Techniques for Quantitative Prospect Evaluation

A master-class by Steven Bloemendaal.

Course length:       3 days

Location: this course is given as an in-house class at your preferred location

The course has a modular design which allow for customization to your needs. The course is aimed at experienced technical professionals with 5-20 year of oil industry experience and who want to refresh and deepen their knowledge of quantitative prospect evaluation techniques. Students should have a basic knowledge of prospect evaluation and statistics. 

At this moment the course is only given as an in-house class at your company. To request information please contact Bloemendaal@GoExplore.consulting.

Training quantitative prospect evaluation

Software

During the course we will make use of the Free GoExplore Software Suite, and Freeware Suites, which you can Download Here.

Course Modules

1) Analyzing a Prospect

This module consists of an exercise where an existing prospect assessment is analyzed from its existing documentation. This analysis leads to a better understanding of what is needed for a quality prospect assessment and its documentation. 

2) Prospect Volumetric Methods

  • The Volumetric Equations

  • Probabilistic Volume Calculation

  • Gross Rock Volume Estimation

  • Column Length Estimation

  • Rock and Fluid Properties Estimation

3) Prospect Risking Methods

  • Risk and Uncertainty

  • Uncertainty, Aleatory versus Epistemic

  • Probability, Frequentist versus Bayesians

  • Estimating Probabilities

4) Prospect Volume Reporting and Cutoffs

  • Reading MonteCarlo Output

  • Commercial Cutoffs

  • Reporting Prospect Volume and Risk

5) MonteCarlo Modules and Volume Calculators

  • Accuracy and Precision

  • Central Limit Theorem

  • The Log-Normal Distribution

  • Limitations of MonteCarlo Models

  • Volume Calculators

6) Distributions and Estimating Techniques

  • Probability Density Functions and Cumulative Distributions

  • Data versus Uncertainty Distributions

  • Estimating Techniques

  • Cognitive Bias

7) Conditional Probabilities and Bayesian Analysis

  • Eight Exercises

  • Methods of Risk Modification

8) Scenario and Multiple Hypothesis Analysis

  • Subsurface Scenarios

  • Scenarios Workflows

  • Assigning Probabilities to Scenarios

9) Multiple Objective Workflows

  • Methods to deal with multiple objectives

  • Dependencies (Association (between Risk and Correlation (between Volumes)

10) Evaluation Pitfalls