Petroleum Economics [PDF]

Zitiervorschau

INTEGRATED GRADUATE DEVELOPMENT PROGRAM CLASS 2011 PETROLEUM ECONOMICS David Wood

IN-HOUSE COURSE prepared for

OMV EXPLORATION & PRODUCTION GMBH Vienna, Austria

HOT Engineering GmbH Parkstrasse 6 A-8700 Leoben, Austria Tel: +43 3842 430530 Fax: +43 3842 430531 E-Mail: [email protected] www.hoteng.com

Copyright © 2012 by HOT Engineering GmbH Parkstrasse 6, A-8700 Leoben, Austria All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, mechanical, photocopying, recording or otherwise, without written permission from HOT Engineering GmbH. Printed in Austria. Not for sale.

Overview of Course Objectives & Materials The Need for Petroleum Economics Project Cash Flow & Income Components Project Cash Flow & Income Components (Exercise #1) Petroleum Reserves Categories & Valuation Discounting & Time-Value Considerations (Exercise #2) Rates of Return Payout Time or Payback Periode Profit to Investment Ratios Risk and Opportunity Analysis Capital Budgeting Techniques & Yardsticks (Exercise #3) Which Oil & Gas Prices Should be Used to Value Assets? Valuing Incremental Investments Inflation, Buying Power, Money of the Day & Real Values Inflation Indices Estimating Values & Costs and Budget Cost Control (Exercise #4) Introduction to Upstream Fiscal Terms & Contract Types Production Sharing & Cost Recovery (Exercise #5) Funding Criteria: The Cost of Capital & Oil & Gas Finance Hurdle Rates and Selection of Discount Rates Probabilistic Methodology & Techniques for Economics & Risk Analysis Decision Analysis, Decision Trees & Flexibility Monte Carlo Simulation Demonstration (Exercise #6)

Petroleum Economics Overview of Course Objectives & Materials David A. Wood

Course Structure & Approach

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The course is structured into a sequence of PowerPoint presentations and exercises. Your participation is welcome. My preference is for an informal approach to encourage an exchange of ideas and experience.

The course aims to be a stimulating & enjoyable experience for all!!

© by David A. Wood

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Course Director: David A. Wood               

Some 30 years of energy industry experience Widespread international operations & project exposure Governments, majors, independents, services & consultants

www.dwasolutions.com [email protected] Twitter: @DWAEnergy Facebook: DWA Energy Limited LinkedIn: David A. Wood

Technical, commercial, training and senior corporate expertise Risk, economics, portfolio and fiscal modelling & research Advises governments and companies on approaches to fiscal design Broad focus: upstream, midstream and downstream Technical evaluation, numerical modelling and due diligence Mergers, acquisitions and divestments (management & negotiation) Project finance, hedging and trading Oil, gas (LNG, GTL and storage), power and renewables Strategy, geopolitics and contract negotiations PhD - Imperial College London (1977) – geology / deepwater drilling Diploma Company Direction – Loughborough / IOD (1996) Independent consultant since 1998; widely published; expert witness

© by David A. Wood

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Petroleum Economics 2-day Module – Daily Themes Outline structure of course - each day has a distinct theme. The aim is to provide delegates with a comprehensive introduction and balanced view of petroleum economics.

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Day 1 – Basic Analysis & Valuation Techniques

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Day 2 – Constructing Economic Evaluation Models

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DAY 1 – Basic Analysis & Valuation Techniques Morning Session 4.1

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Overview of Course Objectives & Materials The Need for Petroleum Economics Project Cash Flow & Income Components

Morning Break Morning Session 4.2

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Distinguishing Cash Flow & Other Measures of Profitability (Exercise#1) Petroleum Reserves Categories & Valuation Discounting & Time-Value Considerations (Exercise#2)

Lunch Break © by David A. Wood

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DAY 1 – Basic Analysis & Valuation Techniques Afternoon Session 4.3

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Rates of Return Payout Time Profit to Investment Ratios Risk and Opportunity Analysis

Afternoon Break Afternoon Session 4.4

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Capital Budgeting Techniques & Yardsticks (Exercise#3) Which Oil & Gas Prices Should be Used to Value Assets?

End of Day 1 © by David A. Wood

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DAY 2 – Constructing Economic Evaluation Models Morning Session 4.5

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Valuing Incremental Investments Inflation, Buying Power, Money of the Day & Real Values Inflation Indices Estimating Values & Costs and Budget Cost Control (Exercise #4) Introduction to Upstream Fiscal Terms & Contract Types

Morning Break Morning Session 4.6

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Production Sharing & Cost Recovery (Exercise #5) Funding Criteria: The Cost of Capital & Oil & Gas Finance Hurdle Rates and Selection of Discount Rates Probabilistic Methodology & Techniques For Economics & Risk Analysis

Lunch Break © by David A. Wood

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DAY 2 – Constructing Economic Evaluation Models Afternoon Session 4.7

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Decision Analysis, Decision Trees & Flexibility Monte Carlo Simulation Demonstration (Exercise #6) Assessment Test

Afternoon Break Afternoon Session 4.8

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OMV Session on in-house “Easy Evaluation” Pre-tax Cash Flow Tool

End of Module

© by David A. Wood

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Ask if You Need Clarification

There is a lot of material to get through, but time will be made for discussion.

Don’t be shy!

© by David A. Wood

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Petroleum Economics The Need for Petroleum Economics David A. Wood

Key Metrics Show Distinctive & Dislocated Trends For E&P Assets

Key performance indicators (KPIs) give different impressions at different stages of an oil and / or gas assets life cycle. Economic and risk analysis provides a means of clarifying and quantifying the importance and relevance of these trends.

