In recent years, various convolutional neural network architectures have been proposed for
first break picking. In this paper, we compare the standard auto‐encoder and U‐net …

The understanding of subsurface information on the Earth is crucial in numerous fields such
as economics of oil and gas, geophysical exploration, archaeology and hydro-geophysics …

We propose a workflow of deblending methodology comprised of rank‐reduction filtering
followed by a signal enhancing process. This methodology can be used to preserve …

Visual simultaneous localization and mapping (VSLAM) is a foundational technology that
enables robots to achieve fully autonomous locomotion, exploration, inspection, and more …

A key step in seismic data processing is first break (FB) picking, or rather, determining the
onset of the first seismic arrivals in seismic records. FB picking is tedious and time …

We have developed a novel first break (FB) picking method based on a robust regression
method called random sample consensus (RANSAC). The proposed method defines FB …

A novel methodology for first break picking (FBP) based on deep learning algorithms is
proposed in this paper. The goal of this study is to automate FBP by application of neural …

There is a huge growth in the amount of data being generated in forms of tabular, text, and
image data. Machine Learning (ML) is a powerful paradigm to support the knowledge …