Projects from the Geothermal Hackathon 2021

The second Geothermal Hackathon happened last week. Timed to coincide with the Geosciences virtual event of the World Geothermal Congress, our 2-day event brought about 24 people together in the famous Software Underground Chateau (I’m sorry if I missed anyone!). For comparison, last year we were 13 people, so we’re going in the right direction! Next time I hope we’re as big as one of our ‘real world’ events — maybe we’ll even be able to meet up in local clusters.

Here’s a rundown of the projects at this year’s event:

Induced seismicity at Espoo, Finland

Alex Hobé, Mohsen Bazagan and Matteo Niccoli

Alex’s original workflow for creating dynamic displays of microseismic events was to create thousands of static images then stack them into a movie, so the first goal was something more interactive. On Day 1 Alex built a Plotly widget with a time zoomer/slider in a Jupyter Notebook. On day 2 he and Matteo tried Panel for a dynamic 3D plot. Alex then moved the data into LLNL Visit for fully interactive 3D plots. The team continues to hack on the idea.

---

Fluid inclusions at Coso, USA

Diana Acero-Allard, Jeremy Zhao, Samuel Price, Lawrence Kwan, Jacqueline Floyd, Brendan, Gavin, Rob Leckenby and Martin Bentley

Diana had the idea of a gas analysis case study for Coso Field, USA. The team’s specific goal was to develop visualization tools for interetpaton of fluid inclusion gas data to identify fluid types, regions of permeability, and geothermal processes. They had access to analyses from 29 wells, requiring the usual data science workflow: find and load the data, clean the data, make some visualizations and maps, and finally analyse the permeability. GitHub repo here.

---

Utah Forge data pipeline

Andrea Balza, Evan Bianco, and Diego Castañeda

Andrea was driven to dive into the Utah FORGE project. Navigating the OpenEI data portal was a bit hit-and-miss, having to download files to get into ZIP files and so on (this is a common issue with open data repositories). The team eventually figured out how to programmatically access the files to explore things more easily — right from a Jupyter Notebook. Their code for any data on the OpenEI site, not just Utah FORGE, so it’s potentially a great research tool. GitHub repo here.

---

Pythonizing a power density estimation tool

Irene Wallis, Jan Niederau, Hannah Wood, Will Middlebrook, Jeff Jex, and Bill Cummings

Like a lot of cool hackathon projects, this one started with spreadsheet that Bill created to simplify the process of making power density estimates for geothermal fields under some statistical assumptions. Such a clear goal always helps focus the mind and the team put together some Python notebooks and then a Streamlit app — which you can test-drive here! From this solid foundation, the team has plenty of plans for new directions to take the tool. GitHub repo here.

---

Computing boiling point for depth

Thorsten Hörbrand, Irene Wallis, Jan Niederau and Matt Hall

Irene identified the need for a Python tool to generate boiling-point-for-depth curves, accommodating various water salinities and chemistries. As she showed during her recent TRANSFORM tutorial (which you must watch!), so-called BPD curves are an important part of geothermal well engineering. The team produced some scripts to compute various scenarios, based on corrections in the IAPWS standards and using the PHREEQC aqueous geochemistry modeling software. GitHub repo here.

---

A big Thank You to all of the hackers that came along to this virtual event. Not quite the same as a meatspace hackathon, admittedly, but Gather.town + Slack was definitely an improvement over Zoom + Slack. At least we have an environment in which people can arrive and immediately get a sense of what is happening in the event. When you realize that people at the tables are actually sitting in Canada, the US, the UK, Switzerland, South Africa, and Auckland — it’s clear that this could become an important new way to collaborate across large distances.