© by David A. Wood

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E&P Investment Appraisal & Decisions Upstream projects are characterised by:

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Large initial capital investment High rate of capital investment throughout asset life

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Long payback period

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High risk and uncertainty

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Complexity

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Multiple stages with deferrable decision points Incremental information flows and decision points Dependency upon volatile product prices and demand

© by David A. Wood

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Cost – Time Cycle for Exploration Through to Field Production

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Constraints on Upstream Oil & Gas Companies Major upstream companies are characterised by:

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Large portfolios of E&P projects available for investment at any one time.

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Finite technical resources & skills to evaluate & manage each project.

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Finite time in which to perform commitment work programmes

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Finite financial resources and frequent budget constraints making them not indifferent to the level of risked capital required to optimise the portfolio.

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Which Development Option Makes Most Economic Sense? The type of field facilities, number of wells, timing of drilling, owning or leasing facilities are all decisions that require economic and risk analysis as well as engineering design.

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Oil Industry of Last 30 Years has been Characterised by Volatility Volatility caused by booms and recessions driven by the supply-demand balance and oil prices. For how long will such cycles be repeated?

Access to quality international upstream permits to explore and develop is a major challenge for IOCs, together with finding and retaining skilled staff.

Oil supply & demand main drivers for volatility in recent decades © by David A. Wood

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Boundary Scenarios Can Frame Economic Sensitivity Analysis Framing the future in terms of options helps to identify and quantify key issues and potential risks and pitfalls. Sensitivity and Simulation analysis are frequently essential to understanding the full picture.

It is important for economic analysts to consider more than one future. © by David A. Wood

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Costs of Delays in The Exploration & Appraisal Portion of Field Life Cycle Delays in exploration / appraisal always have a negative impact on project / company profitability over the long-term project or field cycle. Economic and risk analysis quantifies this impact.

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Extending Field Life by Reducing Operating Costs & Overheads Economic analysis can identify when it is necessary to introduce structural changes in order to extend the projects commercial life by reducing operating / production costs.

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Risk & Fiscal Analyses are Key Parts of the Investment Decision Process The economic structure of the oil and gas industry is intimately associated with risk versus reward tradeoffs and fiscal designs.

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© by David A. Wood

Modern Portfolio Modelling Approach: Economic, Risk and Strategy Analysis In a portfolio approach projects are judged based on their contribution to long-term strategy, and how they interact with the other projects in the portfolio, as displayed by the feasible envelope, efficient frontier and probabilities of metrics being achieved. This is a dynamic process.

Portfolio modelling & management should firmly link investment decision-making at the asset, portfolio and merger / acquisition/ divestment levels to a quantified corporate strategy.

© by David A. Wood

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There are Many Different Reasons Why Valuation & Risk Analysis are Required The results of such analysis are almost always ultimately linked to assisting and clarifying decisions. Some of the main reasons are:

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Establishing that a project can achieve acceptable profitability Comparing the value of projects & investment opportunities Allocating values to different categories of reserves Indicating threshold commercial field sizes in specific environments Distinguishing the most appropriate field development plans Testing the impact of different economic scenarios (e.g. oil price) Assessing the impact of costs and overheads on project returns Identifying value at different points along the supply chain Consider available options for optimising returns from reserves Evaluating merger, acquisition and divestment opportunities Justifying budgets, forecasts, business plans and strategic options Negotiating and comparing fiscal and contract terms Securing project finance and other forms of debt Reporting historical performance & forecasting to stakeholders Quantifying the impact of risk and opportunity on projects Valuing portfolios of oil and gas projects & assessing performance

We will address these reasons and several others during this course. © by David A. Wood

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Petroleum Economic & Risk Analysis Aids Decisions to Balance Risk & Reward Balancing is never easy!!!

Economic & risk analysis is a fundamental process in strategic and operational management of the oil and gas industry. © by David A. Wood

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Petroleum Economics Project Cash Flow & Income Components David A. Wood

Simplified Flow Chart For The Financial Process in a Typical Upstream Oil Company The role of financial management is to optimise the value and use of the basic reservoir of cash and its associated funds flow. Financial management involves funding decisions in the raising of cash in the form of equity and debt. It also involves the efficient allocation of funds between assets, credit investments, etc. Reserves do not appear in this model but can influence depreciation.

© by David A. Wood

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Focus of Economic Analysis For an oil and gas company to prosper it has to find and/or acquire new reserves and make a financial profit.

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E&P companies do not stay in business long without returning a financial profit. Production cannot be sustained without new reserves to produce. Economic analysis must therefore be focused on increasing profits and optimising profitability from their reserves. A key question is how do we define and measure profit?

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© by David A. Wood

Upstream Cash flow Components: Influence Diagram – Role of Reserves Costs are an important component controlling the overall value of projects and reserves. Costs are distinguished as CAPEX & OPEX. CAPEX Decisions, such as project design or field development often pivot on cost, timing, efficiency and capital constraints, e.g. well design. In the production stage OPEX is often the focus in determining efficiency, profitability and viability. Reserves and reservoir characteristics have huge influence on cash flow components.

© by David A. Wood

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Basic E&P Economic Analysis Techniques Are Straight-forward None of the economic calculation techniques commonly applied are complex but their analysis can become so. Most economic evaluations readily establish:  levels of capital investment required  future cash flows  national or local tax liabilities  earned and paying interests The complications arise in:  ranking projects against each other  allowing for existing commitments  allocating & monitoring sources of funds  identifying risks and opportunities  correctly adjusting cash flow for uncertainty  Estimating chances of success.  market conditions and product price forecasting.

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© by David A. Wood

Petroleum Projects Require High Capital Outlay to Achieve Long-term Returns There is an unparalleled relationship of expenditure, risk, timing and revenue in the oil and gas industry that distinguishes it from other industries.

E&P economic analysis focuses on the value of available reserves and the timing of their production that maximizes cash flow and profits (earned income) for those holding interests in those reserves.

