Weekend worship in Salt Lake City

The Salt Lake City hackathon — only the second we've done with a strong geology theme — is a thing of history, but you can still access the event page to check out who showed up and who did what. (This events page is a new thing we launched in time for this hackathon; it will serve as a public document of what happens at our events, in addition to being a platform for people to register, sponsor, and connect around our events.) 

In true seat-of-the-pants hackathon style we managed to set up an array of webcams and microphones to record the finale. The demos are the icing on the cake. Teams were selected at random and were given 4 minutes to wow the crowd. Here is the video, followed by a summary of what each team got up to... 


Unconformist.ai

Didi Ooi (University of Bristol), Karin Maria Eres Guardia (Shell), Alana Finlayson (UK OGA), Zoe Zhang (Chevron). The team used machine learning the automate the mapping of unconformities in subsurface data. One of the trickiest parts is building up a catalog of data-model pairs for GANs to train on. Instead of relying on thousand or hundreds of thousands of human-made seismic interpretations, the team generated training images by programmatically labelling pixels on synthetic data as being either above (white) or below (black) the unconformity. Project pageSlides.

unconformist.ai_preso

Outcrops Gee Whiz

Thomas Martin (soon Colorado School of Mines), Zane Jobe (Colorado School of Mines), Fabien Laugier (Chevron), and Ross Meyer (Colorado School of Mines). The team wrote some programs to evaluate facies variability along drone-derived digital outcrop models. They did this by processing UAV point cloud data in Python and classified different rock facies using using weather profiles, local cliff face morphology, and rock colour variations as attributes. This research will help in the development drone assisted 3D scanning to automate facies boundaries mapping and rock characterization. RepoSlides.

SLC_outcrop_geewhiz_blog.png

Jet Loggers

Eirik Larsen and Dimitrios Oikonomou (Earth Science Analytics), and Steve Purves (Euclidity). This team of European geoscientists, with their circadian clocks all out of whack, investigated if a language of stratigraphy can be extracted from the rock record and, if so, if it can be used as another tool for classifying rocks. They applied natural language processing (NLP) to an alphabetic encoding of well logs as a means to assist or augment the labour-intensive tasks of classifying stratigraphic units and picking tops. Slides.

 

 

SLC_NLP_jet_loggers.png
SLC_bookcliffs.png

Book Cliffs Bandits

Tom Creech (ExxonMobil) and Jesse Pisel (Wyoming State Geological Survey). The team started munging datasets in the Book Cliffs. Unfortunately, they really did not have the perfect, ready to go data, and by the time they pivoted to some workable open data from Alaska, their team name had already became a thing. The goal was build a tool to assist with lithology and stratigraphic correlation. They settled on change-point detection using Bayesian statistics, which they were using to build richer feature sets to test if it could produce more robust automatic stratigraphic interpretation. Repo, and presentation.

 

 

A channel runs through it

Nam Pham (UT Austin), Graham Brew (Dynamic Graphics), Nathan Suurmeyer (Shell). Because morphologically realistic 3D synthetic seismic data is scarce, this team wrote a Python program that can take seismic horizon interpretations from real data, then construct richer training data sets for building an AI that can automatically delineate geological entities in the subsurface. The pixels enclosed by any two horizons are labelled with ones, pixels outside this region are labelled with zeros. This work was in support of Nam's thesis research which is using the SegNet architecture, and aims to extract not only major channel boundaries in seismic data, but also the internal channel structure and variability – details that many seismic interpreters, armed even with state-of-the art attribute toolboxes, would be unable to resolve. Project page, and code.

GeoHacker

Malcolm Gall (UK OGA), Brendon Hall and Ben Lasscock (Enthought). Innovation happens when hackers have the ability to try things... but they also need data to try things out on. There is a massive shortage of geoscience datasets that have been staged and curated for machine learning research. Team Geohacker's project wasn't a project per se, but a platform aimed at the sharing, distribution, and long-term stewardship of geoscience data benchmarks. The subsurface realm is swimming with disparate data types across a dizzying range of length scales, and indeed community efforts may be the only way to prove machine-learning's usefulness and keep the hype in check. A place where we can take geoscience data, and put it online in a ready-to-use for for machine learning. It's not only about being open, online and accessible. Good datasets, like good software, need to be hosted by individuals, properly documented, enriched with tutorials and getting-started guides, not to mention properly funded. Website.