Do check out all these awesome and open-source projects — and check out the #geothermal channel in the Software Underground to keep up with what happens next. We’ll be back in the future — perhaps the near future! — with more hackathons and more geothermal technology. Hopefully we’ll see you there! 🌋

Transformation in 2021

Virtual confererences have become — for now — the norm. In many ways they are far better than traditional conferences: accessible to all, inexpensive to organize and attend, asynchronous, recorded, and no-one has to fly 5,000 km to deliver a PowerPoint. In other ways, they fall short, for example as a way to meet new collaborators or socialize with old ones. As face-to-face meetings become a possibility again this summer, smart organizations will figure out ways to get the best of both worlds.

The Software Underground is continuing its exploration of virtual events next month with the latest edition of the TRANSFORM festival of the digital subsurface. In broad strokes, here’s what’s on offer:

• The Subsurface Hackathon, starting on 16 April — all are welcome, including those new to programming.

• 20 free & awesome tutorials, covering topics from Python to R, geothermal wells to seismic, and even reservoir simulation! And of course there’s a bit of machine learning and physics-based modeling in there too. Look forward to content from scientists in North & South America, Norway, Nigeria, and New Zealand.

• Lightning talks from 24 members of the community — would you like to do one?

• Birds of a Feather community meet-ups, a special Xeek challenge, and other special events.

• The Annual General Meeting of the Software Underground, where we’ll adopt our by-law and appoint the board.

We’ll even try to get at that tricky “hang out with other scientists” component, because we will have a virtual Gather.town world in which to hang out and hack, chat, or watch the livestreams.

If last year’s event is anything to go by, we can expect fantastic tutorial content, innovative hackathon projects, and great conversation between at least 750 digital geoscientists and engineers. (If you missed TRANSFORM 2020, don’t worry — all the content from last year is online and free forever, so it’s not too late to take part! Check it out.)

---

Registering for TRANSFORM

Registration is free, or pay-what-you-like. In other words, if you have funding or expenses for conferences and training, there’s an option to pay a small amount. But anyone can attend TRANSFORM free of charge. Thank you to the event sponsors, Studio X, for making this possible. (I will write about Studio X at a later date — they are doing some really cool things in the digital subsurface.)

To register for any part of TRANSFORM — even if you just want to come to the hackathon or a tutorial — click this button and complete the process on the Software Underground website. It’s a ‘pay what you like’ event, so there are 3 registration options with different prices — these are just different donation amounts. They don’t change anything about your registration.

I hope we see you at TRANSFORM. In the meantime, please jump into the Software Underground Slack and get involved in the conversations there. (You can also catch up on recent Software Underground highlights in the new series of blog posts.)

The hot rock hack is back

Last year we ran the first ever Geothermal Hackathon. As with all things, we started small, but energetic: fourteen of us worked on six projects. Topics ranged from project management to geological mapping to natural language processing. It was a fun two days not thinking about coronavirus.

This year we’ll be meeting up on Thursday 13 and Friday 14 May, starting right after the Geoscience Virtual Event of the World Geothermal Congress. Everyone is invited — geoscientists, engineers, data nerds, programmers. No experience of geothermal is necessary, just creativity and curiosity.

Projects are already being discussed on the Software Underground; here are some of the ideas:

• Data-munging project for Utah Forge, especially well 58-32.

• Update the Awesome list Thomas Martin started last year.

• Implementing classic, or newly published, equations and algorthims from the literature.

I expect the preceeding WGC event will spark some last-minute projects too. But for the time being, you’re welcome to add or vote on ideas on the event page. What tools or visualizations would you find useful?

---

Build some digital geo skills

📣 If you’re looking to build up your coding skills before the hackathon — or for a research project or an idea at work — join us for a Python class. We teach the fundamentals of Python, NumPy and matplotlib using geological and geophysical examples and geo-familiar datasets. There are two classes coming up in May (Digital Geology) and June (Digital Geophysics).

The hot rock hack happened

I was excited about the World Geothermal Congress this year. (You remember conferences — big, expensive, tiring lecture-marathons that scientists used to go to. But sometimes they were fun.)

