COURSE OVERVIEW:

This course provides a comprehensive introduction to the principles and applications of geostatistics in reservoir characterization. Geostatistics is a critical discipline for integrating geological, petrophysical, and engineering data to generate robust reservoir models that support field development decisions. Participants will learn how spatial variability is quantified, how variograms are constructed and interpreted, and how stochastic simulation techniques are applied to model heterogeneity in subsurface reservoirs.

Key topics include data analysis, probability distributions, kriging methods, uncertainty quantification, and building geostatistical models used for static and dynamic reservoir simulations. The course also explores how geostatistical outputs influence drilling decisions, well placement, reserves estimation, and reservoir performance forecasting. Real-world examples and case studies demonstrate the practical application of geostatistical methods to various reservoir types, including sandstone and carbonate systems. By the end of the course, participants will be able to confidently apply geostatistical techniques for improved reservoir understanding and decision making.

COURSE OBJECTIVES:

After completion of the course, the participants will be able to:

• Understand the fundamental concepts and terminology of geostatistics.
• Analyze reservoir data distributions and perform exploratory data analysis.
• Construct and interpret experimental variograms for reservoir properties.
• Evaluate spatial continuity and heterogeneity within the reservoir.
• Apply kriging methods for property estimation and interpolation.
• Differentiate between deterministic and stochastic modeling approaches.
• Generate stochastic realizations for reservoir properties using simulation methods.
• Integrate geological concepts with geostatistical modeling workflows.
• Assess uncertainty and quantify its impact on reservoir predictions.
• Build geostatistical models for porosity, permeability, and facies.
• Understand how geostatistical models feed into reservoir simulation.
• Interpret model results for field development planning and well placement.
• Identify limitations, risks, and data quality issues in geostatistical studies.
• Apply best practices in reservoir characterization using multi-source data.

TARGET AUDIENCE:

• Reservoir engineers
• Geoscientists and geologists involved in subsurface characterization
• Petrophysicists working with core and log data
• Simulation engineers using geostatistical models as inputs
• Field development planners and asset evaluation teams
• Technical staff involved in reservoir modeling and uncertainty analysis

TRAINING COURSE METHODOLOGY:

A highly interactive combination of lectures, discussion sessions, and case studies will be employed to maximise the transfer of information, knowledge, and experience. The course will be intensive, practical, and highly interactive. The sessions will start by raising the most relevant questions and motivating everybody to find the right answers. The attendants will also be encouraged to raise more of their questions and to share in developing the right answers using their analysis and experience. There will also be some indoor experiential activities to enhance the learning experience. Course material will be provided in PowerPoint, with necessary animations, learning videos, and general discussions.

The course participants shall be evaluated before, during, and at the end of the course.

COURSE CERTIFICATE:

National Consultant Centre for Training LLC (NCC) will issue an Attendance Certificate to all participants completing a minimum of 80 percent of the total attendance time requirement.