Volve: not open after all

Back in June, Equinor made the bold and exciting decision to release all its data from the decommissioned Volve oil field in the North Sea. Although the intent of the release seemed clear, the dataset did not carry a license of any kind. Since you cannot use unlicensed content without permission, this was a problem. I wrote about this at the time.

To its credit, Equinor listened to the concerns from me and others, and considered its options. Sensibly, it chose an off-the-shelf license. It announced its decision a few days ago, and the dataset now carries a Creative Commons Attribution-NonCommercial-ShareAlike license.

Unfortunately, this license is not ‘open’ by any reasonable definition. The non-commercial stipulation means that a lot of people, perhaps most people, will not be able to legally use the data (which is why non-commercial licenses are not open licenses). And the ShareAlike part means that we’re in for some interesting discussion about what derived products are, because any work based on Volve will have to carry the CC BY-NC-SA license too.

Non-commercial licenses are not open

Here are some of the problems with the non-commercial clause:

NC licenses come at a high societal cost: they provide a broad protection for the copyright owner, but strongly limit the potential for re-use, collaboration and sharing in ways unexpected by many users

  • NC licenses are incompatible with CC-BY-SA. This means that the data cannot be used on Wikipedia, SEG Wiki, or AAPG Wiki, or in any openly licensed work carrying that license.

  • NC-licensed data cannot be used commercially. This is obvious, but far-reaching. It means, for example, that nobody can use the data in a course or event for which they charge a fee. It means nobody can use the data as a demo or training data in commercial software. It means nobody can use the data in a book that they sell.

  • The boundaries of the license are unclear. It's arguable whether any business can use the data for any purpose at all, because many of the boundaries of the scope have not been tested legally. What about a course run by AAPG or SEG? What about a private university? What about a government, if it stands to realize monetary gain from, say, a land sale? All of these uses would be illiegal, because it’s the use that matters, not the commercial status of the user.

Now, it seems likely, given the language around the release, that Equinor will not sue people for most of these use cases. They may even say this. Goodness knows, we have enough nudge-nudge-wink-wink agreements like that already in the world of subsurface data. But these arrangements just shift the onus onto the end use and, as we’ve seen with GSI, things can change and one day you wake up with lawsuits.

ShareAlike means you must share too

Creative Commons licenses are, as the name suggests, intended for works of creativity. Indeed, the whole concept of copyright, depends on creativity: copyright protects works of creative expression. If there’s no creativity, there’s no basis for copyright. So for example, a gamma-ray log is unlikely to be copyrightable, but seismic data is (follow the GSI link above to find out why). Non-copyrightable works are not covered by Creative Commons licenses.

All of which is just to help explain some of the language in the CC BY-NC-SA license agreement, which you should read. But the key part is in paragraph 4(b):

You may distribute, publicly display, publicly perform, or publicly digitally perform a Derivative Work only under the terms of this License

What’s a ‘derivative work’? It’s anything ‘based upon’ the licensed material, which is pretty vague and therefore all-encompassing. In short, if you use or show Volve data in your work, no matter how non-commercial it is, then you must attach a CC BY-NC-SA license to your work. This is why SA licenses are sometimes called ‘viral’.

By the way, the much-loved F3 and Penobscot datasets also carry the ShareAlike clause, so any work (e.g. a scientific paper) that uses them is open-access and carries the CC BY-SA license, whether the author of that work likes it or not. I’m pretty sure no-one in academic publishing knows this.

By the way again, everything in Wikipedia is CC BY-SA too. Maybe go and check your papers and presentations now :)

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What should Equinor do?

My impression is that Equinor is trying to satisfy some business partner or legal edge case, but they are forgetting that they have orders of magnitude more capacity to deal with edge cases than the potential users of the dataset do. The principle at work here should be “Don’t solve problems you don’t have”.

Encumbering this amazing dataset with such tight restrictions effectively kills it. It more or less guarantees it cannot have the impact I assume they were looking for. I hope they reconsider their options. The best choice for any open data is CC-BY.