Until this year, the WGC has only happened every 5 years and we missed the last one because it was in Australia… and the 2023 edition (it’s moving to a 3-year cycle) will be in China. So this year’s event, just a stone’s throw away in Iceland, was hotly anticipated.

And it still is, because now it will be next May. And we’ll be doing a hackathon there! You should come, get it in your calendar: 27 and 28 May 2021.

Meanwhile, this year… we moved our planned hackathon online. For the record, here’s what happened at the first Geothermal Hackathon.

Logistics: Timezones are tricky

There’s no doubt, the biggest challenge was the rotation of the earth (though admittedly it has other benefits). I believe the safest way to communicate times to a global audience is UTC, so I’ll stick to that here. It’s not ideal for anyone (except Iceland, appropriately enough in this case) but it reduces errors. We started at 0600 UTC and went until about 2100 UTC each day; about 15 hours of fun. I did check in briefly at 0000 UTC on each morning (my evening), in case anyone from New Zealand showed up, but no-one did.

Rob Leckenby and Martin Bentley, both in the UTC+2 zone, handled the early morning hosting, with me, Evan and Diego showing up a few hours later (we’re all in Canada, UTC–a few). This worked pretty well even though, as usual, the hackers were all perfectly happy and mostly self-sufficient whether we were there or not.

Technology-wise, we met up on Zoom, which was good for the start and the end of the day, and also for getting the attention of others in between (many people left the audio open, one ear to the door, so to speak.) Alongside Zoom we used the Software Underground’s Slack. As well as the #geothermal channel, each project had a channel — listed below — which meant that each project could have a separate video meetup at any time, as well as text-based chat and code-sharing. It was a good combination.

Let’s have a look at the hacks.

---

Six projects

An awesome list for geothermal — #geothermal-awesome — Thomas Martin (Colorado School of Mines), with some input from me and others, made a great start on an ‘awesome list’ document for geothermal, with a machine learning amphasis. He lists papers, tools, and open data. You can read (or contribute to!) the document here.

Collaboration tools for geothermal teams — #geothermal-collaboration-tools — Alex Hobé (Uppsala) and Valentin Métraux (GEO2X), with input from Martin Bentley and others, had a clear vision for the event: he wanted to map out the flow of data and interpretations between professionals in a geothermal project. I’ve seen similar projects get nowhere near as far in 2 months as Alex got in 2 days. The team used Holoviews and NetworkX to make some nice graphics.

GEOPHIRES web app — #geothermal-geophires — Marko Gauk (SeisWare) wanted to get into web apps at the event, and he succeeded! He built a web-based form for submitting jobs to a server running GEOPHIRES v2, a ‘full field’ geothermal project modeling tool. You can check out his app here.

Geothermal Natural Language Processing — #geothermal-nlp — Mohammad ‘Jabs’ Aljubran (Stanford), Friso (Denver), along with Rob and me, did some playing with the Stanford geothermal bibliographic database. Jabs and Friso got a nice paper recommendation engine working, while Rob and I managed to do automatic geolocation on the articles — and Jabs turned this into some great maps. Repo is here. Coming soon: a web app.

Experiments with porepy — #geothermal-porepy — Luisa Zuluaga, Daniel Coronel, and Sam got together to see what they could do with porepy, a porous media simulation tool, especially aimed at modeling fractured and deformable rocks.

Radiothermic map of Nova Scotia — #geothermal-radiothermic — Evan Bianco downloaded some open data for Nova Scotia, Canada, to see if he could implement this workflow from Beamish and Busby. But the data turned out to be unscaled (among other things), and therefore probably impossible to use for quantitative purposes. At least he made progress on a nice map.

All in all it was a fun couple of days. You can’t beat a hackathon for leaving behind emails and to-do lists for a day

Training and hackathons are moving online

A while back, I announced that we’re running some public courses in June. These courses will now be online.

