AASPI Attribute-Assisted Seismic Processing & Interpretation

A Research Consortium conducted at U Oklahoma, U Alabama, U Texas Permian Basin and SISMO

Software Demos

Multispectral Coherence
Application Authors
Application of AASPI multispectral coherence for faults and channels
Jose Pedro Mora
Multispectral Coherence Challenge
Diana Salazar Florez
The AASPI Machine Learning Toolbox
Application Authors
AASPI unsupervised learning - Overview of a 5-step workflow
Thang Ha
AASPI unsupervised learning step 1 - Generate the training data
Thang Ha
AASPI unsupervised learning step 2 - Analyze the input data
Thang Ha
AASPI unsupervised learning step 3 - Create the model
Thang Ha
AASPI unsupervised learning step 4 - Perform the classification
Thang Ha
AASPI unsupervised learning step 5 - Display the results
Thang Ha
Additional AASPI Demos
Application Authors
Vector plot functionality
Thang Ha
Overview of new enhancements and capabilities
David Lubo-Robles
Attribute overview: Aberrancy
Sumit Verma

School of Geosciences | Mewbourne College of Earth & Energy | The University of Oklahoma
Department of Geological Sciences | College of Arts and Sciences | The University of Alabama
Department of Geosciences | College of Arts and Sciences | The University of Texas Permian Basin
SISMO

Date of last revision: 13 May 2023
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