• Uncertainties and risks associated with the oil and gas field development,
• Geostatistics and Quantification of Uncertainty and Risk Qualified Decision Making 
• Issues and optimization of subsurface data management and Life-cycle uncertainty management
• Analytical interpretation of centrifuge data to determine the relative permeability curve
• Construction of Q-Q plots, semi variograms, kriging, and uncertainty modelling

By the end of this RECTUS training course, participants will learn to:

• Identify uncertainties and risks associated with E&P lifecycle
• Use statistical tools to make adequate decisions under uncertainty
• Learn which modelling techniques are used for different reservoir types
• Perform data analysis trough inference, identifying outliers, declustering and trend analysis
• Perform Monte-Carlo simulation to determine oil and gas reserves

This training course is designed for all professionals working in the field of data analysis, oil and gas exploration, geology and reservoir modelling. But the main focus is on Subsurface Managers or the people trying to become Surface Managers and effectively manage Subsurface Teams.

This training course is suitable to a wide range of professionals but will greatly benefit: 

• Subsurface Managers
• Production geologists
• Geophysicists
• Petrophysicists
• Reservoir engineers
• Production engineers
• Production chemists
• Well Engineers
• Economists

Participants to this training course will receive a thorough training on the subjects covered by the seminar outline with the Tutor utilising a variety of proven adult learning teaching and facilitation techniques. Seminar methodology includes presentation of theoretical concepts, video lectures, example case studies and many exercises that will be done through the guided work of the delegates themselves.

Day One: Statistical Analysis and Probability Theory 

• Describing Data with Numbers
• Probability and Displaying Data with Graphs
• Random Variables, Probability Density Function (pdf)
• Expectation and Variance
• Bivariate Data Analysis
• Sample case: preparing a well log plot and identifying correlation

Day Two: Descriptive Geostatistics 

• Geologic constraints
• Univariate distribution and Multi-variate distribution
• Gaussian random variables
• Random processes in function spaces
• Geostatistical Mapping Concepts
• Structural Modeling
• Cell Based Facies Modeling
• Sample case: Analytical interpretation of centrifuge data to determine the relative permeability curve

Day Three: Modeling Uncertainty 

• Sources of Uncertainty
• Deterministic Modeling
• Models of Uncertainty
• Model and Data Relationship
• Model Verification and Model Complexity
• Sample case: Reservoir Modeling
• Creating Data Sets Using Models
• Parameterization of Sub grid Variability

Day Four: Quantifying Uncertainty 

• Introduction to Monte Carlo methods
• Sampling based on experimental design
• Gaussian simulation
• General sampling algorithms
• Simulation methods based on minimization
• Sample case: Monte Carlo method for determining oil and gas reserves
• Sample case: Multiwell systems calculation using Darcy’s law

Day Five: Visualizing Uncertainty 

• Distance Methods for Modeling Response Uncertainty
• K-means clustering
• Estimation using simple kriging
• Petrophysical Property Simulation
• Sample case: Oil reservoir uncertainty visualization
• Value of Information and the cost of data gathering

RECTUS attendance certificate will be issued to all attendees completing minimum of 80% of the total course duration