47 citations · 66 across the 4 of their papers we have counts for
4 papers
Active learning for seismic processing parameterisation, with an application to first break picking
Alan Richardson
Parameter values for seismic processing steps are often chosen on a regular grid of samples and interpolated. Active learning instead attempts to optimally select the samples on wh…
Seismic data denoising and deblending using deep learning
Alan Richardson, Caelen Feller
An important step of seismic data processing is removing noise, including interference due to simultaneous and blended sources, from the recorded data. Traditional methods are time…
Generative Adversarial Networks for Model Order Reduction in Seismic Full-Waveform Inversion
Alan Richardson
I train a Generative Adversarial Network to produce realistic seismic wave speed models. I integrate the generator network into seismic Full-Waveform Inversion to reduce the number…
Seismic Full-Waveform Inversion Using Deep Learning Tools and Techniques
Alan Richardson
I demonstrate that the conventional seismic full-waveform inversion algorithm can be constructed as a recurrent neural network and so implemented using deep learning software such…