As the subsurface teams comprise of multitude of people and disciplines which are focused on managing production from the field and getting more oil and gas from the field itself, managing the team is extremely difficult task that falls on the shoulders of Subsurface Managers.
This task is additionally complicated with the uncertainties and risks associated with the geology, petro physics and economic issues. This training course is designed to help subsurface managers tackle the risks and uncertainties related primarily to geoscience, and it will also cover the wider area, as the subsurface team consists of: Production geologist, Geophysicist, Petrophysicist, Reservoir engineer, Production engineer, Production chemist, Well Engineer and Economist. Therefore, the full understanding of risk and uncertainties related to these fields will be taken into consideration and presented for the Subsurface Managers to be able to communicate with the members of their teams and find the optimal compromise between them.
This training course will highlight:
- 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 training course, participants will be able 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
DAY 1
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 2
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 3
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 4
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 5
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
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