Digitalization... of what?

I've been hearing a lot about 'digitalization', or 'digital transformation', recently. What is this buzzword?

The general idea seems to be: exploit lots and lots of data (which we already have), with analytics and machine learning probably, to do a better job finding and producing fuel and energy safely and responsibly.

At the centre of it all is usually data. Lots of data, usually in a lake. And this is where it all goes wrong. Digitalization is not about data. And it's not about technology either. Or cloud. Or IoT.

 Interest in the terms "digital transformation" and "digitalization" since 2004, according to  Google Trends . The data reveal a slight preference for the term "digitalization" in central and northern Europe.  Google Ngram Viewer  indicates that the term "digitalization" has been around for over 100 years, but it is also a medical term connected with the therapeutic use of  digitalis . Just to be clear, that's not what we're talking about.

Interest in the terms "digital transformation" and "digitalization" since 2004, according to Google Trends. The data reveal a slight preference for the term "digitalization" in central and northern Europe. Google Ngram Viewer indicates that the term "digitalization" has been around for over 100 years, but it is also a medical term connected with the therapeutic use of digitalis. Just to be clear, that's not what we're talking about.

It's about people

Oh no, here I go with the hand-wavy, apple-pie "people not process" nonsense... well, yes. I'm convinced that it's humans we're transforming, not data or technology. Or clouds. Or Things.

I think it's worth spelling out, because I think most corporations have not grasped the human aspect yet. And I don't think it's unreasonable to say that petroleum has a track record of not putting people at the centre of its activities, so I worry that this will happen again. This would be bad, because it might mean that digitalization not only fails to get traction — which would be bad enough because this revolution is long overdue — but also that it causes unintended problems.

Without people, digital transformation is just another top-down 'push' effort, with too much emphasis on supply. I think it's smarter to create demand, or 'pull', so that professionals are asking for support, and tools, and databases, and are engaged in how those things are created.

Put technical professionals at the heart of the revolution, and the rest will follow. The inverse is not true.

Strategies

This is far from an exhaustive list, but here are some ideas for ways to get ahead in digital transformation:

  • Make it easy for digitally curious people to dip a toe in. Build a beginner-friendly computing environment, and encourage people to use it. Challenge your IT people to support a culture of experimentation and creativity. 
  • Give those curious professionals access to professional development channels, whether it's our courses, other courses, online channels like Lynda.com or Coursera, or whatever. 
  • Build a community of practice for 'scientific computing'. Whether it's a Yammer group or something more formal, be sure to encourage frequent face-to-face meetups, and perhaps an intranet portal.
  • Start to connect subsurface professionals with software engineers, especially web programmers and data scientists, elsewhere in the organization. I think the best way is to embed programmers into technical teams. 
  • Encourage participation in external channels like conferences and publications, data science contests, hackathons, open source projects, and so on. I guarantee you'll see a step change in skills and enthusiasm.

The bottom line is that we're looking for a profound culutral change. It will be slow. More than that, it needs to be slow. It might only take a year or two to get traction for an idea like "digital first". But deeper concepts, like "machine readable microservices" or "data-driven decisions" or "reproducible workflows", must take longer because you can't build that high without a solid foundation. Successfully applying specific technologies like deep learning, augmented reality, or blockchain, will certainly require a high level of technology literacy, and will take years to get right.

What's going on with scientific computing in your organization? Are you 'digitally curious'? Do you feel well-supported? Do you know others in your organization like you?


The circuit board image in the thumbnail for this post is by Carl Drougge, licensed CC-BY-SA.

Beyond pricing: the fine print

Earlier this week, I wrote about pricing professional services. A slippery topic, full of ifs and buts (just like geoscience!). And it was only half the story, because before commencing on a piece of work, you and your client have to agree on a lot of things besides price. To avoid confusion later, it's worth getting those things straight before you start.

