An alternative approach for machine learning seismic interpretation and its application in Daqing Oilfield
Author:
Affiliation:
1. Beijing Key Laboratory of Petroleum Data Mining, China University of Petroleum (Beijing)
Publisher
Society of Exploration Geophysicists
Link
https://library.seg.org/doi/pdf/10.1190/segam2018-2989898.1
Reference7 articles.
1. Reservoir lithofacies analysis using 3D seismic data in dissimilarity space
2. Semi-supervised least squares support vector machine algorithm: application to offshore oil reservoir
3. Paolo, B., V. Lipari, and S. Tubaro, 2017, A machine learning approach to facies classification using well logs: 87th Annual International Meeting, SEG, Expanded Abstracts, 2137–2142, 10.1190/segam2017-17729805.1.
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1. Fluid and lithofacies prediction based on integration of well-log data and seismic inversion: A machine-learning approach;GEOPHYSICS;2021-07-01
2. Porosity Prediction With Uncertainty Quantification From Multiple Seismic Attributes Using Random Forest;Journal of Geophysical Research: Solid Earth;2021-07
3. Estimation of Soil Heavy Metal Content Using Hyperspectral Data;Remote Sensing;2019-06-20
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