© by David A. Wood

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Cash Flow Projections Cumulative net cash flow is the basis for most economic analysis. It is calculated on a “before and after tax” basis and has these major components:

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Cash Items: monies actually paid and received. Non-Cash Items: such as depreciation, depletion (North America), book values used mainly for tax and accounting calculations. Royalties: property of the state either paid in money or product is not technically a cash or non-cash item as it is never owned by the E&P company.

© by David A. Wood

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Cash Flow Components - Cash Items Monies actually paid and received can be subdivided into a number of specific categories:

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Working interest E&P revenues Income from property sales (and their capital gains tax) Working interest local taxes Operating costs Overheads (corporate / operational, G&A, loan interest) Capital investments Land, lease and licence fees and bonuses Corporation taxes (investment tax credits) Special petroleum taxes (e.g. PRT in older UK licences) Debt capital and interest repayments

© by David A. Wood

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Cash Flow Combines Cash Inflows with Cash Outflows Inflows usually equate to production revenues but also may include asset sales. Outflows include expenditures and taxes.

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© by David A. Wood

Taxable Income is Not Cash Flow but Profit Adjusted by Accounting & Taxation Rules

Calculations of taxable income depend upon accounting and tax rules which vary from country to country and sometimes between E&P contracts in the same country. It is often referred to as Net Income or Earnings (in US)

© by David A. Wood

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Calculation of Key Project & Corporate Accounting Measures Applicable to Oil & Gas Projects

The term Mineral-Interest Reserves is used to distinguish projects from those projects subject to the terms of Production Sharing Agreements (PSAs). Some companies focus more on cash flow performance (~EBITDA) others more on earnings.

© by David A. Wood

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The Tax Burden in E&P Contracts Has Many (Often Complex) Components

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Taxable Income Is Usually Not Cash Flow Calculations of taxable incomes depend upon accounting and tax rules, particularly involving the depreciation of capital costs.

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Generic Corporate Tax Model Calculations of taxable incomes, particularly in tax-royalty fiscal regimes, are usually complex and require specialist tax advice.

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Depreciation of Capital Costs This is applied to costs for items that will benefit the company for more than a single year. It is a system that spreads the costs of such items over each year of its useful life or production unit.

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Depreciation can be calculated in a variety of ways some of which load more depreciation on to the early years where the equipment is most useful and its maintenance costs should be lowest. Methods allowed depend upon prevailing legislation. Book value of capitalised assets is their original cost less the accumulated depreciation. It should not be confused with market value or replacement value. A gain or loss on the sale of an asset is computed by comparing the sale price with the book value. These are included as extra line items on income statements. Small items even though they may last several years are often treated as an expense in the year in which they are purchased provided it does not yield material errors.

© by David A. Wood

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Typical Asset Lives For DD&A Purposes Asset lives will depend upon prevailing legislation, but example ranges are:

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Production plant including in-field flow lines and tangible well costs - 5 to 10 years. Intangible costs (sometimes a portion of these have to be capitalised rather than expensed) – 5 years.

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Drilling equipment & vehicles – 5 years.

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Transmission / Trunk pipelines – 10 to 40 years.

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Refinery Plant & equipment – 10 to 20 years.

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Buildings – 20 to 30 years.

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Computer hardware and software – 3 to 5 years.

© by David A. Wood

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Depreciation & Calculation of Book Value Depreciation records are concerned with costs not value. Hence purchase price less accumulated depreciation equals remaining cost but is termed the book value. This is not a value but a remainder.

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Consider a machine that cost $60,000 and management estimates its useful life to be 10 years and its salvage value after 10 years to be $10,000. On a straight-line depreciation basis the annual depreciation rate will be ($60,000 - $10,000) /10 which equals $5,000 per year. At the end of the second year an accumulated depreciation schedule for the machine could be: – Original purchase costs:

$60,000

– 1st year depreciation allowance:

$5,000

– 2nd year depreciation allowance:

$5,000

– Total accumulated depreciation:

$10,000

– Book Value:

$50,000

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© by David A. Wood

Depreciation is a Key Non-cash Component in Calculating Net Income Amortisation of capital investments so as to spread costs over a period of time for tax or accounting purposes. Methods are designed to recover capital costs over the life of an asset. Some depreciation methods accelerate the amortisation process (e.g. double declining balance; SYD; MACRS). Depreciation methods used in E&P industry are: –

Units of Production (costs recovery linked to production and reserves) - widely used for accounting purposes.

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Straight Line - costs recovered in equal fractions per year.

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Declining balance - various rates are applied - single(100%), 150% & double (200%) rates used.

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Sum of the Years’ Digits (rarely used outside North America).

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MACRS -(modified accelerated cost recovery system) used for U.S. federal income tax (FIT) capital cost depreciation

© by David A. Wood

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Depreciation & Capital Cost Recovery Depreciation rate is important to project valuation in that it controls how quickly capital investments are recovered from cash flow.

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From the investor’s point of view it wishes to recover all costs as soon as possible. The best solution would be expensing all capital costs together with operating cost (equivalent to a 100% annual depreciation rate applied from the year of expenditure). If capital costs are depreciated over 5, 10, or 20-year periods discounted cash flow values for a venture decrease as the annual depreciation rate reduces. Governments like to have low annual depreciation rates as it increases their tax revenues as companies show higher taxable incomes in the early years of a project. This is a means of governments receiving a share of revenues from oil and gas projects from early in the production life of a field development.

© by David A. Wood

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Different Rates of Depreciation It is not unusual for different depreciation rates to be applied to different categories of capital expenditure.