Here are most of the things we try to cover in every agreement:

  • Don't include expenses in your professional fees. Extras like travel expenses should always be separate. Be clear about your policies (for example, if I'm traveling more than 8 hours, I'm booking business class tickets). Do your client a favour by estimating the expenses for them, but pad everything a bit so you don't surprise them later with more than the estimate. Promise to provide receipts for everything.
  • You should charge for your travel time. I usually charge this at my full day rate, but sometimes less if I know I can be somewhat productive on the journey. I've read of consultants not charging if they're traveling at the weekend, because it's not a normal work day... To me this is backwards: if I'm traveling for work at the weekend, someone better be paying for my time!
  • Know your sales tax situation. I recommend getting professional help from a chartered accountant on this. Do not assume the client will know: they won't, and it's not their responsibility to, it's yours. I'm afraid you will be reading tax treaties and filling out some pretty gross forms.
  • Charge more for travel outside your 'comfort zone'. For example, I add at least 20% outside the US & Canada or Western Europe, depending on the place. Travel is exhausting, you're away from home, you need vaccinations, you need visas, everything is unfamiliar. All good fun when you're on holiday, but stressful, expensive, and time-consuming when you're trying to be an awesome professional.
  • Get paid as soon as possible. I've never done it, but I know people who charge a percentage up front. For longer jobs, specify that you wish to charge partial invoices, perhaps monthly. Ask for Net 15 terms (i.e. they'll have 15 days to pay your invoices), but settle for Net 30. Longer than this seems unfair to me. Add late fees and interest to overdue accounts, and reissue the invoice at every due date.
  • Make it easy for people to pay you. Be specific about how to pay, and give people options. It's safe to give them your bank account details (I put them on my invoices, along with foreign banking details like SWIFT and IBAN codes), and electronic funds transfer is the best way to get paid. Put your tax number on your invoices, some clients need it. I use Stripe for accepting credit cards, but bear in mind that you probably don't want to accept credit cards over about $10k.
  • Get good at currencies. Remember to be very specific about currencies whenever you talk money. Use ISO4217. If you can, make things simple for people; I charge USD to US customers. I have a USD account and use a foreign exchange service (Firma) for FX. I spend a lot of money in the US too, so I also have a USD credit card, paid in USD.
  • Do the work you want to do, the way you want to do it. This is kind of the point of 'being your own boss', right? Of course, you have to be reasonable, and compromise when necessary (OK, if every contract is a compromise, maybe you are too particular!). Talk to your client! It's OK to negotiate, ask questions, and so on. Every time I've asked for contracts or terms to be changed, it has at least been entertained, and it usually works out.

It can be awkward raising all this; you probably don't want to dump it all on someone at your first meeting. We usually put all the gory details into as short and informal a document as we can (usually part of the project description or 'scope of work', or in a 'letter of understanding'), show it to the client, answer their questions about it, and eventually reference it in the contract. Most contracts allow for some document that describes the specific conditions of the contract, but it's worth checking that those conditions don't contradict the contract. If they do, ask for the contract to be changed to reflect whatever you agree with the client.

If you're just starting out on the professional services road, I hope this is all of some help to you. And I hope it's not too daunting. 


“Fine Print” by Damian Gadal is licensed under CC BY 2.0

Pricing professional services, again

I have written about this before, but in my other life as an owner of a coworking space. It's come up in Software Underground a couple of times recently, so I thought it might be time to revisit the crucial question for anyone offering services: what do I charge?

Unfortunately, it's not a simple answer. And before you read any further, you also need to understand that I am no business mastermind. So you should probably ignore everything I write. (And please feel free to set me straight!)

Here's a bit of the note I got recently from a blog reader:

I'm planning to start doing consulting and projects of seismic interpretation and prospect generations but I don't know what's a fair price to charge for services. I sure there're many of factors. I was wondering if you can share some tips on how to calculate/determine the cost of a seismic interpreter project? Is it by sq mi of data interpreted, maps of different formations, presentations, etc.?