They have also decreased in price by 33% because we don’t need a physical space or physical sandwiches. So the 3-day Intro to Geocomputing class now costs only USD 1200 (or $300 for students). The 2-day Intro to Machine Learning class, which is only available on the Americas timing for now, is USD 800, or USD 600 if you take both classes.

The really nice thing is that because they have no physical location, you can take part from anywhere! Well, anywhere with good Internet. Both courses are still running the week of 1 June, and there are a few places left on both courses.

More info:

• Online course with timing for the Americas.

• Online course with timing for Europe and Africa.

The hackathons are going online too

We’re also involved in some public hackathons that are moving online. Both events will now also be FREE.

On 30 April and 1 May, we’re running a (very experimental) online Geothermal Hackathon. If you’re into hot rocks, or just want to hack on open data and new problems for a couple of days, you should join us! I can’t tell you much about what we’ll be doing though. It depends a lot on who shows up at the start, and what they want to do. You can join the conversation ahead of time on Software Underground — look for the #geothermal channel.

Later, from 6 to 14 June (yep, not a typo) the Software Underground will be hosting a multi-day, muti-modal, multi-mayhem digital subsurface festival. No, I don’t really know what that means… but I know it’s going to be awesome. Again, the conversation is happening on Software Underground — hunt down the #global-hack-2020 channel.

Check back here soon for more about this brand new kind of event.

The hacks are back

We ran the first geoscience hackathon over 7 years ago in Houston. Since then we’ve hosted another 26 subsurface hackathons — that’s 175 projects, and over 900 hackers. Last year, 10 of the 11 hackathons that Agile* facilitated were in-house.

This is exciting. It means that grass-roots, creative, high-speed collaboration and technology development is possible inside large corporations. But it came at the cost of reducing our public events… and we want to bring the hackathon experience to everyone!

So this year, as well as helping execute a dozen or so in-house hackathons, we’ll be running and supporting more public hackathons too. So if you’ve been waiting for a chance to learn to code or try a social coding event, or just hang out with a lot of nerdy geoscientists and engineers — here’s your chance!

---

May: Geothermal Hackathon

The first event of the year is a new one for us. We’ll be at the World Geothermal Congress in Reykjavik, Iceland, in the last week of April. The second weekend, 2 and 3 May, we’ll be running a hackathon on machine learning for geothermal subsurface applications. Iceland is only a short flight from the rest of Europe and many places in North America, so if you fancy something completely different, this is for you! Find out more and sign up.

[An earlier version of this post had the event on the previous weekend.]

---

June: Subsurface Hackathon (USA)

We’re back in Houston in June! The AAPG ACE is there — clashing with EAGE unfortunately — and we’ll be holding a (completely unrelated) hackathon on the weekend before: 5 to 7 June. Enthought is hosting the event in their beautiful new Houston digs, and Dell EMC is there too as a major sponsor. The theme is Tools… It’s going to be a big one! Find out more and sign up.

We are running two public Python classes before this event. Check them out.

June: Amstel Hack (Europe)

The brilliant Filippo Broggini (ETHZ) is running a European hackathon again this year, again right before EAGE — and therefore the same weekend as the Houston event: 6 and 7 June. The event is being hosted at Shell’s Technology Centre in Amsterdam, and is guaranteed to be awesome. If you’re going to EAGE, it’s a no-brainer. Find out more and sign up.

We are also running a public Python class before this event. Check it out.

---

That’s it for now… I hope you can come to one of these events. If you’re just starting out on your technology journey, have no fear — these events are friendly and welcoming. If you can’t make any of them, don’t worry: there will be more in the autumn, so stay tuned. Or, if you want help making one happen at your company, get in touch.

To get email alerts about new hackathon events, sign up here. No spam, we promise.

FORCE ML 2019: project round-up

The FORCE Machine Learning Hackathon and Symposium were a great success again this year (read all about last year). Kudos to Peter Bormann of ConocoPhillips Norge, who put the programme together — held over 3 days at the NPD in Stavanger, Norway, together. Here’s a round-up of the projects.

