eHR-245 HampsonRussell LithoSI & Emerge Virtual Workshop

Audience

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

Content

LithoSI is a relatively new, interactive package which complements our very successful Emerge software. Together with Emerge, they both allow the transformation of seismic volumes and/or elastic attributes (from Strata and/or AVO) to geological or reservoir properties such as facies, saturation and porosity. Note that in this one-day workshop, we will not cover all of the material in our standard LithoSI and Emerge workshop.

Learning Objectives

  • Basic introduction to Bayesian classification, multivariate Probability Density Functions (PDFs) and their optimization, Kernel Density Estimation (LithoSI)
  • Teaches the theory and application of linear and multi-linear regression in well log prediction and seismic lithology classification (Emerge)
  • Practical exercises comprise 65% of the unit content
  • LithoSI: Defining litho-classes, selecting attributes, optimizing PDFs, validating the results, volume application
  • Emerge: Combining optimal attributes to predict volumes of log data from seismic, crossvalidation techniques, volume application, predicting logs from logs

Duration

1-day

Prerequisites

None

Software Covered

LithoSI, Emerge

Course Format

Virtual Training delivered via GoToTraining

Audience

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

Content

Duration1-day PrerequisitesNone Software CoveredLithoSI, EmergeCourse FormatVirtual Training delivered via GoToTraining

Learning Objectives

Basic introduction to Bayesian classification, multivariate Probability Density Functions (PDFs) and their optimization, Kernel Density Estimation (LithoSI)
Teaches the theory and application of linear and multi-linear regression in well log prediction and seismic lithology classification (Emerge)
Practical exercises comprise 65% of the unit content
LithoSI: Defining litho-classes, selecting attributes, optimizing PDFs, validating the results, volume application
Emerge: Combining optimal attributes to predict volumes of log data from seismic, crossvalidation techniques, volume application, predicting logs from logs

Duration

1-day

Number of Participants

Prerequisites

None

Software Used

Course Format

Virtual Training delivered via GoToTraining

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