Let's break the reply down into a few aspects:

Know the price you're aiming for and don't go below it. I've let myself get beaten down once or twice, and it's not a recipe for success: you may end up resenting the entire job. One opinion on Software Underground was to start with a high price, then concede to the client during negotiations. I tend to keep a fair price fixed from the start, and negotiate on other things (scope and deliverables). Do try not to get sucked into too much itemization though: it will squeeze your margins.

But what is the price you're aiming for? It depends on your fixed costs (how much do you need to get the work done and pay yourself what you need to live on?), time, complexity, your experience, how simple you want your pricing to be, and so on. All these things are difficult. I tend to go for simplicity, because I don't want the administrative overhead of many line items, keeping track of time, etc. Sometimes this bites me, sometimes (maybe) I come out ahead. 

Come on, be specific. If you've recently had a 'normal' job, then a good starting point is to know your "fully loaded cost" (i.e. what you really cost, with benefits, bonuses, cubicle, coffee, computer, and so on). This is typically about 2 to 2.5 times your salary(!). That's what you would like to make in about 200 days of work. You will quickly realize why consultants are apparently so expensive: people are expensive, especially people who are good at things.

If I ever feel embarrassed to ask for my fee, I remind myself that when I worked at Halliburton, my list price as a young consultant was USD 2400 per day. Clients would sign year-long contracts for me at that rate.

It's definitely a good idea to know what you're competing with. However, it can be very hard to find others' pricing information. If you have a good relationship with the client, they may even tell you what they are used to paying. Maybe you give them a better price, or maybe you're more expensive, because you're more awesome.

Remember your other bottom lines. Money is not everything. If we get paid for work on an open source project (open code or open content), we always discount the price, often by 50%. If we care deeply about the work, we ask for less than usual. Conversely, if the work comes with added stress or administration, we charge a bit more.

One thing's for sure: sometimes (often) you're leaving money on the table. Someone out there is charging (way) more for (much) lower quality. Conversely, someone is probably charging less and doing a better job. The lack of transparency around pricing and salaries in the industry doubtless contributes to this. In the end, I tend to be as open as possible with the client. Often, prices change for the next piece of work for the same client, because I have more information the second time.

Opinions wanted

There's no doubt, it's a difficult subject. The range of plausible prices is huge: $50 to $500 per hour, as someone on Software Underground put it. Nearer $50 to $100 for a routine programming job, $200 for professional input, $400 for more awesomeness than you can handle. But if there's a formula, I've yet to discover it. And maybe a fair formula is impossible, because providing critical insight isn't really something you can pay for on a 'per hour' kind of basis — or shouldn't be.

I'm very open to more opinions on this topic. I don't think I've heard the same advice yet from any two people. When I asked one friend about it he said: "Keep increasing your prices until someone says No."

Then again, he doesn't drive a Porsche either.


If you found this post useful, you might like the follow-up post too: Beyond pricing: the fine print.


Silos are a feature, not a bug

If you’ve had the same problem for a long time, maybe it’s not a problem. Maybe it’s a fact.
— Yitzhak Rabin

"Break down the silos" is such a hackneyed phrase that it's probably not even useful any more. But I still hear it all the time — especially in our work in governments and large enterprises. It's the wrong idea — silos are awesome.

The thing is: people like silos. That's why they are there. Whether they are project teams, organizational units, technical communities, or management layers, silos are comfortable. People can speak freely. Everyone shares the same values. There is trust. There is purpose.

The problem is that much of the time — maybe most of the time, for most people — you want silos not to matter. Don't confuse this with not wanting them to exist. They do exist: get used to it. So now make them not matter. Cope don't fix. 

Permeable seals

In the context of groups of humans who want to work together, what do permeable silos look like? I mean really leaky ones.