SLC_petrodict.png

Petrodict

Mark Mlella (Univ. Louisiana, Lafayette), Matthew Bauer (Anchutz Exploration), Charley Le (Shell), Thomas Nguyen (Devon). Petrodict is a machine-learning driven, cloud-based lithology prediction tool that takes petrophysics measurements (well logs) and gives back lithology. Users upload a triple combo log to the app, and the app returns that same log with with volumetric fractions for it's various lithologic or mineralogical constituents. For training, the team selected several dozen wells that had elemental capture spectroscopy (ECS) logs – a premium tool that is run only in a small fraction of wells – as well as triple combo measurements to build a model for predicting lithology. Repo.

Seismizor

George Hinkel, Vivek Patel, and Alex Waumann (all from University of Texas at Arlington). Earthquakes are hard. This team of computer science undergraduate students drove in from Texas to spend their weekend with all the other geo-enthusiasts. What problem in subsurface oil and gas did they identify as being important, interesting, and worthy of their relatively unvested attention? They took on the problem of induced seismicity. To test whether machine learning and analytics can be used to predict the likelihood that injected waste water from fracking will cause an earthquake like the ones that have been making news in Oklahoma. The majority of this team's time was spent doing what all good scientists do –understanding the physical system they were trying to investigate – unabashedly pulling a number of the more geomechanically inclined hackers from neighbouring teams and peppering them with questions. Induced seismicity is indeed a complex phenomenon, but George's realization that, "we massively overestimated the availability of data", struck a chord, I think, with the judges and the audience. Another systemic problem. The dynamic earth – incredible in its complexity and forces – coupled with the fascinating and politically charged technologies we use for drilling and fracking might be one of the hardest problems for machine learning to attack in the subsurface. 


AAPG next year is in San Antonio. If it runs, the hackathon will be 18–19 of May. Mark your calendar and stay tuned!

Unsolved problems in applied geoscience

I like unsolved problems. I first wrote about them way back in late 2010 — Unsolved problems was the eleventh post on this blog. I touched on the theme again in 2013, before and after the first 'unsession' at the GeoConvention, which itself was dedicated to finding the most pressing questions in exploration geoscience. As we turn towards the unsession at AAPG in Salt Lake City in May, I find myself thinking again about unsolved problems. Specifically, what are they? How can we find them? And what can we do to make them easier to solve?

It turns out lots of people have asked these questions before.

unsolved_problems.png

I've compiled a list of various attempts by geoscientists to list he big questions in the field. The only one I was previous aware of was Milo Backus's challenges in applied seismic geophysics, laid out in his president's column in GEOPHYSICS in 1980 and highlighted later by Larry Lines as part of the SEG's 75th anniversary. Here are some notable attempts:

  • John William Dawson, 1883 — Nova Scotia's most famous geologist listed unsolved problems in geology in his presidential address to the American Association for the Advancement of Science. They included the Cambrian Explosion, and the origin of the Antarctic icecap. 
  • Leason Heberling Adams, 1947 — One of the first experimental rock physicists, Adams made the first list I can find in geophysics, which was less than 30 years old at the time. He included the origin of the geomagnetic field, and the temperature of the earth's interior.
  • Milo Backus, 1980 — The list included direct hydrocarbon detection, seismic imaging, attenuation, and anisotropy.  
  • Mary Lou Zoback, 2000 — As her presidential address to the GSA, Zoback kept things quite high-level, asking questions about finding signal indynamic systems, defining mass flux and energy balance, identifying feedback loops, and communicating uncertainty and risk. This last one pops up in almost every list since.
  • Calgary's geoscience community, 2013 — The 2013 unsession unearthed a list of questions from about 50 geoscientists. They included: open data, improving seismic resolution, dealing with error and uncertainty, and global water management.
  • Daniel Garcia-Castellanos, 2014 — The Retos Terrícolas blog listed 49 problems in 7 categories, ranging from the early solar system to the earth's interior, plate tectonics, oceans, and climate. The list is still maintained by Daniel and pops up occasionally on other blogs and on Wikipedia.

