Oil and Gas Financial Modelling – A Practical Approach

Financial Management Skills, Financial Modelling and Forecasting

Introduction

Many senior and middle managers do not utilise Excel to its maximum potential. Instead, they use it as they would a calculator. If you fall into this category then this course is for you. Having completed this training course, you will have the requisite tools to utilise Excel to its fullest and be better equipped to challenge decisions. In addition, if you work in the upstream or downstream and your career progression is being restricted by outdated knowledge of modelling techniques then this course will help you move your career forward.

Highlights of this training course include: 

• A course which takes delegates from Excel basics to the most advanced use of Excel
• Real world approach to the discipline
• Numerous examples based around the Oil and Gas industry
• Dual approach that not only develops modelling skills but also financial management skills

Objectives

This training seminar provides delegates with the tools required to find better answers to questions such as:

• How to improve the quality of the quantitative analysis of my corporate presentations?
• How to apply financial modelling in the Oil and Gas industry?
• How to model investment appraisal techniques and how to assess the appropriate discount rate?

Training Methodology

Each of the sessions will involve formal lectures, demonstration of modelling techniques and the opportunity for practical application. Screen recordings of important techniques and examples will be made available to delegates to assist in the practical applications and to facilitate application of the techniques used when they approach to the workplace.

Organizational Impact

The delegates on this training course will benefit by:

• Providing your staff with the opportunities to develop high level financial management techniques appropriate to the Oil and Gas industry
• Updating their quantitative techniques to enable them to make better informed decisions
• Transforming their Excel skills so that they leave with advanced knowledge of Excel for financial modelling

Personal Impact

By attending this course you will:

• Have advanced ability in financial modelling using Excel
• Have a larger skills set when contributing to corporate decisions
• Have the ability to question important decisions formed using financial modelling

Who Should Attend?

• Decision makers and financial modelers in the up-stream and down-stream Oil and Gas industry
• High level managers integral to the decision making process who wish to develop their financial modeling skills

Seminar Outline

DAY 1

An Introduction to the Excel Environment, with Oil and Gas based Examples

• A quick-start tutorial for Excel
• Describing data sets using statistics
• Representing data sets graphically
• Understanding the concept of normal distribution
• Trend analysis using Excel
• Time series analysis
• Mini-Case studies

DAY 2 

Statistical Analysis (Applied to the Oil and Gas Industry) Using Excel

• Use of Excel functions for statistical analysis
• Descriptive statistics
• Mean, Median, Standard deviation, Skewness and Kurtosis
• Use of scatter diagrams, frequency and Histogram distribution
• Regression techniques to calculate cost of equity financing
• Analysis of equity returns of Oil and Gas industry companies
• Mini-Case studies

DAY 3

Investment Appraisal Using Excel

• Investment appraisal using NPV, IRR and payback as applied to the Oil and Gas industry
• Use of Excel functions for investment appraisal: IRR, PV and NPV
• Modified Internal Rate of Return (MIRR)
• Use of scenario analysis and stress testing
• Predicting financial distress
• Mini-Case studies

DAY 4

Financial Analysis in the Up and Down Stream Oil and Gas Industry

• Introduction to financial statements
• Ratio analysis applied to the Oil and Gas Industry
• Ratios as a system – pyramids of ratios
• Financial modelling
• Cash flow forecasts using Excel
• Mini-Case studies

DAY 5

Oil Product Spreads

• Examining the relationship between energy products
• Differences between data sets
• Correlation analysis
• Confidence intervals
• Analysis Of Variance (ANOVA)
• Mini-Case studies