Uncertainty Analysis & Geostatistics in Reservoir Modeling Training

Overview

🎯 Course Description:

This uncertainty analysis and geostatistics in reservoir modeling course provides participants with both fundamentals and hands-on applications. The program emphasizes how geoscientists can apply uncertainty analysis and geostatistics in reservoir modeling to quantify variability, build realistic property models, and support better exploration and development decisions.

👥 Who Should Attend:

Reservoir engineers and geologists
Geomodellers and petrophysicists
Exploration & development geoscientists
Subsurface team leaders and project managers
Technical staff involved in field development planning
Professionals working in uncertainty quantification

🧾 Training Format:

Duration: 5 Days (In-person or Online, Instructor-led)
Methodology: Lectures, hands-on modeling sessions, group discussions
Materials: Course slides, modeling workflows, sample datasets
Software: Demo sessions may use Petrel, RMS, or open-source geostat packages (e.g., SGeMS)

🗓️ 5-Day Detailed Agenda

Day 1: Fundamentals of Uncertainty in Subsurface Modeling

Time	Topic
09:00 – 09:30	Course Introduction & Objectives
09:30 – 10:30	Types and Sources of Uncertainty in Reservoir Models
10:30 – 10:45	☕ Coffee Break
10:45 – 12:15	Geological vs. Petrophysical vs. Dynamic Uncertainty
12:15 – 13:15	🍽️ Lunch
13:15 – 14:45	Introduction to Probabilistic Thinking
14:45 – 15:00	☕ Coffee Break
15:00 – 16:30	Case Studies: Uncertainty Impact in Development Decisions

Day 2: Introduction to Geostatistics

Time	Topic
09:00 – 10:30	Spatial Continuity and Random Variables in 3D Space
10:30 – 10:45	☕ Coffee Break
10:45 – 12:15	Exploratory Data Analysis (EDA): Histograms, Trends
12:15 – 13:15	🍽️ Lunch
13:15 – 14:45	Variogram Theory and Modeling
14:45 – 15:00	☕ Coffee Break
15:00 – 16:30	Practical Variogram Calculation and Fitting

Day 3: Geostatistical Modeling Techniques

Time	Topic
09:00 – 10:30	Deterministic vs. Stochastic Models
10:30 – 10:45	☕ Coffee Break
10:45 – 12:15	Kriging, Co-Kriging and Sequential Gaussian Simulation
12:15 – 13:15	🍽️ Lunch
13:15 – 14:45	Simulation of Lithofacies and Petrophysical Properties
14:45 – 15:00	☕ Coffee Break
15:00 – 16:30	Hands-on Exercise: Simulating Porosity and Permeability

Day 4: Uncertainty Propagation and Scenario Generation

Time	Topic
09:00 – 10:30	Uncertainty Propagation through the Static Model
10:30 – 10:45	☕ Coffee Break
10:45 – 12:15	Scenario-Based Modeling: Low, Mid, High Cases
12:15 – 13:15	🍽️ Lunch
13:15 – 14:45	Using Probabilistic Grids in Reservoir Simulation
14:45 – 15:00	☕ Coffee Break
15:00 – 16:30	Hands-on: Generating Multiple Realizations

Day 5: Decision Making Under Uncertainty & Integration

Time	Topic
09:00 – 10:30	Risk-Based Decision Making and Monte Carlo Methods
10:30 – 10:45	☕ Coffee Break
10:45 – 12:15	Integrating Geological, Petrophysical & Production Data
12:15 – 13:15	🍽️ Lunch
13:15 – 14:45	Group Project: Build and Present Uncertainty Scenarios
14:45 – 15:00	☕ Coffee Break
15:00 – 16:30	Final Review, Q&A, Certificates and Course Feedback

Target audiences

Reservoir Engineers, Geologists

Uncertainty Analysis & Geostatistics in Reservoir Modeling Training

$ 5,750

Course Features

Lecture 0
Quiz 0
Duration 5 days
Skill level All levels
Language English
Students 40
Assessments Yes

Uncertainties & Geostatistics in Reservoir Modeling Workshop

Overview

🎯 Course Description:

👥 Who Should Attend:

🧾 Training Format:

🗓️ 5-Day Detailed Agenda

Day 1: Fundamentals of Uncertainty in Subsurface Modeling

Day 2: Introduction to Geostatistics

Day 3: Geostatistical Modeling Techniques

Day 4: Uncertainty Propagation and Scenario Generation

Day 5: Decision Making Under Uncertainty & Integration

Target audiences

Course Features

TRAINING SOLUTIONS

QUICK LINKS

Uncertainties & Geostatistics in Reservoir Modeling Workshop

Overview

🎯 Course Description:

👥 Who Should Attend:

🧾 Training Format:

🗓️ 5-Day Detailed Agenda

Day 1: Fundamentals of Uncertainty in Subsurface Modeling

Day 2: Introduction to Geostatistics

Day 3: Geostatistical Modeling Techniques

Day 4: Uncertainty Propagation and Scenario Generation

Day 5: Decision Making Under Uncertainty & Integration

Target audiences

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Course Features

TRAINING SOLUTIONS

QUICK LINKS

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