The answer is: it depends. Here are the features they will have:

  • They serve their organization. The silo must serve the organization or community it's part of. I think a service-oriented mindset gets the best out of people: get them asking "How can I help?". If it is not serving anyone, the silo needs to die.
  • They are internally effective. This is the whole point of the silo, so this had better be true. Make sure people can do a better job because of the efficiencies of the silo. Resources are provided. Responsibilities are understood. The shared purpose must result in great things... if not, the silo needs to die.
  • They are open. This is the leakiness criterion. If someone needs something from the silo, it must be obvious how to get it, and the cost of getting it must be very low. If someone wants to join the silo, it's obvious how to do this, and they are welcomed. If something about the silo needs to change, there is a clear path to making this known.
  • They are transparent. People need to know what the silo is for. If people look in, they can see how things work. Don't build secret clubs, black boxes, or other dark places. Conversely, if people in the silo want to look outside, they can. Importantly: if the silo's level of transparency doesn't make you uncomfortable, you're not doing enough of it.

The openness is key. Ideally, the mechanism for getting things from the silo is the same one that the silo's own inhabitants use. This is by far the simplest, cheapest way to nail it. Think of it as an interface; if you're a programmer, think of it as an API. Indeed, in many cases, it will involve an actual API. If this does not exist, other people will come up with their own solutions, and if this happens often enough, the silo will cease to be useful to the organization. Competition between silos is unhelpful.

Build more silos!

A government agency can be a silo, as long as it has a rich, free interface for other agencies and the general public to access its services. Geophysics can be a silo, as long as it's easy for a wave-curious engineer to join in, and the silo is promoting excellence and professional development amongst its members. An HR department can be a silo, as long as its practices and procedures are transparent and people can openly ask why the heck they still use Myers–Briggs tests.

Go and build a silo. Then make it not matter most of the time.


Image: Silos by Flickr user Guerretto, licensed CC-BY.

What will people pay for?

Many organizations in the industry are asking this question right now. Software and service companies would like to sell product, technical societies would like to survive diminished ad sales and conference revenue, entrepreneurs would like to find customers. We all need to make a living.

I was recently asked this very question by a technical society. However, it's utterly the wrong question. Even asking this question reveals a deep-seated misunderstanding of what technical societies are for.

The question is not "What will people pay for?", it's "What do people need?". 

The leaders of our profession

Geoscientists and engineers are professionals. Our professional contributions are defined by our work and its purpose, not by our jobs and its tasks. This is essentially what makes a professional different from other workers: we are purpose-oriented, not task-oriented. We're interested in the outcome, not the means.

But even professionals benefit from leadership. Professional regulators notwithstanding, our technical societies are the de facto leaders of the profession. The professional regulator is the 'line manager' of the profession, not the 'chief geoscientist'.

Leadership is about setting an example, inspiring great work, and providing the means to grow and make the best contributions people can make. Societies need to be asking themselves how they can create the conditions for a transformed profession, a more relevant and resilient one. In short, how can they be useful? How can they serve?

OK, so what do people need?

I don't claim to have all the answers, or even many of them, but here are some things I think people need:

  • Representation. Get serious about gender and race balance on your boards and committees. There is recent progress, but it's nowhere near representative. Related: get out of North America and improve global reach.
  • Better ways to contribute and connect. Experiment more — a lot more, and urgently — with meetings and conferences. Help people participate, not just attend. Help people connect, not just exchange business cards. 
  • New ways to contribute and connect. Get serious about social media. Get scientists involved — social media is not a marketing exercise. Think hard about how you can engage your members through blogs and other content.
  • Reproducible science. Go further with open access, open data, and open source code. Make your content work harder. Make it reach further. Demand more of your authors to make their work reproducible.
  • A bit less self-interest. Stop regarding things you didn't organize or produce as a threat. Other people's events and publications may be of interest to your members, and your mission is to serve them.

Don't listen to my blathering. The AGU and the EGU are real leaders in geoscience — be inspired by them, follow their lead. Pay more attention to what's happening in publishing and conferences in other technical verticals, especially technology.