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Exploration costs (drilling & G&G costs) are often depreciated at 100%(i.e. expensed) to provide investors with an incentive to make new and risky investments. Development costs are often divided into categories such as tangible (plant with a long life) and intangible (materials or services consumed in an operation, e.g. drilling mud, wire-line services). The intangibles are often expensed or subject to a more rapid depreciation rate. Allocation between categories can be arbitrary and subject to change. It is the cause of many disputes with the tax authorities. UK authorities have in recent years reduced the depreciation rates applied to intangibles on development wells in response partly to side-track technology developments.

© by David A. Wood

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Depreciation, Depletion & Amortization - DD&A This originally North American concept is now also widely used in international oil and gas accounting.

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Depreciation is a means of accounting for the recovery and allocation of costs associated with fixed (tangible) assets over the deemed useful life of an asset. Annual depreciation charge is deducted from revenue in the net income calculation. Depletion is the same concept as depreciation but applied to purchase prices (i.e. acquisition values) of mineral resources (e.g. oil & gas) enabling them to be deducted for tax purposes over time. Amortization is the same concept as depreciation but applied to intangible assets. Commonly these terms are used interchangeably and /or collectively as DD&A. Depreciable life of specific assets is governed by rules specified in the prevailing accounting and tax legislation.

© by David A. Wood

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Example DD&A Methodology Stated by US Oil Company in a 10-K Return to SEC The following extract comes from Apache Corp’s form 10-K submission of Feb, 2011 to SEC for year ending Dec 31st 2010:

Source: Apache Corp 10K 2010 © by David A. Wood

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DD&A is an Operating Expense on the Income Statement The following extract comes from Apache Corp’s condensed statement of operations in its 10-K submission of Feb, 2011 to SEC for year ending Dec 31st 2010:

Source: Apache Corp 10K 2010

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© by David A. Wood

Depletion (DD&A) Calculated by Unit of Production Method DD&A is the only impact reserves have on the profit & loss (income) statement. The unit of production annual depletion calculation can be expressed generically by the equation: (C – AD – S) * P / R Where: –

C

= Capital cost of plant and equipment

–

AD

= Accumulated depreciation to date

–

S

= Salvage or residual value

–

P

= Annual production (boe)

–

R

= 1P Reserves Remaining at beginning of year (or 2P reserves in Canada and many other countries)

The unit values that are deducted for tax purposes can be substantial (e.g. $2/boe up to >$10/boe. The higher values may indicate higher cost / lower reserves than originally expected. Good performers maintain DD&A charges below $5 / boe particularly when calculated on a 2P basis. Merger and acquisition costs are usually included in the depletion cost pool. © by David A. Wood

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Petroleum Economics Project Cash Flow and Income Components (Exercise #1) David A. Wood

Calculation of “Profit”, “Cash flow” & “Income” Measures Applicable to Oil & Gas Projects

When a figure is referred to as “profit”, “cash flow” or “income” without qualification or explanation it is important to distinguish what it is actually measuring. There are several different possibilities! © by David A. Wood

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Input Information for Calculating Measures of “Profit”

When a figure is referred to as “profit”, “cash flow” or “income” without qualification or explanation it is important to distinguish what it is actually measuring. There are several different possibilities! © by David A. Wood

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Petroleum Economics Petroleum Reserves Categories & Valuation David A. Wood

How Do We Know There are Reserves Out There? “Shell said the oil exists – if only they can find it. Trouble is, they can’t convince the SEC”. Same applied in 2004 to El Paso, Forest, Nexen, Husky, etc…. Many reserve write-downs occurred. These headlines in the general media and cartoons emphasize the popular view of how oil reserves are measured and how they exist in the sub-surface. Reality is more complex and uncertain, but Shell are damaged by both popular image and the technical reality.

© by David A. Wood

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Relevance of Resources Versus Reserves to Petroleum Portfolios

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Conventional versus Non-conventional Petroleum Resources SPE Oil & Gas Resource Committee (2007) place Ultra-heavy crude, tight gas sands and shale gas in their conventional categories. They draw the horizontal line lower.

© by David A. Wood

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Classification of Upstream Oil & Gas Assets & their Reserves

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Reserves Terminology Commonly Applied in Valuation

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1P Reserves – Proven Developed (PD) – Producing (PDP) – Non –producing (PDNP) – Proven undeveloped (PUD)

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2P Reserves – Proven plus Probable

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3P Reserves – Proven plus probable plus possible

© by David A. Wood

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Petroleum Reserves Classification SPE versus SEC Until 2010 SPE and SEC have had different requirements for reserves reporting that has caused many issues for petroleum companies registered on US stock exchanges.

© by David A. Wood

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Petroleum Reserves Classification SPE / WPC / AAPG / SPEE This approach is in line with SPE /WPC / AAPG /SPEE guidelines and the Petroleum Resource Management System (PRMS) approved in 2007 updated November 2011.

© by David A. Wood

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Resource Classification Commences with In-place Classifications Culmination of two-year review approved in March 2007 (updated Nov 2011).

© by David A. Wood

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Bookable Oil & Gas Reserves Valued in Production Asset Sales

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Aligning Reserves Definitions with Petroleum Project Cycle This approach is in line with SPE /WPC / AAPG /SPEE guidelines and the Petroleum Resource Management System (PRMS) approved in 2007.

SPEE = Society of Petroleum Evaluation Engineers AAPG = American Association of Petroleum Geologists

© by David A. Wood

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Project-based Approach Works best for Petroleum Reserves Valuation Petroleum Resource Management System (PRMS, 2007) recognises the need for much more than establishing resource volumes.

© by David A. Wood

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Categorizing Reserves by Levels of Uncertainty – Key to Valuation Petroleum Resource Management System (PRMS, 2007, 2011) acknowledges deterministic and probabilistic methodologies. In practice integrating both approaches is useful.

© by David A. Wood

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Forecasts and Valuation Scenarios

Valuations and decisions are based on the evaluators view of “Forecast Conditions” – i.e. those assumed to exist during a project’s implementation. Alternate valuation scenarios are typically considered in the decision process and, in some cases, to supplement reporting requirements. One sensitivity case commonly reviewed assumes “current conditions” will remain constant throughout the life of the project (“constant case”).

