Crystal Ball Industry Examples


Oil & Gas Applications


Oil & Gas exploration deals with many unknowns, with high risk and uncertainty an inherent part of the oil and gas industry. The management of risk in oil and gas exploration has always been difficult.


Oil & Gas ApplicationsToday, Crystal Ball is the tool chosen by Australian oil and gas companies to analyse risk and make more informed, lucrative decisions.
Crystal Ball is a Microsoft Excel-based suite of analytical tools that includes Monte Carlo simulation, optimisation and forecasting.
With little effort, you can apply these advanced analytical techniques to your upstream or downstream spreadsheets to create more accurate reserve forecasts and financial and operational predictions.
In Australia companies such as Woodside, BP, Shell, Santos, BHP Billiton Petroleum and Nexus Energy use Crystal Ball to add insight when performing probabilistic reserves analysis, planning capital projects, preparing drilling AFE's, evaluating exploration opportunities, as well as estimating reserves and predicting petrochemical prices.


"The use of Monte Carlo simulation tools in the petroleum industry is now common among the more sophisticated hydrocarbon exploration and production organisations. Nexus Energy has been using Crystal Ball for probabilistic assesment of its prospect inventory, resource and reserves volumes since the company started. We enjoy unobtrusive and efficient support for Crystal Ball from Hearne Scientific Software, and look forward to continuing the relationship in the future." - Graham Bunn, Chief Petroleum Engineer, Nexus Energy Ltd. (ASX: NXS)


In April 2003, Nexus Energy Ltd gained its first exploration permit in the offshore Gippsland Basin. Since then the Company's acreage holding has grown significantly to nine permits within four offshore basins around Australia.


Key features of interest to the oil and gas industry include sensitivity and tornado analysis, correlation, historical data fitting and optimisation.

  • The sensitivity analysis and tornado analysis are two separate methods that help you to understand which of the uncertain inputs (e.g., the recovery factor or the price of oil) drive the uncertainty in your models.
  • Correlation lets you link uncertain inputs and account for their positive or negative dependencies.
  • If historical data does exist, the data fitting feature will compare the data to the distribution algorithms and calculate the best possible fit and parameters for your data.
  • Optimisation helps determine optimal decision choices to maximise or minimise your goals (e.g., maximise the return on a portfolio of assets, optimal number of well to drill), and efficient frontier runs multiple optimisations to determine the best balance of risk and reward for a particular problem or portfolio.

Crystal Ball Case Studies

BP uses Monte Carlo Analysis as a Risk Management Tool

Many managers understand that probabilistic methods can give more reliable project time and cost estimates than deterministic alternatives. Fewer realise that by highlighting the key drivers of success, such methods can add extra value and enable a proactive approach to risk.

A 1 hour presentation by Hugh Williamson, BP's global specialist on well cost estimation and risk management, is available online. view presentation>>

Portfolio Optimisation applied to Acquisition Evaluation

This paper describes some of the lessons learnt in building a portfolio model of petroleum assets. The example is based on the evaluation of an acquisition opportunity, a setting which imposed its own constraints on the methodology. View PDF report>>

An Application of Portfolio optimisation with Risk Assessment to Exploration & Production Projects

This paper presents an application of portfolio optimisation with risk assessment to exploration & production projects. The study aims to maximise the worth of the company while accounting, investigating and analysing the inherent uncertainties and requirements of the petroleum industry. View PDF report>>

Other applications of Crystal Ball in the Oil and Gas industry

The following examples were provided by customers and represent only some of the potential oil & gas and energy applications for Crystal Ball.

  • Analysis of productive properties for acquisition

  • Analysis of trading issues and of wide variations in project to project costs

  • Analyse new ventures

  • Assess the probability of drilling a successful well

  • Cash flow forecasting and interest rate analysis

  • Cost estimation for chemical consumption with associated risks

  • Determine lifecycle of current capital investments

  • Determining optimum replacement rates for offshore equipment

  • Developing pricing views for marketing gas at all major trading hubs across North America

  • Economic evaluation of oil and gas exploration prospects and exploration portfolios

  • Economical optimisation for investment and replacement questions in Electricity and Gas distribution networks

  • Error analysis of petrophysical evaluations

  • Estimate the possible reserve sizes of unproved oil and gas prospects prior to drilling

  • Evaluating the inherent risk in achieving financial targets for acquisitions

  • Figuring commercial terms for service offerings

  • Forecast liquidity availability

  • Generating stochastic oil and gas volumetric reserves estimates

  • Geologic estimations of oil in place and risk analysis

  • Give my clients cost and schedule risk profiles

  • Improve the accuracy of cost estimates of single well exploration

  • Model utilisation trends

  • Predict petrochemical prices, supply/demand volumes, imports, exports, operating rates for plants

  • Optimising employee incentive programs

  • Portfolio optimisation

  • Preparation of project budgets

  • Reserves determination

  • Risk Analysis on Petroleum exploration and Development Projects

  • Risk and sensitivity on proposed capital projects

  • Risk-based analysis of major project capital expenditures in the oil sands industry

  • Risk-based analysis of oil and gas exploration and development opportunities

  • Sales and market clearing price forecasting

  • Tech portfolio management and asset allocation

  • Use CB Predictor to analyse historical trends in production costs