HR-240 Seismic LithoSI Workshop

Audience

Geophysicists, geologists, engineers and technical staff who want to understand the theory and learn how to apply these increasingly critical techniques.

Content

This course covers the theory and practical use of LithoSI, an interactive program that is fully linked within HampsonRussell software and is used to analyze combinations of inversion results (typical pre-stack inversion results) to describe classes or lithologies. The outputs are litho-probability cubes, transforming inversion results into geological properties.

Learning Objectives

  • Discussion of the LithoSI workflow for facies and fluid classification using multiple elastic parameters from the inversion of the seismic data
  • Basic introduction to Bayesian classification, multivariate Probability Density Functions (PDFs) and their optimization through Kernel Density Estimation
  • Teaches how to design complex multi-variate probability distribution functions to ensure proper classification of lithologies and accurate definition of litho-probabilities
  • Shows how to understand the quantification of uncertainty in seismic lithology and fluid prediction
  • Practical Exercises: Defining litho-classes, selecting attributes, optimizing PDFs, validating the results and volume application

Duration

1-day

Prerequisites

None

Software Covered

LithoSI

Course Format

Workshop

Audience

Geophysicists, geologists, engineers and technical staff who want to understand the theory and learn how to apply these increasingly critical techniques.

Content

This course covers the theory and practical use of LithoSI, an interactive program that is fully linked within HampsonRussell software and is used to analyze combinations of inversion results (typical pre-stack inversion results) to describe classes or lithologies. The outputs are litho-probability cubes, transforming inversion results into geological properties.

Learning Objectives

Discussion of the LithoSI workflow for facies and fluid classification using multiple elastic parameters from the inversion of the seismic data
Basic introduction to Bayesian classification, multivariate Probability Density Functions (PDFs) and their optimization through Kernel Density Estimation
Teaches how to design complex multi-variate probability distribution functions to ensure proper classification of lithologies and accurate definition of litho-probabilities
Shows how to understand the quantification of uncertainty in seismic lithology and fluid prediction
Practical Exercises: Defining litho-classes, selecting attributes, optimizing PDFs, validating the results and volume application

Duration

1-day

Number of Participants

Prerequisites

None

Software Used

Course Format

Workshop

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