© by David A. Wood

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Pivotal Role for Probable Reserves in Acquisition Valuations In some areas, probable reserves assume a key role in acquisition values. Significant value is ascribed to probable reserves in: Offshore, particularly in hostile or deep water environments. where significant investment decisions for facilities and infrastructure have to be made early in development. Assets are immature and lots of undeveloped potential remains. Internationally probabilistic reserves categories are applied. 2P reserves (probabilistic proved plus probable) is the reserve estimate commonly where probable reserves are to form a significant part of the assets to be acquired. Method is suited to valuing whole fields rather than small parcels of land. However, internationally it is also not unusual to discount or risk probable reserves more heavily than proved reserves when calculating acquisition values.

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© by David A. Wood

Why Do Companies Acquire Assets, Merge or Divest? Because the benefits out-weigh the downsides and growth or focus on material assets can be achieved. The most common reasons given by oil companies are to:  achieve greater efficiency;  consolidate and grow to meet increased competition;  increase shareholder value;  benefit from operational synergies;  diversify asset portfolio;  balance asset portfolio.

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Mergers and acquisitions do allow economies of scale and step-decreases in G&A costs. Downsides are potential job or location cuts. Restructuring and relocation often mean many voluntary and involuntary redundancies.

© by David A. Wood

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How Does an Acquisition or Divestment Add Value to an Asset Portfolio?

© by David A. Wood

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Petroleum Economics Discounting & Time-Value Considerations (Exercise #2) David A. Wood

Time-Value Considerations Oil and gas projects are characterised by high capital investment in early years, without revenue, followed by high revenue after production startup which gradually declines in line with production towards field abandonment.

Rate at which costs are recovered impacts contractor’s value. © by David A. Wood

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Present Value (PV) Concepts Money to be received at some time in the future is said to have a present value which is less than the amount received by the interest that could be earned on it in the interim.

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The PV is the amount that could be invested at an interest rate such that the amount plus the total interest earned equals the future value (FV).

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Future value (FV) = PV + (i * PV )

(where i is the interest rate for one

interest period and FV is the value at the end of that one interest period).

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Re-arranged to: FV = PV (1 + i)

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An example: FV = ($2,000) (1+0.15) = $2,300 so that $300 is the simple interest at 15% on an investment of $2,000 (the principal).

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© by David A. Wood

Present & Future Values and the Time Value of Money PV and FV are related to each other through interest rates and discount factors.

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For example, if an interest rate (i) of 10% applies for one investment period then a PV of US$10 million has a FV of US$11 million at the end of the investment period: FV = PV * (1 + i)

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In this example the FV of US$11million can be discounted to a PV of US$10 million at the start of the investment period by applying a discount factor (1 + d) of 10%: PV = FV / (1 + d)

© by David A. Wood

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Simple Versus Compound Interest If the interest is withdrawn at the end of the period only simple interest (on the principal investment) is earned the next period.

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If the interest is re-invested in subsequent periods it will earn interest itself in addition to that earned by the principal, i.e. compound interest. Compound FV for a second period: –

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= ($2,300)(1.15) = ($2,000)(1.15)(1.15) = $2,645

Thus FV of a PV invested at an interest rate of i per year has the general form: –

FV = PV (1 + i)n

–

(1 + i)n

where n = number of years

is called the compound factor.

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© by David A. Wood

The Discount Factor This is the reciprocal of the compound factor and represents one of the most important concepts of cash flow analysis. Applying the discount factor to the FV calculates its PV such that: –

PV = FV [ 1 / (1 + i)n ] = FV (1 + i) –n

–

Hence the PV of an FV of $6,125 to be received at the end of three years based on an annual interest rate of 7% is $5,000.

–

$5,000 = $6,125 (1 + 0.07) –3

–

In this case the 7% is called the discount rate.

© by David A. Wood

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Risking Cash Flow Profiles by Increasing Discount Rate is Not Appropriate Higher discount rates preferentially penalise later years in a cash flow profile.

© by David A. Wood

Net Present Value (NPV) is the Sum of Discounted Cash Flows for Each Period A general solution for the NPV calculation is:

 



where CFj is the annual net cash flow in year j, i is the discount rate, n is the total number of time periods. Cash flow in the initial period CF0 remains undiscounted. This can be more neatly expressed as:

Most spreadsheets have NPV functions. It is important to take care that the initial investment and type of discounting applied to it are appropriate.

© by David A. Wood

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Net Present Value Profile Trends Calculating the NPV’s of cash flows of projects to be compared at different discount rates and viewing them graphically can discriminate.

© by David A. Wood

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Present Value Profile Trends Projects that look the most attractive at one discount value may not do so at another.

© by David A. Wood

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Discrete Investment Functions Interest earned on money in a deposit account is normally paid at set regular (discrete) intervals. The example below shows an investment of $10,000 accumulating with interest earned at 6% per annum. It grows discretely at the end of each annual investment period.

© by David A. Wood

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Discrete Versus Continuous Functions Production from an oil or gas well accumulates continuously by the minute and over a long period its cumulative production represents a continuous function (usually with breaks for well service). The example here shows a well producing at an initial rate of 10,000 bopd and declining exponentially at a rate of 20% per annum for 10 years.

© by David A. Wood

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Nominal Versus Continuous Compounding Nominal interest is the annual interest rate if money is compounded annually. If compounding is set at periods other than one year then the FV equation needs re-stating: – FV = PV [ 1 + (i / P)] n where P equals interest conversions per year and n equals the number of interest conversions for the total investment period and i equals nominal interest rate per year. – $2,000 compounded quarterly at 6% per year becomes $2,000 [1 +(0.06/4)]12 after three years = $2,391. Annual compounding equals $2,382. – For continuous compounding: FV = PV (e in) where n is the number of i interest periods. $2,000 after three years at 6% is: $ 2,000 (e 0.18) = $2,394.