A visualization of how human-generated rock descriptions were distributed with respect to porosity measured from the core plug.

from.cr.dscrptn.to.clssfctn

The team took up Peter’s challenge of translating abbreviated core descriptions (hence the strange team name) into something useful. Overall, the pipeline was clean > translate > classify. Cleaning was required to deal with a lot of ‘as above’ and other expediencies. As a first pass for translation, they tried simply substituting complete words for abbreviations: sandstone for ss, limestone for ls, and so on, but had more success with a bidirectional LSTM.

Find it clean it analyse it

Given a pile of undifferentiated well files containing over 40,000 curves including LAS and DLIS, the team wanted to find and analyse image log data, especially FMIs. They successfully read the data they wanted with the new dlisio library from Equinor, then threw some texture analysis at it after interpolating across the data gaps and resampling to 360 bins. They then applied a k-means clustering with 6 clusters, to find some key textures in the data. GitHub repo.

Just Surf

Using a synthetic dataset, the team (mostly coders from Emerson) set out to use convolutional deep neural networks to check if the structural model seems sensible, quantify the uncertainty, and validate the gridding algorithm used. The team brought 100 realizations for each map, and tried various combinations of single realizations and statistics from the cohort. They found that transfer learning on ResNet-50 did better than training from scratch. They said they looked forward to building on the work to produce tools for quality assurance, and they hope to use seismic data next time.

Siamese seismic

The team applied a Siamese network, normally used on human faces, to the problem of classifying 3D seismic facies. The method is semi-supervised: the network is trained on the entire dataset, with some labeled subimages. This establises a latent space (a 3D latent space of the F3 seismic data is shown to the right) with semantically meaningful norms (i.e. distance between points means something useful), in which clusters can be found. Classification on unseen subimages is done in the latent space. The team almost had an app working, and also produced the start of a new open dataset of labels for the F3 seismic volume. The team was rewarded with a prize for innovation. GitHub repo.

Lost Frequencies

This team formed spontaneously at the Tuesday meetup when it looked like there might not be any seismic projects! They set out to estimate attenuation using neural networks. This involved learning to pick maximum frequency from the peak frequency plus the seismic trace. They found that a 1D CNN did best out of all the methods they tried, and that including well logs somehow would likely improve the result quite a bit.

Rock Pandas

A creenshot from the app the team built. Each circle is a collection of documents that can be filtered dynamically.

Geolocalizing documents is a much-needed task in any pile of PDF files. This team got lots of documents from Peter, with the goal to put them on a map. The characteristically diverse team extracted keywords from an NPD corpus, with preprocessing and regular expressions for well names and so on. They built a nice-looking slippy map app allowing a user to click on a well or field entity, and see the documents associated with the location. Documents hitting multiple keywords were tagged on many entities. The Rock Pandas team won the coveted People's Choice Award, for making a great start on a hard problem, and producing a working app in limited time. GitHub repo.

Core team

In a reprise of a project last year, the team set out to get grain size from core photos. But then they thought: why not cut out the middle man and go straight for reservoir parameters? So they tried to get permeability from core photos. Using simple models, they got an accuracy of 60% with linear regression, and 69% with a neural network. Although they had some glitches in their approach (using porosity and not using depth, for example), they built a first pipeline for an interesting problem.

Some Unsupervised team members clustering around a problem.

Somehow Unsupervised

Unsupervised learning has been a theme in a coupe of previous hackathons (Copenhagen and FORCE 2018), and it was good to see another iteration of these exciting ideas. The team used the very nice Geolink dataset. After filtering out poor quality data (based on caliper and local statistics), the team applied dimensionality reduction methods like UMAP and t-SNE (these are conceptually like PCA, but much more effective) to reduce the dataset to just 2 dimensions — allowing them to make lots of crossplots. Coloring points by lithology, sand type, GR, or fluid type allowed them to look at all sorts of trends and patterns. The team won a prize for the amount of ground they covered and the attractive plots. GitHub repo.