The list continues — you can see them all in this presentation I made for a talk (online) at the Bureau of Economic Geology last week (thank you to Sergey Fomel for hosting me!). During the talk, I took the opportunity to ask those present what their unsolved problems are, especially the ones in their own fields. Here are a few of what we got (the rest are in the preso):

1-what-are-the-biggest-unsolved-problems-in-your-field-1.jpg

What are your unsolved problems in applied geoscience? Share them in the comments!


If you have about 50 minutes to spare, you can watch the talk here, courtesy of BEG's streaming service.

Click here to watch the talk >>>

This year's social coding events

If you've always wondered what goes on at our hackathons, make 2018 the year you find out. There'll be plenty of opportunities. We'll be popping up in Salt Lake City, right before the AAPG annual meeting, then again in Copenhagen, before EAGE. We're also running events at the AAPG and EAGE meetings. Later, in the autumn, we'll be making some things happen around SEG too. 

If you just want to go sign up right now, head to the Events page. If you want more deets first, read on.

Salt Lake City in May: machine learning and stratigraphy

This will be one of our 'traditional' hackathons. We're looking for 7 or 8 teams of four to come and dream up, then hack on, new ideas in geostatistics and machine learning, especially around the theme of stratigraphy. Not a coder? No worries! Come along to the bootcamp on Friday 18 May and acquire some new skills. Or just show up and be a brainstormer, tester, designer, or presenter.

Thank you to Earth Analytics for sponsoring this event. If you'd like to sponsor it too, check out your options. The bottom line is that these events cost about $20,000 to put on, so we appreciate all the help we can get. 

It doesn't stop with the hackathon demos on Sunday. At the AAPG ACE, Matt is part of the team bringing you the Machine Learning Unsession on Wednesday afternoon. If you're interested in the future of computation and geoscience, come along and be heard. It wouldn't be the same without you.

Copenhagen in June: visualization and interaction

After events in Vienna in 2016 and Paris in 2017, we're looking forward to being back in Europe in June. The weekend before the EAGE conference, we'll be hosting the Subsurface Hackathon once again. Partnering with Dell EMC and Total E&P, as last year, we'll be gathering 60 eager geoscientists to explore data visualization, from plotting to virtual reality. I can't wait.

In the EAGE Exhibition itself, we're cooking up something else entirely. The Codeshow is a new kind of conference event, mixing coding tutorials with demos from the hackathon and even some mini-hackathon projects to get you started on your own. It's 100% experimental, just the way we like it.

Anaheim in October: something exciting

We'll be at SEG in Anaheim this year, in the middle of October. No idea what exactly we'll be up to, but there'll be a hackathon for sure (sign up for alerts here). And tacos, lots of those. 

You can get tickets to most of these events on the Event page. If you have ideas for future events, or questions about them, drop us a line or leave a comment on this post!


I'll leave you with a short and belated look at the hackathon in Paris last year...

A quick look at the Subsurface Hackathon in Paris, June 2017. 

Rock Hack 2014

We're hosting another hackathon! This time, we're inviting geologists in all their colourful guises to come and help dream up cool tools, find new datasets, and build useful stuff. Mark your calendar: 5 & 6 April, right before AAPG.

On 4 April there's the added fun of a Creative geocomputing course. So you can learn some skills, then put them into practice right away. More on the course next week.

What's a hackathon?

It's not as scary — or as illegal — as it sounds! And it's not just for coders. It's just a roomful of creative geologists and friendly programmers figuring out two things together:

  1. What tools would help us in our work?
  2. How can we build those tools?

So for example, we might think about problems like these:

  • A sequence stratigraphy calibration app to tie events to absolute geologic time
  • Wireline log 'attributes'
  • Automatic well-to-well correlation
  • Facies recognition from core
  • Automatic photomicrograph interpretation: grain size, porosity, sorting, and so on
  • A mobile app for finding and capturing data about outcrops
  • Sedimentation rate analysis, accounting for unconformities, compaction, and grain size

I bet you can think of something you'd like to build — add it to the list!

Still not sure? Check out what we did at the Geophysics Hackathon last autumn...

How do I sign up?

You can sign up for the creative geocomputing course at Eventbrite.

If you think Rock Hack sounds like a fun way to spend a weekend, please drop us a line or sign up at Hacker League. If you're not sure, please come anyway! We love visitors.

If you think you know someone who'd be up for it, let them know with the sharing buttons below.

The poster image is from an original work by Flickr user selkovjr.