© by David A. Wood

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Various Compounding Outcomes Common compounding methods are summarised in this table for an investment period of one year, but with formulae that work for multiple years. In the formulae shown “n” equals the number of years in the total investment period (n=1 in the examples shown for just one year) and “i “equals nominal interest rate per year:

© by David A. Wood

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Net Present Value (NPV): A Yardstick Useful for Ranking Projects (Exercise #2) You have the option to select one project for investment from projects X, Y and Z and the discount rate for all three projects is 10% per annum.



X costs $2million now and returns $3 million in 4 years.



Y costs $2million now and returns $4million in 6 years.



Z costs $3million now and returns $4.8 million in 5 years.

Calculate the NPV for each project, using the discount factor table provided. Then use the NPVs to rank the projects in order (best to worst) and select the best for investment.

© by David A. Wood

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Discount Factor Table In practice a spreadsheet, calculator or economic software package would calculate this for you.

© by David A. Wood

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Petroleum Economics Rates of Return David A. Wood

Rates of Return An earned interest on the money invested.



There are two quite distinct rates of return commonly used and referred to: – The accounting or book rate of return including return on net assets and return on capital employed (ROCE) or return on average capital employed (ROACE). – The internal or investor’s rate of return (IRR) and its modifications.

 

It is important not to confuse the two. Accountants, investors and financial analysts often refer to the former. It is the later that interests petroleum economists and investors when looking at project economics.

© by David A. Wood

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Book Rate of Return This is a single-year performance measure usually extracted from financial accounts.



Book ROR =



Profit/Year Investment

The average value for the total life of a multi-year project can however be approximated as: Book ROR = Profit Investment Ratio Number of Years



Such ratios are used for annual financial reporting purposes and corporate performance analysis and are not suitable for economic decisions concerning specific projects.

© by David A. Wood

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Investor’s Rate of Return (IRR) The rate which will discount the cumulative cash flow to zero, before or after taxes. Put another way it is the rate of return at which the PV of future returns equals the initial outlay.

   

“d” equals the IRR when:  Rn (1+d) -n = 0 where n is the number of years and R is the net cash flow in each year. For such a series of cash flows, a trial-and-error or iterative solution is required to obtain the IRR; there is no direct solution with more than two cash transactions. “d” is sometimes compared with a hurdle rate or minimum acceptable rate of return (MARR). If it exceeds that value the project is viable.

© by David A. Wood

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Investor’s Rate of Return: Appropriate Uses Although widely used as an investment yardstick it has significant problems.

Advantages:  Valid as a qualifying parameter.  Widely used within industry.  Does not depend on project magnitude. Disadvantages:  Assumes all monies can be & are reinvested at IRR.(but can be modified for a specific re-investment rate – MIRR)  Not valid as a ranking parameter.  May not yield a unique solution.  Gives no indication of project magnitude.

© by David A. Wood

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IRR and NPV Reflect Time-Value Influences Consider cash flows X and Y. The only difference is in the timing of the investment, but note the impact on both NPV and IRR.

© by David A. Wood

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IRR and Discount Rate Relationship NPV’s for a range of discount rates either side of the IRR.

© by David A. Wood

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Discounted Versus Undiscounted Cash Flows The undiscounted cash flow for each period is discounted back to its equivalent value at the start of period 1 by the discount rate and formula.

© by David A. Wood

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Investor’s Rate of Return Example For an interest hurdle rate of 6% project A requires an investment of $18,000 for a $20,000 return one year later while project B involves an initial outlay of $2,000 for a return of $2,500 one year later. Which project should be selected for investment?

 

IRRA = (20,000/18,000) - 1 = 0.11 = 11%. IRRB = (2,500/2,000) - 1 = 0.25 = 25%.

 

NPVA = -18,000 +(20,000/1.06) = $868. NPVB = -2,000 +(2,500/1.06) = $359.

 

IRR suggests B is better than A; NPV suggests A is better than B. More information than IRR in isolation is needed for a good decision. If there were 8 other projects like B then they would represent the best investment of $18,000.

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© by David A. Wood

Investor’s Rate of Return is an Indicative not a Definitive Yardstick IRR is not a good yardstick for discriminating between projects or justifying projects as this example shows.

IRR does not always give a unique solution. NPV is more realistic as it is calculated at a discount rate that is meaningful to the company concerned (e.g. its investment hurdle rate or cost of capital).

© by David A. Wood

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Investor’s Rate of Return Excel versus Interpolation Spreadsheets offer good IRR functions but it can be calculated by interpolation or graphically. Table below uses mid-year discounting.

Example of Investor's Rate of Return Calculation

Year 0 1 2 3 Totals

 

Present Present Present Net Cash Value Value Value Flow (PV10) (PV15) (PV20) -500 -500 -500 -500 400 381 373 365 100 87 81 76 100 79 71 63 100 47 25 5 21.29% IRR (Excel) 21.28% quick hand calculation

Present Value (PV25) -500 358 72 57 -13

[5 / (5+13)] * (25 -20) +20 = 21.28% Interpolation must not be over more than 10 percentage points.

© by David A. Wood

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IRR Does Not Always Provide a Single Solution There are two IRR points for this project. Both are mathematically correct – one ~ 5% the other ~29%. The shape of the graph shows that for discount rates between these two values the project is profitable.

