Introduction: Picking Horizons - The Evolution of Analytical and ML Methods

Research papers
Dive into the world of seismic interpretation and discover how Machine Learning is transforming horizon tracking in the oil and gas industry. This video is perfect for geophysicists, data scientists, and curious minds alike who want to understand how cutting-edge technology is redefining the way we explore subsurface.
📓 Resources: Fast seismic horizon reconstruction based on local dip transformation - Least-squares horizons with local slopes and multigrid correlations - Seismic horizon extraction with dynamic programming - Unfaulting and unfolding 3D seismic images - Flattening without picking - Extracting horizon surfaces from 3D seismic data using deep learning - Automatic tracking for seismic horizons using convolution feature analysis and optimization algorithm - Seismic horizon tracking using a deep convolutional neural network - Deep Relative Geologic Time: A Deep Learning Method for Simultaneously Interpreting 3-D Seismic Horizons and Faults - Automatically interpreting all faults, unconformities, and horizons from 3D seismic images - Horizon volumes with interpreted constraints - Deep learning for relative geologic time and seismic horizons - Generating Seismic Horizon Using Multiple Seismic Attributes - Simulating the procedure of manual seismic horizon picking -