Rock Stars

The Rock Stars took on Peter’s Make me that rock project. He wants an app which provides plausible rock properties and uncertainty for any location, depth, and formation on the Norwegian shelf. This gigantic team (12 of them!) decided to cluster the data first, then build a model for each cluster. They built an app which could indeed provide porosity and permeability given a location and depth. That such a huge team managed to converge on anything was an achievement, and they won a prize for taking on a tough project and getting a good way into it.

---

That’s it for this year! Thanks to all the participants for a fun week, and thank you to the sponsors (below) for supporting the event. Hope to see you in 2020.

More pictures from the event. Thanks to Alex Schaaf and the others that took photos.

Advice for a new hacker

So you’ve signed up for a hackathon — or maybe you’ve seen an event and you’re still thinking about it.

First thing: I can almost guarantee that you will not regret it, so if you haven’t committed yet, I challenge you to go and sign up now.

But even once you’ve chosen to go, maybe you feel nervous about your skills, or are worried about spending two days with strangers, or aren’t sure about the idea of competitive coding. Someone asked me recently how to prepare — technically and mentally — for the event.

I should say that I’ve only participated in a couple of hackathons, so I definitely don’t know everything there is to know. But I have organized more than 20 hackathons, and helped people skill up for them and (I hope!) enjoy them. Here are the top 10-ish things you can to do to get the most out of the event:

1. Brush up on your coding. Before the event, find out a bit about what kinds of projects are in the offing. If it’s a machine learning theme, brush up on your data science. Maybe image processing or text processing will be needed. Data management skills and database manipulation are always appreciated. Familiarty with a cloud environment, e.g. AWS, will help.

2. Find a friend. Either take someone with you, or find a friendly face when you get there. It’s 100% possible to navigate the experience on your own, but much more fun with a partner.

3. Dive in. You get out of the event what you put in. It’s like most learning experiences. You need an open mind, an enthusiastic demeanour, and a can-do attitude.

4. Contribute. There’s never enough time, so you are a much-needed part of your team, but unless there’s a strong effort to coordinate the project, it’ll be a bit unstructured. You’ll have to take the initiative on things.

5. Use a kanban. To help team members see the big picture and select tasks for themselves, put them on stickies on a nearby board. Make 3 areas: ‘to do’, ‘in progress’ and ‘done’. The goal is to move them from left to right.

6. Ask for help. Every event Agile runs has non-hackers around to help out with stuff — anything from dietary needs to datasets to coding advice. Don’t get stuck on something, find someone to help you.

7. Take breaks. You and your team should go for a short walk every 90 minutes or so. Relax a bit, but also get caught up: get progress reports from everyone, re-evaluate the goals, identify issues. You will find more clarity away from your keyboards.

8. Work backwards from the demo. A good strategy is to outline what would make a killer demo of the project you have selected. Include at least one “Wow” feature if at all possible. Then work out what you need to either fake or build to make that demo. Build what you can, fake the rest.

9. Check in with the other teams. This might not fly at highly competitive events, but at more casual affairs or if everyone is working on different projects, try chatting to some other teams, especially during breaks.

10. Label your equipment. Hackathons are pretty chaotic, and although 99.9% of hackers are awesome, it’s still a roomful of strangers, so label the gear you care about. And of course keep your phone and computer locked.

11. Reciprocate. Almost all these bits of advice have corollaries: be friendly and welcoming, accept contributions from others, give help if asked, and so on. Hackathons are social events as much as technical ones — enjoy meeting and collaborating with others.

If you have signed up for an event — I hope you love it! Do let us know how you get along. Or, if you’ve already been to a hackathon and have some advice to share — leave a comment below.