© by David A. Wood

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IRR & MIRR (ERR): The Reinvestment Issue A calculated IRR is not actually earned unless positive cash flows from each period are reinvested at the IRR rate. Consider the following investment: Actual "i" Earned May Not Be the IRR Year 0 1 2 3 Totals

Net Cash Flow ($1,000) $680 $680 $680 $1,039

PV@: 38% ($1,000) $465 $318 $217 $0

MIRR – modified IRR function  incorporates a re‐investment  rate so overcomes this  shortcoming of IRR.

then FV= $2040 = $1000 * e 3i then Ln (2.040) / 3 = i = 23.8%

MIRR Excel function returns the  modified internal rate of return  for a series of periodic cash  flows. It considers both the cost  of the investment and the  interest received on  reinvestment of cash.

If $680 is taken out each year and re-invested at rates less than 38% then 24%< i 0 then a project is commercially viable on a risked basis. Values of zero indicate the minimum reserves threshold for a commercially viable risked project.

© by David A. Wood

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NPV and Reserves Risk Need to be Combined to Reveal Risked Values It is instructive to review the full probability distributions to understand the range of possible outcomes.

© by David A. Wood

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Risk Capacity Can Quickly Define the Minimum Reserve Threshold Cross plotting risk capacity and reserves risk against field size is a quick method of identifying the minimum reserves threshold, i.e. where the curves intersect is equivalent to the reserves size at EMV =0.

© by David A. Wood

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EMV:Risk-Reward Ratio Relationship: Both = 0 at Minimum Reserve Threshold

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© by David A. Wood

Risk-Reward Relationships are Influenced By Fiscal Terms Expected Value theory weights the value of a successful project with the chance of success and cost of failure with the chance of failure.

The discounted cash flow (Net Present Value – NPV) is the value of success. The risk capital expenditure on exploration measures the potential cost of failure – i.e. the dry hole cost.

© by David A. Wood

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Petroleum Economics Decision Analysis, Decision Trees & Flexibility David A. Wood

Decision Tree Nomenclature Decision trees are a means of diagramming a series of decisions, events, and outcomes to incorporate probabilities and EMVs.

  

They make analysis of a tortuous sequence of decision alternatives possible and presentable. They provide a permanent record of the analysis contributing to a decision as it existed, or was thought to exist, at the time of an original decision. Two node symbol convention is commonly used: –

Decision node, with actions taken (usually symbolised by a circle)

–

Event or chance node, with outcomes that occur (usually symbolised by a square)

© by David A. Wood

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Decision Tree Preparation: A Two-step Process Decision trees should be constructed systematically.

   

Step 1: Diagram and label the sequence of decisions, events, and outcomes with the associated probabilities of each event and outcome. Probabilities associated with one chance node should sum to 1.0 (i.e. the sum of all branches having the same origin equals 1). Step 2: Calculate expected monetary values and post them on the tree by working from right to left. It is necessary to calculate and post the EMV of each event node and leg.

© by David A. Wood

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Decision Trees: Step 1 A pictorial representation of a sequence of events and possible outcomes can help make complex decisions. The “event” node is sometimes referred to as the “chance” node.

© by David A. Wood

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Decision Trees: Step 2 EMV = (-2 * 0.7) + (2 * 0.15) + (15 * 0.1) + (75 * 0.05) = $4.2 mm

The EMV is placed by the event node and represents the risked value of everything to the right of it, i.e. the value of what would follow from the decision to drill. To maximise EMV decision here would be to drill. © by David A. Wood

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Petroleum Economics Monte Carlo Simulation Demonstration (Exercise#6) David A. Wood

Quantitative Approaches Require Probabilistic Models to Handle Uncertainty Models are required to process economic and risk data provided as probabilistic input distributions.

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Spreadsheets combined with simulation add-ins (e.g. Crystal Ball , @Risk ) or driven by self-built simulation and statistical analysis VBA macros, offer a powerful tool to aid this analysis.

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Having defined the range of the expected cost / value distributions of each event the simulation software transforms this into a distribution of selected type and then samples that distribution in a statistically valid way for a large number of model iterations or trials.

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In the oil & gas industry Monte Carlo simulation is widely used to model uncertainty & value for field / prospect reserves, economics, risks and portfolios as well as for cost, time, resource analysis in project planning.

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Simulation is also widely used in the financial sector to value financial instruments.

© by David A. Wood

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Simulation Example: Purchase of a Laptop & Software as Two Separate Items Market research of 30 sources suggests that the price of the laptop required can vary over a range of $700 to $1,700. A single average number does not adequately describe this range or the shape of the distribution, but it does provide the best estimate of price at $1,200

© by David A. Wood

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Simulation Example: The Two Separate Items May Have Quite Different Price Distributions Market research of 30 separate sources suggests that the price of the software required can vary over a range of $500 to $1,500. The distribution is asymmetrical with a positive skew resulting in mode (most frequent), median (P50) and mean having different values. Cumulative Probability is calculated for each value to provide a probability of the price being equal to or less than a certain value.

© by David A. Wood

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Analogy of Simulation Process With Selection of Lottery Balls Consider each of the 30 price samples for each item as the numbered balls inside two separate lottery barrels.

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The laptop lottery barrel would contain 1 $700 ball but 6 $1,200 balls, etc. The software lottery barrel would contain 1 $500 ball but 8 $700 balls.

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It is therefore 6 times more likely that a $1,200 ball will be drawn from the laptop lottery barrel than a $700 ball.

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A well constructed simulation model samples the distributions in a similar way, i.e. proportional to the frequency of occurrence. It uses cumulative probabilities to do this.

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For each trial it then adds the value on the two samples drawn from the “lottery barrels” or distributions to give the combined cost.

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The process then replaces all the balls and repeats the process for the number of iterations (trials) specified.

© by David A. Wood

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Considerations Based Upon the Two Cost Distributions Prior to running a simulation analysis the following points can be deduced:



Randomly buying the two articles in any store the chance of paying the lowest combined price of $1,200 or the highest combined price of $3,200 is much less than the chance of paying the combined average prices of the two distributions.



