Training | Data analysis, mapping and subsurface property modeling with geostatistics

Learning outcomes

• Enhanced data insight: Develop a deep understanding of your data through advanced geostatistical analysis, leading to more informed decision-making.
• Improved mapping quality: Learn to create high-quality maps by integrating various data types, ensuring comprehensive spatial representations.
• Uncertainty quantification: Master techniques to quantify uncertainties in your models, providing a clear assessment of confidence levels in your results.
• Technique selection: Understand the assumptions underlying different geostatistical methods to select the most suitable approach for your data

Who should attend

• Geoscientists and reservoir engineers involved in geomodeling and reservoir characterization and looking for a practical, synthetic, and pragmatic introduction to geostatistical methods for reservoir characterization.
• Environmental consultants and engineers aiming to enhance data analysis and mapping capabilities.
• Academics and researchers.
• Agricultural engineers, air quality specialists, climatologists, epidemiologists, foresters, geotechnical engineers, soil scientists, and others interested in spatial data analysis.

Prerequisites

No prior knowledge of geostatistics is required; however, a basic understanding of elementary statistics is recommended to facilitate comprehension of course material.