Pie in the sky is still pie

People will say, "That's all great Matt, but right now it's about survival." I get this a lot, but I'm not buying it. When times are good, you don't need to do the right thing; when times are hard, you can't afford to. True, all this would be easier if you'd started doing the right thing when times were good, but you didn't, so here we are.

Sure it's tough now, but are you sure you can afford to wait till tomorrow?


I've written lots before on these topics. Suggested reading:

Is subsurface software too pricey?

Amy Fox of Enlighten Geoscience in Calgary wrote a LinkedIn post about software pricing a couple of weeks ago. I started typing a comment... and it turned into a blog post.


I have no idea if software is 'too' expensive. Some of it probably is. But I know one thing for sure: we subsurface professionals are the only ones who can do anything about the technology culture in our industry.

Certainly most technical software is expensive. As someone who makes software, I can see why it got that way: good software is really hard to make. The market is small, compared to consumer apps, games, etc. Good software takes awesome developers (who can name their price these days), and it takes testers, scientists, managers.

But all is not lost. There are alternatives to the expensive software. We — practitioners in industry — just do not fully explore them. OpendTect is a great seismic interpretation tool, but many people don't take it seriously because it's free. QGIS is an awesome GIS application, arguably better than ArcGIS and definitely easier to use.

Sure, there are open source tools we have embraced, like Linux and MediaWiki. But on balance I think this community is overly skeptical of open source software. As evidence of this, how many oil and gas companies donate money to open source projects they use? There's just no culture for supporting Linux, MediaWiki, Apache, Python, etc. Why is that?

If we want awesome tools, someone, somewhere, has to pay the people who made them, somehow.

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So why is software expensive and what can we do about it?

I used to sell Landmark's GeoProbe software in Calgary. At the time, it was USD140k per seat, plus 18% annual maintenance. A lot, in other words. It was hard to sell. It needed a sales team, dinners, and golf.  A sale of a few seats might take a year. There was a lot of overhead just managing licenses and test installations. Of course it was expensive!

In response, on the customer side, the corporate immune system kicked in, spawning machine lockdowns, software spending freezes, and software selection committees. These were (well, are) secret organizations of non-users that did (do) difficult and/or pointless things like workflow mapping and software feature comparisons. They have to be secret because there's a bazillion dollars and a 5-year contract on the line.

Catch 22. Even if an ordinary professional would like to try some cheaper and/or better software, there is no process for this. Hands have been tied. Decisions have been made. It's not approved. It can't be done.

Well, it can be done. I call it the 'computational geophysics manoeuver', because that lot have known about it for years. There is an easy way to reclaim your professional right to the tools of the trade, to rediscover the creativity and fun of doing new things:

Bring or buy your own technology, install whatever the heck you want on it, and get on with your work.

If you don't think that's a possibility for you right now, then consider it a medium term goal.

Why I don't flout copyright

Lots of people download movies illegally. Or spoof their IP addresses to get access to sports fixtures. Or use random images they found on the web in publications and presentations (I've even seen these with the watermark of the copyright owner on them!). Or download PDFs for people who aren't entitled to access (#icanhazpdf). Or use sketchy Russian paywall-crumbling hacks. It's kind of how the world works these days. And I realize that some of these things don't even sound illegal.

This might surprise some people, because I go on so much about sharing content, open geoscience, and so on. But I am an annoying stickler for copyright rules. I want people to be able to re-use any content they like, without breaking the law. And if people don't want to share their stuff, then I don't want to share it.

Maybe I'm just getting old and cranky, but FWIW here are my reasons:

  1. I'm a content producer. I would like to set some boundaries to how my stuff is shared. In my case, the boundaries amount to nothing more than attribution, which is only fair. But still, it's my call, and I think that's reasonable, at least until the material is, say, 5 years old. But some people don't understand that open is good, that shareable content is better than closed content, that this is the way the world wants it. And that leads to my second reason:
  2. I don't want to share closed stuff as if it was open. If someone doesn't openly license their stuff, they don't deserve the signal boost — they told the world to keep their stuff secret. Why would I give them the social and ethical benefits of open access while they enjoy the financial benefits of closed content? This monetary benefit comes from a different segment of the audience, obviously. At least half the people who download a movie illegally would not, I submit, have bought the movie at a fair price.