Cumulative probabilities are expressed on a scale of 0 (price is always greater than that) to 1 (price is always less than that). If a total number of 30 is used to calculate the cumulative probability the highest price will have a probability of 1

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Spreadsheet random number generators provide numbers randomly between 0 and 1 (but never actually those two numbers exactly). If the highest price has a probability of 1 it will never be sampled by a random number in such a sequence.



To overcome this a total of 31 is used to calculate the cumulative probabilities shown in the previous graphs.

© by David A. Wood

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Random Numbers are Selected to Represent Cumulative Probabilities This simple model uses VLOOKUP tables in Excel to extract values from the two price data sets based on two series of random numbers.

Other trials omitted….. space constraints ……

A random number is linked to a cumulative probability and the price associated with the next lowest cumulative probability in the tables adjacent to previous graphs is selected. The model then adds the two prices derived in each trial to provide a combined price.

© by David A. Wood

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Output Distribution From Monte Carlo Simulation Model The output or forecast distribution is uneven (and in this case bimodal) with gaps because limited number of trials make it statistically inadequate with results strongly influenced by chance. Most sets of 50 trials show a single mode, but some are more uneven than others. Many more trials are required to generate a statistically smooth output distribution. Expressing this as a cumulative probability distribution provides information on the chance of not paying more than a specific combined price. What if the two price distributions are correlated?

© by David A. Wood

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Advantages of Monte Carlo Simulation The main purposes of a simulation study are to generate a statistically valid probability distribution(s) for the objective function(s) and to provide greater understanding of the relationship between the input metrics and the objective functions. Advantages of Simulation are:  Mathematics is relatively straightforward and widely used, forming the heart of diverse aspects of financial analysis (e.g. pricing options, corporate portfolio models etc.).



Spreadsheet functions & VBA code are mostly sufficient.

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Distributions encapsulate both optimistic and pessimistic estimates and limit potential for forecasts being unduly biased in either direction. Bias is a problem with single point estimates.

   

More trials can be run in seconds to improve statistics.

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People accept the technique and believe the results (sometimes too readily!!).

Models can usually be updated easily. Correlations and complex dependencies can be incorporated. The effort of using a model once established is low.

© by David A. Wood

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Monte Carlo Simulation Technique – Step by Step For Cash flow Analysis (1) A number of different input distributions are combined to calculate reserves and prospect expected monetary values (EMVs) for a number of trials.

© by David A. Wood

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Monte Carlo Simulation Technique – Step by Step For Cash flow Analysis (2) A number of different distributions are combined to calculate prospect NPV’s & EMV’s by the Monte-Carlo technique.

David Wood has published details of simulation applications in the Oil & Gas Journal (e.g. OGJ 1 Nov, 1999; 23 Oct 2000 plus executive reports).

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© by David A. Wood

@risk 12

Caution Required For Monte Carlo Simulation Model Structure & Interpretation Frequency distributions generated by computer can be very believable despite being based in some cases on meaningless input distributions.

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The computed frequency distributions for in-place hydrocarbons commonly produced by simulation are only as good as the quality of the frequency distributions assigned to the input variables.

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It is important to identify those variables which are dependent upon (or correlated with) other variables and treat them as functions of those independent variables.



A geological example of dependent variables are porosity and water saturation that are inversely correlated in many cases. Capital costs and operating costs are positively correlated in some oil and gas projects (i.e. as one increases so does the other).



If porosity and water saturation are treated as independent then random numbers will associate an unrealistic water saturation with a porosity in individual iterations of the simulation.

© by David A. Wood

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Mechanics of Monte Carlo Simulation Cumulative frequency distributions, random numbers and a large number of iterations means many numbers to crunch and analyse.



A Monte Carlo simulation requires that the uncertain variables be defined as either discrete or continuous frequency (probability) functions.



Numerous passes through the entire calculation are made. For each calculation the value assigned to each variable is determined by a random number sampling the variable distribution.



A different random number is applied to each variable for each pass or iteration of the model.

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In this way, each value utilized for each variable occurs according to its prescribed frequency function for the distribution type selected.

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The result is a frequency distribution of the calculated metric.

© by David A. Wood

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Random Sampling of Independent Variables For independent variables it is important that the random numbers selected to sample each variable are random and distributed in accordance with the selected distribution to approximate each variable. Random sampling of two uniform distributions crossplotted should appear similar to the adjacent diagram. Increasing the number of sample trials should result in filling the gaps and not increasing the clusters. Different mathematical routines are available to smooth sample point spread, but these are beyond the accuracy of the method for most oil and gas problems.

© by David A. Wood

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Statistical Stability & Significance of Simulations Sufficient simulation passes should be made so that the standard deviation of the calculated distribution is no longer changing significantly. Another rule to follow is to run a simulation until the standard error of the mean (i.e. standard deviation / √ number of trials in the simulation) is less than 1% of the mean.

© by David A. Wood

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Decision Trees and Simulation A Monte Carlo simulation derives a distribution which represents a large number of possible outcomes rather than a few discrete outcomes of a simple decision tree.

© by David A. Wood

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Exercise #6: Monte Carlo “Simulation”: Two Variable / 10 Trial Problem To illustrate the technique a simplistic calculation is required in this exercise using just two variables defined as discrete distributions.

© by David A. Wood

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Example of Monte Carlo “Simulation” Perform the 10 Trials (Exercise #6) Net cash flow is calculated for each of ten iterations (trials) by multiplying the $/barrel selected value by the reserves selected value. But firstly fill in the blanks for the two variable columns.

© by David A. Wood

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Simulation Exercise #6 Sequence of analysis: 1.

Select values for each trial

2.

Use rules established in first table

3.

Calculate net cash flow for each trial

4.

Work out the mean of the net cash flow distribution

5.

Arrange the results into a cumulative frequency distribution

© by David A. Wood

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