Transcript
Train the Estimation Model
Petrel Geophysics
Advanced Interpretation (2)
Objectives
Train the estimation model.
– Use the process with neural net as method.
Genetic inversion.
– Perform Well log conditioning.
– Choose genetic inversion as an attribute.
– Define correctly parameters.
Train Estimation Model: Neural Nets (1)
1. Generate one or more Attribute cubes from the same
seismic volume.
2. Open the Train Estimation Model process under Utilities.
5. Set a selection of
Training data.
6. Click Correlation analysis to calculate the correlation coefficients
between the input volumes.
4. Drop in the mother seismic volume in the
Seismic drop-in area.
3. Use Create new and Classification options. From the drop-down
menu under Data type, choose Seismic.
Train Estimation Model: Neural Nets (2)
7. Click the Settings tab and specify the number of classes under Unsupervised.
8. Set the Training parameters or use the defaults.
9. Display the Time slice from the newly created
Classified volume.
Classe
s
0
1
2
Genetic Inversion required inputs are limited to the seismic amplitude cube and the
Property well logs
Introduction to Genetic Inversion
Benefits of Genetic inversion
• Lithology identification.
• Facilitate interaction between seismic interpreters with geologists,
petrophysicists, and reservoir engineers.
• Inverted data set can be used directly to constrain initial reservoir models.
• Improve volumetric estimations.
• Target wells more precisely.
A new approach to derive any petro-physical property linked to the seismic amplitude
volume using a non-linear seismic inversion, multi-layer neural network as well as a
genetic algorithm is to combine them to provide a powerful and straightforward
seismic inversion.
Genetic Inversion: Overview
Genetic inversion
Well log
Low frequency filter True amplitude
Seismic volume
Property cube
Genetic Inversion: Well Log Conditioning
At a minimum, well logs must be
despiked and low frequency
filtered to match the seismic
resolution to show a deflect
where a seismic reflector displays.
• Porosity (black left)
• Porosity filtered (red middle)
• Seismic (black wiggle right)
Genetic Inversion
2. From Stratigraphic
methods, choose
Genetic inversion.
3. Under the Input/Output tab, drop in the Input seismic volume and define the output name.
(Leave it unselected and it will be given a default name.)
1. Right-click the seismic
volume in the Input
pane and select
Volume attributes.
Genetic Inversion: Parameters
4. Go to the Parameters tab, which is divided into three sections:
A) Learning input: Define the input for the training process.
B) Settings: Adjust the 3D operator for the Neural nets.
C) Advanced options: Set the quality criteria for stopping the
training process. The default values are set to fit most data sets.
A
B
C
Acoustic impedance cube
EXERCISE
p417-429
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