Applying Machine Learning Technologies in the Niobrara Formation, DJ Basin, to Quickly Produce an Integrated Structural and Stratigraphic Seismic Classification Volume Calibrated to Wells Read More »
EAGE – Visit booth #2225 to hear industry thought leaders present applications of machine learning and deep learning technologies to seismic interpretation in different geologic settings.
The Oil & Gas Machine Learning Symposium will host thought leaders from E&P companies, consulting firms, and large technology companies. With a focus on geoscience, reservoir characterization, and technology, the Symposium will highlight developments in AI, Machine Learning, Deep Learning, Data Analytics, Cloud Computing, and the Industrial Internet of Things (IIoT).
Over the last few years, there has been an increase in the application of machine learning, a type of artificial intelligence, in the interpretation of seismic data.
Sharareh Manouchehri, Nam Pham, Terje A. Hellem and Rocky Roden predict lithofacies and reservoir properties using multi-attribute seismic analysis based on an unsupervised machine learning process called Self-Organizing Maps (SOMs).