So make a stand for open content! Don't share stuff that the creator didn't give you permission to share. They don't deserve your gain filter.

The big data eye-roll

First, let's agree on one thing: 'big data' is a half-empty buzzword. It's shorthand for 'more data than you can look at', but really it's more than that: it branches off into other hazy territory like 'data science', 'analytics', 'deep learning', and 'machine intelligence'. In other words, it's not just 'large data'. 

Anyway, the buzzword doesn't bother me too much. What bothers me is when I talk to people at geoscience conferences about 'big data', about half of them roll their eyes and proclaim something like this: "Big data? We've been doing big data since before these punks were born. Don't talk to me about big data."

This is pretty demonstrably a load of rubbish.

What the 'big data' movement is trying to do is not acquire loads of data then throw 99% of it away. They are not processing it in a purely serial pipeline, making arbitrary decisions about parameters on the way. They are not losing most of it in farcical enterprise data management train-wrecks. They are not locking most of their data up in such closed systems that even they don't know they have it.

They are doing the opposite of all of these things.

If you think 'big data', 'data' science' and 'machine learning' are old hat in geophysics, then you have some catching up to do. Sure, we've been toying with simple neural networks for years, eg probabilistic neural nets with 1 hidden layer — though this approach is very, very far from being mainstream in subsurface — but today this is child's play. Over and over, and increasingly so in the last 3 years, people are showing how new technology — built specifically to handle the special challenge that terabytes bring — can transform any quantitative endeavour: social media and online shopping, sure, but also astronomy, robotics, weather prediction, and transportation. These technologies will show up in petroleum geoscience and engineering. They will eat geostatistics for breakfast. They will change interpretation.

So when you read that Google has open sourced its TensorFlow deep learning library (9 November), or that Microsoft has too (yesterday), or that Facebook has too (months ago), or that Airbnb has too (in August), or that there are a bazillion other super easy-to-use packages out there for sophisticated statistical learning, you should pay a whole heap of attention! Because machine learning is coming to subsurface.

A focus on building

We've got some big plans for modelr.io, our online forward modeling tool. They're so big, we're hiring! An exhilarating step for a small company. If you are handy with the JavaScript, or know someone who is, scroll down to read all about it!

Here are some of the cool things in Modelr's roadmap:

Interactive 1D models – to support fluid substitution, we need to handle physical properties of pore fluids as well as rocks. Our prototype (right) supports arbitrary layers, but eventually we'd like to allow uploading well logs too.

Exporting models – imagine creating an earth model of your would-be prospect, and sending it around to your asset team to strengthen it's prognosis. Modelr solves the forward problem, PickThis solves the inverse. We need to link them up. We also need SEG-Y export, so you can see your model next to your real data.

Models from sketches – Want to do a quick sketch of a geologic setting, and see what it would look like under the lens of seismic? At the hackathon last month, Matteo Niccoli and friends showed a path to this dream — sketch a picture, take a photo, and upload it to the the app with your phone (right). 

3D models Want to visualize how seismic amplitudes vary according to bed thickness? Build a 2D wedge model and you can analyze a tuning curve. Now, want to explore the same wedge spanning a range of physical properties? That's a job for a 3D wedge model. 

Seismic attributes – Seismic discontinuity attributes, like continuity, or curvature can be ineffective when viewed in cross-section; they're really meant to be shown in time-slices. There is a vast library of attributes and co-rendering technologies we want to provide.

If you get excited about building simple tools on the web for difficult tasks under the ground, we'd love to talk to you. We have an open position for a full-time web developer to help us carry this project forward. Check out the job posting.