---

If you’re looking for an event to go to and you’re in western Europe — here’s one! It’s the FORCE Machine Learning Hackathon in Stavanger, Norway. I recently wrote about it — check it out.

If you’re looking for subsurface or geoscience project ideas, then I have a lot of reading for you. Check out the long list of hackathons reports on this blog. You can also dive into the Software Underground Slack to discuss project ideas there.

The hack returns to Norway

Last autumn Agile helped Peter Bormann (ConocoPhillips Norge) and the FORCE consortium host the first geo-flavoured hackathon in Norway. Maybe you were there, or maybe you read about the nine fascinating machine learning projects here on the blog. If so, you’ll know it was a great event, so we’re doing it again!

Hackthon: 18 and 19 September
Symposium: 20 September

---

Check out last year’s projects here. Projects included Biostrat!, Virtual Metering, sketch2seis, and AVO ML — a really interesting AVO approach exploiting latent spaces (see image, right). Most of them are on GitHub and could be extended this year.

Part of what I love about these things is that we have no idea what the projects will be. As last year, there’ll be a pre-hackathon meetup in Storhaug the evening before Day 1 (on 17 September) — we’ll figure it all out there. In the meantime, if you have an idea check out the link at the end of this post where you can share and discuss it with others.

---

The hackathon will be followed by a one-day symposium on machine learning in the subsurface (left). This well attended event was also excellent last year, and promises to deliver again in 2019. Peter did a briliant job of keeping things rooted in real results from real research, so you won’t be subjected to the parade of marketing talks you might have been subjected to at certain other conferences.

---

Find out more and sign up on NPD.no! Don’t delay; places are limited.

Submit and discuss project ideas on Agile’s Events page. Note that this does not sign you up for the event.

Get on softwareunderground.com/slack to discuss the event in the #force-hack-2019 channel.

See you there!

The London hackathon

At the end of November I reported on the projects at the Oil & Gas Authority’s machine learning hackathon in Aberdeen. This post is about the follow-up event at London Olympia.

---

Like the Aberdeen hackathon the previous weekend, the theme was ‘machine learning’. The event unfolded in the Apex Room at Olympia, during the weekend before the PETEX conference. The venue was excellent, with attentive staff and top-notch catering. Thank you to the PESGB for organizing that side of things.

Thirty-eight digital geoscientists spent the weekend with us, and most of them also took advantage of the bootcamp on Friday; at least a dozen of those had not coded at all before the event. It’s such a privilege to work with people on their skills at these events, and to see them writing their own code over the weekend.

Here’s the full list of projects from the event…

---

Sweet spot hunting

Sweet Spot Sweat Shop: Alan Wilson, Geoff Chambers, Marco van der Linden, Maxim Kotenev, Rowan Haddad.

Project: We’ve seen a few people tackling the issue of making decisions from large numbers of realizations recently. The approach here was to generate maps of various outputs from dynamic modeling and present these to the user in an interactive way. The team also had maps of sweet spots, as determined by simulation, and they attempted to train models to predict these sweetspots directly from the property maps. The result was a unique and interesting exploration of the potential for machine learning to augment standard workflows in reservoir modeling and simulation. Project page. GitHub repo.

---

An intelligent dashboard

Dash AI: Vincent Penasse, Pierre Guilpain.

Project: Vincent and Pierre believed so strongly in their project that they ran with it as a pair. They started with labelled production history from 8 wells in a Pandas dataframe. They trained some models, including decision trees and KNN classifiers, to recognizedata issues and recommend required actions. Using skills they gained in the bootcamp, they put a flask web app in front of these to allow some interaction. The result was the start of an intelligent dashboard that not only flagged issues, but also recommended a response. Project page.

This project won recognition for impact.

---

Predicting logs ahead of the bit

Team Mystic Bit: Connor Tann, Lawrie Cowliff, Justin Boylan-Toomey, Patrick Davies, Alessandro Christofori, Dan Austin, Jeremy Fortun.

