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Advanced Seismic Reservoir Characterization Workshop

Jul 05 - Jul 09, 2021 11:00 am
Malaysia , Online

Category: Training

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HampsonRussell Attributes Workshop

Course Benefit

  • Explains both the theory and practice of selected advanced seismic attributes
  • Teaches the user how to apply advanced seismic attributes using North Sea F3 dataset
  • Understands the applications and limitations of seismic attributes for seismic reservoir characterization

HampsonRussell Emerge Workshop

Course Benefit

  • A comprehensive overview of the generation of seismic attributes
  • Provides a mechanism for the user to derive complex relationships between seismic attributes and petrophysical parameters
  • Understanding of how to recognize reliable attributes when estimating reservoir parameters.
  • Basic theory of neural network technologies
  • Application of neural network technology in well log prediction, petrophysical volume generation and seismic lithology classification
  • Structured to teach theory alongside practical exercises, equipping the user in the operation of the Emerge software

HampsonRussell GeoSI Workshop

Course Benefit

  • Explains both the theory and practice of stochastic inversion using GeoSI modules
  • Shows how GeoSI is fully integrated into the HampsonRussell Geoview interface
  • Teaches the user how to apply GeoSI using a real North Sea oil sand example

Content

HampsonRussell Attributes Workshop

Introduction to Seismic Attributes and Spectral Decomposition
Exercise 1: Spectral Decomposition

Edge Enhancement Attributes, Curvature Attributes and Energy Ratio Attributes
Exercise 2: Edge Enhancement Attributes, Curvature Attributes and Energy Ratio Attributes

Bandwidth Attributes and PCA Analysis
Exercise 3: Bandwidth Attributes

HampsonRussell Emerge Workshop

Emerge introduction
Exercise 1: Setting up an Emerge Project

Seismic Attributes and Cross Plotting
Exercise 2: The Single-Attribute List

Multiple Attributes and Validation of Attributes
Exercise 3: The Multi-Attribute List

Using the Convolutional Operator
Exercise 4: The Convolutional Operator
Exercise 5: Processing the 3D Volume

Neural Networks in Emerge
Exercise 6: Predicting Porosity Logs

Deep Feed-forward Neural Networks (DFNN)
Exercise 7: Using Deep Feed-forward Neural Networks

Training the Probabilistic Neural Network (PNN)
Exercise 8: Using Probabilistic Neural Networks

Case Study: Using Emerge to predict Vshale

PNN Classification
Exercise 9: Using PNN for Classification

S-wave Prediction
Exercise 10: Predicting Logs from Other Logs

HampsonRussell GeoSI Workshop

Introduction to Geostatistical Inversion

Introduction to GeoSI
Exercise 1: Project Setup and data loading

Log Correlation, Wavelets and Model Building
Exercise 2: Wavelet extraction and model building

Stochastic Inversion
Exercise 3: Stochastic Inversion

Facies Prediction
Exercise 4: Facies Prediction

Visualization of results
Exercise 5: Visualization

Duration: 5-day

Software used: HampsonRussell Attributes, Emerge, GeoSI

Course Format: Instructor-led, workflow-based, classroom training

Instructor(s): TBD

Number of Participants: 14

Price

  • US$ 3,750 (5 Days: Attributes, Emerge & Emerge DFNN, GeoSI)
  • US$ 3,000 (4 Days: Emerge & Emerge DFNN, GeoSI)
  • US$ 2,250 (3 Days: Attributes, Emerge & Emerge DFNN)
  • US$ 2,250 (3 Days: Attributes, GeoSI)
  • US$ 1,500 (2 Days: Emerge & Emerge DFNN)
  • US$ 1,500 (2 Days: GeoSI)
  • US$ 750 (1 Day: Attributes)

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Contact: Mona Hamzah
monaliza.hamzahsani@cgg.com

Terms and Conditions

  • Training placements will only be confirmed upon receipt of official company purchase order (PO) or confirmation of successful credit card payment.
  • In case of booking by credit card, full payment will be required in advance of the course attendance and processed in USD. Payment made is non-refundable. You may substitute participant at zero penalty if written notice is received at least 5 days prior to the commencement date of the course.
  • In case of booking by company PO, invoice will be submitted following course attendance.
  • Invoice may be issued by another CGG entity as CGG deems fit and not necessarily the CGG entity providing the course.
  • Invoice is payable within 30 days from the date of the invoice.
  • Price is net of any applicable tax and payment must be made in the specified currency.
  • All courses are subject to CGG having received sufficient registration for convening the course, and CGG GeoSoftware reserves the right to change, postpone or cancel any course. In such event, advance notification will be given to Participants.
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