mm) Price ($mm) Overvalued $10 $1,389 $1,289 $14 Undervalued $10 $1,790 $1,690 $19 Undervalued 4 Source: Salman Partners Inc. **90mm Shares Outstanding, $100mm Debt

Primary Valuation Methodologies in Oil & Gas Inputs Production Economic Annual Realized Sale Operating Taxes Discount (bbl/d) Life (years) Decline (%) Price ($/bbl) Exp. ($/bbl) ($/bbl) Rate (%) Multiples 35,000 5 40 90 30 10 10 Model Engine Year 1 Year 2 Year 3 Year 4 Year 5 NPV-10 ($mm) = CF1 + CF2 + CF3 + CF4 + CF5 Deterministic (1+k) (1+k)^2 (1+k)^3 (1+k)^4 (1+k)^5 DCF Outputs Year 1 Year 2 Year 3 Year 4 Year 5 NPV-10 ($mm) = $581 $317 $173 $94 $51 NPV-10 ($mm) = $1,216 Valuation of SPE (based on DCF) Current Share Implied EV Implied Market Implied Share Undervauled/ Price ($mm) Cap ($mm) Price ($mm) Overvalued 5 Source: Salman Partners Inc. $10 $1,216 $1,116 $12 Undervalued

Expected Presentation Outline Time (mins) 5 Standard Methods to Value Oil & Gas Companies 15 Using Monte Carlo to Value Oil & Gas Companies 5 Sample Valuation of an Oil & Gas Company Q & A 6

Stochastic vs. Deterministic DCF Asset 1 Asset 2 Asset 1 Asset 2 Asset 3 Key G&G Data Chance of 24% Asset 3 Success Reserves 50mmboe Deterministic DCF Field Size 24%xP50 % Gas 2% Production Fixed production 32 o Liquids API profiles profile Key Economic Data Working Interest 50% Cash flows Fixed cash flows % Gas 2% Exp. cost $5mm Appraisal and 5 appraisal wells, Development 20 development Capex F(discovery) wells wells Opex $10 per boe Time to develop 2 years Deterministic Fiscal Regime Colombia DCF Medium Oil Price Oil WTI Futures Asset 1 Asset 2 Asset 1 Asset 3 Stochastic DCF Reserves Asset 2 (ie. Monte Carlo) Asset 3 Production Stochastic profiles Key Data Same as above except: DCF (ie. Chance of Cash flows Monte Carlo) Success Appraisal and Field Size Development wells 7 Source: Salman Partners Inc.

Valuation Methodologies in Oil & Gas Methodology Considerations Applicability to O&G Exploration Enterprise value (market cap + net Pro : Fast and easy The diversity of companies in oil and gas � debt) is divided by a variety of exploration limits multiples for valuation. Con : Requires comparable Multiples usually are good 1 st pass metrics to compare across companies, relative valuations companies indicators but more analysis is needed to Most Common only (will not indicate if entire Multiples improve valuation accuracy. sector is over or under-valued). Possible metrics include reserves, � resources (risked and un-risked), NAV (net asset value) can be derived production, EBITDA, etc. using multiples or DCF or a mix of both Assets are valued based on Pro: Reflects fundamental asset NAV is the valuation method of choice � estimated future cash-flows value; Useful for diverse companies in oil and gas valuations and can be discounted at an appropriate derived using multiples (simple, less Con : Requires detailed Deterministic discount rate refined) or DCF (harder, more refined) assumptions to develop reliable or a mix of both DCF cash flow forecasts Model assumptions are � deterministic ( single-values ) as are model outputs (ie. A single NAV or NPV) Assets are valued based on Pro: Excels when outcome Monte Carlo analysis of exploration � estimated future cash-flows certainty is low but the possible portfolios is relatively common within discounted at an appropriate outcomes are well defined (ie. E&P companies for internal portfolio discount rate (same as rolling a 6-sided die, black-jack). assessments Stochastic deterministic DCF) Con : Complicated analysis DCF (ie. requiring even more detail than Some model assumptions are � Monte Carlo) deterministic DCF. Also, if poorly probabilistic distributions rather defined inputs are used, subject to than single-values . (ie. instead of garbage-in, garbage-out Resource = 50mmbbl, Resource = values in a log-normal distribution ranging from 1 to 100 mmbbl). 8 Source: Salman Partners Inc.

Which Methodology is Best? Stochastic DCF Deterministic DCF Multiples Increasing Understanding of Possible Outcomes Producing Assets Well-defined (discoveries) Exploration Assets (prospects) Immature Exploration Assets (leads) Impossible to Value Increasing Outcome Certainty 9 Source: Salman Partners Inc.

Current Methodology Used on the Street? Methodology Rationale � Multiples (ie. NAV) � Less outcome uncertainty in booked reserves and � Deterministic DCF (ie. NAV, NPV) production suggests Producing deterministic DCF is Assets usually the best approach � Deterministic modelling � Multiples (ie. NAV) fails to capture the � Deterministic DCF (ie. “Risked” NAV) impact of downside risk and upside on valuation Exploration Assets “Risked” NAV 10 Source: Salman Partners Inc.

Valuing a Single-Attempt Uncertain Outcome Game (one attempt allowed) Adjusting for Risk Risk Neutral ($mm) Risked Averse ($mm) Amount of Downside Risk? 1 100% Chance – you get $1mm 1 1 Pmean of the Game = $1mm Risk Free 50% Chance – you get $2mm 2 50% Chance – you get $0 1 0.8 Coin Toss Pmean of the Game = $1mm 1% Chance – you get $100mm 3 Price of Risk? 99% Chance – you get $0 1 0.3 Unlikely Pmean of the Game = $1mm 0.01% Chance – you get $10bn 4 99.99% Chance – you get $0 1 0.1 Impossible Pmean of the Game = $1mm � Amount of downside risk and the price of risk are the key drivers Valuation � How to measure the amount of risk? 11 How to measure the price of risk? � Source: Salman Partners Inc.