Project: Thinking of this awesome demo, I threw down the gauntlet of real-time look-ahead prediction on the Friday evening, and Connor and the Mystic Bit team picked it up. They did a great job, training a series of models to predict a most likely log (see right) as well as upper and lower bounds. In the figure, the bit is currently at 1770 m. The model is shown the points above this. The orange crosses are the P90, P50 and P10 predictions up to 40 m ahead of the bit. The blue points below 1770 m have not yet been encountered. Project page. GitHub repo.

This project won recognition for best execution.

---

The seals make a comeback

Selkie Se7en: Georgina Malas, Matthew Gelsthorpe, Caroline White, Karen Guldbaek Schmidt, Jalil Nasseri, Joshua Fernandes, Max Coussens, Samuel Eckford.

Project: At the Aberdeen hackathon, Julien Moreau brought along a couple of satellite image with the locations of thousands of seals on the images. They succeeded in training a model to correctly identify seal locations 80% of the time. In London, another team of almost all geologists picked up the project. They applied various models to the task, and eventually achieved a binary prediction accuracy of over 97%. In addition, the team trained a multiclass convolutional neural network to distinguish between whitecoats (pups), moulted seals (yearlings and adults), double seals, and dead seals.

Impressive stuff; it’s always inspiring to see people operating way outside their comfort zone. Project page.

---

Interpreting the language of stratigraphy

The Lithographers: Gijs Straathof, Michael Steventon, Rodolfo Oliveira, Fabio Contreras, Simon Franchini, Malgorzata Drwila.

Project: At the project bazaar on Friday (the kick-off event at which we get people into teams), there was some chat about the recent paper on lithology prediction using recurrent neural networks (Jiang & James, 2018). This team picked up the idea and set out to reproduce the results from the paper. In the process, they digitized lithologies from one of the Posiedon wells. Project page. GitHub repo.

This project won recognition for teamwork.

---

Know What You Know

Team KWYK: Malcolm Gall, Thomas Stell, Sebastian Grebe, Marco Conticini, Daniel Brown.

Project: There’s always at least one team willing to take on the billions of pseudodigital documents lying around the industry. The team applied latent semantic analysis (a standard approach in natural language processing) to some of the gnarlier documents in the OGA’s repository. Since the documents don’t have labels, this is essentially an unsupervised task, and therefore difficult to QC, but the method seemed to be returning useful things. They put it all in a nice web app too. Project page. GitHub repo.

This project won recognition for Most Value.

---

A new approach to source separation

Cocktail Party Problem: Song Hou, Fai Leung, Matthew Haarhoff, Ivan Antonov, Julia Sysoeva.

Project: Song, who works at CGG, has a history of showing up to hackathons with very cool projects, and this was no exception. He has been working on solving the seismic source separation problem, more generally known as the cocktail party problem, using deep learning… and seems to have some remarkable results. This is cool because the current deblending methods are expensive. At the hackathon he and his team looked for ways to express the uncertainty in the deblending result, and even to teach a model to predict which parts of the records were not being resolved with acceptable signal:noise. Highly original work and worth keeping an eye on.

---

A big Thank You to the judges: Gillian White of the OGTC joined us a second time, along with the OGA’s own Jo Bagguley and Tom Sandison from Shell Exploration. Jo and Tom both participated in the Subsurface Hackathon in Copenhagen earlier this year, so were able to identify closely with the teams.

Thank you as well to the sponsors of these events, who all deserve the admiration of the community for stepping up so generously to support skill development in our industry:

---

That’s it for hackathons this year! If you feel inspired by all this digital science, do get involved. There are computery geoscience conversations every day over at the Software Underground Slack workspace. We’re hosting a digital subsurface conference in France in May. And there are lots of ways to get started with scientific computing… why not give the tutorials at Learn Python a shot over the holidays?

To inspire you a bit more, check out some more pictures from the event…