Our world is changing and skilled workers are being replaced by intelligent systems. Where do the strengths of humans lie? Working in ML and taking the stage, whenever anyone lets me, I am no stranger to the question: What is AI good at? What are humans good at? So I was invited to give a […]
Category Archives: Computer Science
Kaggle Days Two – Googling in San Francisco
Have you met our Lord and Saviour AutoML? Day two of the Kaggle Days was, what it had to be, a competition. Very interesting to be in a room with Grandmasters, Pros and then there’s me. But the real struggle was for everyone to compete with the AutoML solutions by Google and H2O.ai. One of […]
Kaggle Days One – Googling in San Francisco [2/3]
Does anyone else know that feeling? You listen to too many people doing awesome things, you eventually get a small existential crisis. Well. I do. In Day one we explored Google Next ’19 and my highlights. While Google Next was still on, I was up to other shenanigans. My real reason to come to San […]
Research Talk — Deep Learning for 4D Pressure Saturation Inversion [Youtube]
I presented in Amsterdam during the Practical Reservoir Monitoring Workshop in Amsterdam. This is the accompanying video. Abstract In this work, we present a deep neural network inversion on map-based 4D seismic data for pressure and saturation. We present a novel neural network architecture that trains on synthetic data and provides insights into observed field […]
Keynote Bonanza and No Coffee – The EAGE / PESGB ML Workshop
Last month EAGE and PESGB organized the first machine learning workshop in geoscience in Europe. Clearly, I had every intention of going. And obviously, I met many of my favourite co-conspirators there, when I did. The workshop was divided between a day of keynotes and a day of technical talks. The keynotes accompanied the PETEX […]
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 […]
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 […]
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 […]
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 […]
