Michael provides a number of customized courses for the oil and gas sector. The sector faces a number of modelling challenges, such as creation of models with flexible time axis (e.g. to be able to shift the first oil date), the use of optimisation tools (e.g. when is the best first oil date, given financing constraints for the development phase?, or: what is the optimal level of participation in a project?), and the need to quickly add or delete data sets (e.g. so that the effect of new fields or assets sales can easily be accounted for). To effectively deal with such issues in an efficient way requires a good level of modelling and Excel/VBA knowledge.

In addition, the sector naturally faces the challenge of how to account for risk, and the associated questions of optimisation within a risky context (e.g. if we need five exploration successes in the next two years to meet our medium term business plan, then how many projects do we need to start? … what about to meet the plan with 70% versus 90% confidence …? What are the implications for human and other resources … size of teams etc.?). Questions of general uncertainty are also of importance when authorising business cases (e.g. volumetric uncertainty, value of information/testing etc.).

Courses in this area are usually highly customized, because the potential range of topics to be covered (Excel, VBA, decision-making, trees, simulation, risk, optimisation) is large. Courses can be held over the internet or in-house at any location globally.

In addition to in-house customised courses, Michael is offering a specially-designed public course that will cover many of these issues. The course will be held on May 22nd-25th in Hammersmith, London. The price is £2900+VAT for all four days, with lunch and refreshments included. Participants may choose also to attend only Days 1-2 or Day 3-4, each at a price of £1650+VAT. Participants from the same company are entitled to discounts (30% for second participant, 50% for third and subsequent participants). Contact us to find out more.

Overview of Public Course, May 22nd-25th, Hammersmith, London

This is an interactive and hands-on course aimed at developing participants’ skills in implementing a wide range of financial and economic modelling applications that are found in the oil and gas and related sectors, including risk and decision analysis. Key themes include: best practices in designing and structuring models, sensitivity and scenario analysis, tools to create highly flexible models (such as moving cash flows in time), risk-, uncertainty-, and simulation modelling, optimisation, real options and value-of-information analysis. As well as a range of advanced Excel techniques, participants learn core elements of VBA and the use of some Excel add-ins for simulation modelling, decision trees, and optimisation.

Days 1-2: Modelling of O&G Applications using Excel and VBA

  • Objectives and types of models; the modelling process
  • Excel as a modelling platform; benefits and limitations
  • Key best practices in Excel modelling
  • Review of core Excel functions
  • Model auditing and short-cuts (introduction and key points)
  • Tools for sensitivity analysis and optimisation
  • Introduction to statistical analysis and database manipulation and analysis (filtering, dynamic sorting, database functions, database queries, intro. to array functions etc.)
  • Hands-on exercises, with applications to business planning and forecasting, tax calculations, production sharing agreements, cash flow valuation, project finance modelling
  • Flexible and efficient modelling using Lookup, Date, Text, Information and other functions
  • Hands-on exercises in data manipulation, creating flexible start dates in models, and database approaches to modelling (e.g. highly flexible business plans, allowing rapid input or deletion of new assets or data etc.), scenario analysis, variance analysis, manipulating and cleaning data (e.g. downloads of oil prices, dates, multi-currency databases, matching and reversing data, and combining databases together, splitting text and numerical fields using functions, to create databases from underlying dataset)
  • Introduction to VBA for O&G modelling applications
  • Hands-on exercises with VBA e.g. automation of repetitive actions, such as database consolidation, division of time series from quarterly to monthly, running multiple database queries

Days 3-4: Risk and Uncertainty Modelling

  • Core concepts in risk and simulation modelling
    • Applications of risk modelling in business, finance, and oil and gas (overview)
    • Benefits of risk modelling
    • The role of distributions in risk models
    • The use of distributions; key terms and concepts
    • Importance of non-symmetry and its sources in real-life processes
    • Key distributions for risk modelling (Triangular, PERT, Normal, Lognormal, Binomial, etc.)
    • Standard and alternate parameters
  • Introduction to simulation @RISK® and hands-on exercise in cost budgeting
    • Key icons, sources of help
    • Running a simulation and results interpretation e.g.
      • Density and cumulative curves
      • Tornado graphs and scatter plots
    • Using Statistics functions for model outputs
    • Saving files, repeating a simulation and related aspects (incl. sampling methods, no. of iterations, convergence testing etc.)
  • Modelling discovery risk
  • Hands-on exercise: Volumetric uncertainty
  • Introduction to the LogNormal distribution
  • Distribution fitting (overview)
  • Hands-on exercises:
    • Reserves aggregation modelling (portfolio P10s etc)
    • Event risk modelling
    • Distribution of successes for a given portfolio
    • Number of projects required to first discovery (and time to occurrence)
    • Integration with volumetric uncertainty modelling per prospect
  • Overview of distributions relating to time-to-occurrence processes
  • Introduction to dependency modelling
  • Hands-on exercise: Discovery probabilities contingent on earlier success
  • Hands-on exercise: Dependencies in volumetric estimation
  • Hands-on exercise: Correlation modelling in reserves aggregation
  • Hands-on exercise: Multiple simulations
    • Comparison of the effect of correlation and other dependency relationships
    • For risk mitigation analysis
  • Hands-on exercise: The Discrete distribution
    • Scenario generation
    • Selecting scenarios for uncertain production profiles
    • Comparison with multiple simulations
    • Derivation of Swanson’s rule (time permitting)
    • (Time permitting) Further software topics and modelling examples/demos
    • Other @RISK® software features
      • Integrating @RISK® into existing models (RiskStatic, function swap)
      • Excel reports, working with simulation data, working with graphs etc.
    • Applications
      • Production decline modelling (overview and discussion)
      • Drill program timing and resources: uncertainty and optimisation
      • Cash flow models
      • Modelling profit share agreements and fiscal systems; optimisation aspects of these
      • Mapping volume to non-linear cost curves
      • Time-series modelling (crashes, mean-reversion, Markov chains, correlated series)
      • Integrated economics (uncertainty in reserves, production, costs and operations)
      • Valuing flexibility and real options
      • Schedule risk analysis
      • Modelling portfolio effects e.g. reserves aggregation, or sizing and optimisation of E&A portfolios
      • Modelling other dependencies e.g. between porosity and oil saturation
  • An Introduction to Decision Trees, and to Optimisation
    • Role and benefits of using decision trees
    • Implicit assumptions and limitations of trees
    • Introduction to modelling with PrecisionTree® (cumulative pay-off trees)
    • Hands-on exercises:
      • Product development example
      • Introduction to Bayesian analysis and the value of information
      • Seismic test decision
    • Other software features
      • Decision Analysis and Sensitivity Analysis menus
      • Reference trees
  • Introduction to Solver, Evolver or other optimisation tools
  • Hands-on exercise: optimising the launch dates of projects in a portfolio