Cheaper Deep Learning by Transfer Learning Cats to Seismic [SEG Conference 2018]

This years SEG I got the opportunity to present some of my work on transfer learning. In automatic seismic interpretation, progress is preceived as incremental already, although the field has only been established fairly recently. It was shown with new deep neural networks, usually convolutional neural networks, that reproducing human seismic interpretation is possible. This […]

I placed 1300th on Kaggle and it’s amazing!

I placed 1360 in a deep learning competition and here’s why that is a win in my book. I spend too much time on social media, but this time I was lucky. I checked my feed on LinkedIn quickly and saw an announcement from TGS a seismic contractor. They had teamed up with Kaggle, a […]

CC-BY Loren Kerns

SEG-Y sucks! Or does it?

Many a times I have been cursing, when I got a new seismic file. Be it a 2D line, 3D cubes or pre-stack data, the standard is seldomly adhered to by most companies. The Standard SEGY as defined by the standard is now in revision 2. Most standards will likely be rev1 in these days. […]

Mid Oceanic Ridge

Geophysical Assumptions

If you assume you make an ASS of yoU and ME. That may be true in personal connections, but assumptions are necessary in physics. Particularly, geophysics needs all the assumptions it can get. The subsurface isn’t exactly nice, giving us data. We can only look from one side (mostly). The Earth itself filters our signal, […]

CC-BY-SA Pablormier DE

Making Full-Waveform Inversion Uncool again

You know what’s hype? Full-waveform inversion. If you’re in geophysics specifically involved in some sort of inversion, you want to be doing FWI. It’s what the cool kids do. You know what’s the problem? Cool kids really like to be an exclusive club. The same thing is happening in Machine Learning and Deep Learning. Fast.ai […]

Noise CC-BY Kevin Dooley

What’s with the noise?

We often only look at reflection data in a stack. But, along the way a lot of “noise” has been processed out of the seismic data to chisel out the “signal”. It’s all about signal against noise. However, one person’s noise may just be another person’s signal. Let me elaborate. If you’ve been around during […]

Dipping your Toes – Machine Learning for Geoscientists

My fellow students know this and I hope recruiters will never read this: I was never good at math in university. It was only later when it came to the application in actual geophysical problems that tensors, linear algebra, and differential equations clicked. Personally, I don’t recommend this, as it makes life unnecessarily hard. Machine […]

Challenges in Machine Learning

Geoscience and Machine Learning – EAGE 2017 Workshop

Is it data science? Machine learning? Big Data? Deep learning? Fancy math? Or just chalked up statistics with enough data? This Monday marked the start of the EAGE 2017 in Paris for me. If you have read this blog or the EAGE Student Newsletter before, you may have seen that I am some sort of […]

Getting started with the SEG Machine Learning contest

The Society for Exploration Geophysicists (SEG) started a contest to predict facies from wireline logs via machine learning. Get your Buzzword Bingo cards ready, we’re about to dive deep. The October 2016 issue of The Leading Edge had a geophysics tutorial of a special kind. Brendon Hall explains how we can use machine learning to […]