New virtual training for digital geoscience

Looking to skill up before 2022 hits us with… whatever 2022 is planning? We have quite a few training classes coming up — don’t miss out! Our classes use 100% geoscience data and examples, and are taught exclusively by earth scientists.

We’re also always happy to teach special classes in-house for you and your colleagues. Just get in touch.

Special classes for CSEG in Calgary

• CSEG Crash Course, 7 to 10 September — there are no prerequisites for this class.

• CSEG Doodle Train on 1 to 4 November — this class assumes you’ve taken the crash course, or have some basic Python and NumPy skills.

Public classes with timing for Americas

• Geocomputing: week of 22 November

• Machine Learning: week of 6 December

Public classes with timing for Europe, Africa and Middle East

• Geocomputing: week of 27 September

• Machine Learning: week of 8 November

So far we’ve taught 748 people on the Geocomputing class, and 445 on the Machine Learning class — this wave of new digital scientists is already doing fascinating new work and publishing new research. I’m very excited to see what unfolds over the next year or two!

Find out more about Agile’s public classes by clicking this big button:

A (useless) map of geo-mathematics

Most scientific problems involve at least a bit of maths, even if it’s just adding things up or finding averages.

But some problems require quite a bit of maths, like solving an equation, or throwing vectors around, or even a Fourier transform or two. A lot of people switch off at this point.

Yet other problems require a lot of maths. Maybe we need a finite difference model, a volume integral, or a deep neural network. Most of us back away from the problem at this point and look for a collaborator with a lot of equations on their whiteboard.

But it’s pretty hard to find new collaborators right now. And what if you run into these problems a lot? Maybe you need to be the one with the equationy whiteboard!

What then? Where do you start? We need a map!

A roadmap for learning…

…is what I set out to draw. I failed. Possibly there exists a map, with START HERE in one corner and a whiteboard full of equations in the other. But I doubt it.

I ended up drawing this:

It was fun to draw, but I highly doubt that it’s any practical use. The conclusion I came to is: there is no path. In fact, this artificially flattened projection of the n-dimensional mathiverse — no doubt reflecting my own weak grasp on half of these topics — is probably a unique, personal perspective. It reflects my interests and my nonlinear journey from A-level calculus (which I loved) to undergraduate maths (which I found very hard) to… whatever half-truths I know today.

But I want to learn, where do I start?

So if there is no path, what can you do to improve? Where should you start? How can you learn? Easy: follow your nose. Start with a project — something that interests you, something you’ll stick with. Maybe it’s a spreadsheet you have, or a plot you want to make. When you get to the maths, as you inevitably will, dig in. Read around. Google things. Get a whiteboard.

As an example, when I worked on the tricky (and unsolved!) task of recovering data from pseudocolour images, my maths journey looked something like this:

Images ➡ clustering ➡ RGB vectors ➡ distance metrics ➡ k-d trees ➡ graphs ➡ Hamiltonian paths ➡ TSP solvers

Admittedly, there’s some computer science in there too, but hey, this is applied maths.

As I described recently in Illuminated equations, there are several ways to serve, and consume, mathematical ideas: words, pictures, plots, symbols, annotations, and code (and probably some others). Seek out sources that give you three or more of these things. For me, being able to run some code makes a huge difference. Indeed, learning Python has directly led to me reading entire books on graph theory, linear algebra, deep learning, Fourier transforms, and all sorts of other things.

Well, learning Python and watching Numberphile.

I think it’s a myth that you have to be good at maths to learn to code. Instead, I think learning to code can — if you want — help make you good, or at least better, at maths. By giving you a way to try things without fully knowing what you are doing (after all, np.fft.fft(x) is pretty easy to type!), code gives you a way to peek at the answer. If you do it often enough, and follow up with some reading, understanding follows eventually.

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.)

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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.)

No going back

At last, 2021 is fully underway. There’s a Covid vaccine. The president of the US is not deranged. Brexit is essentially over. We can go back to normal now, right? Soon anyway… after the summer… right?

No.

There is no ‘back’ on this thing, only forward. Even if there was a back, there is no ‘normal’.

So, as comforting as they are, I try to avoid ideas like ‘recovery’, or ‘getting back to normal’. Instead, I look forward to different — and better — things tomorrow.

You can’t go back

In spite of what you might have gathered from a certain Christoper Nolan movie, the arrow of time only points in one direction: from the past to the future. Sometimes this seems scary, because you can’t control the future. But, unlike the past, you can affect it. Specifically, you can improve it.

The price is uncertainty, because we don’t know what the future holds. If you work in the petroleum industry, debilitating uncertainty is a familiar sensation. I feel like people have been looking forward to ‘the recovery’ for as long as I can remember. People refer to the short-period (roughly 5-year) ups and downs as ‘cyclic’, but that’s not what it is. It never returns to its previous state. Ever. It’s more of a spiral in the multi-dimensional universe, never seeing the same world twice. And it’s not a pretty spiral, because it’s not going anywhere in particular (except, in the case of the oil industry, down).

There are no cycles, returning the world to some previous state now and then. Thank goodness! Instead, we have more of a random walk in a high-dimensional space, never returning to the same state. This is absolutely simplistic, and hard to draw in 2D… but you get the idea.

The thing is, the world is a complex system, full of feedback and nonlinearity. Changing one thing changes a hundred other things. So the world after an earth-juddering event like the Covid pandemic is not the same as the world before that event. A great many things have changed completely, for example:

• Working from home means that millions of people have an extra hour or two in their day. That’s hard to roll back.

• Some industries have been crushed (airlines, hospitality), others have exploded (try and buy a bicycle!).

• We’ve been shown a new, more inclusive, more accessible, more sustainable way to run events and conferences.

A nudge to adapt

Even if you could go back, do you want to? Sometimes, of course, it’s human nature. We miss people we’ve lost, or feelings we cherished, and it’s comforting to remember old times. And the future will hold new people and new experiences. But it’s impossible to forget that the ‘good old days’ were not awesome for everyone. The 1970’s were filled with overt racism and sexism. The 1980’s saw unfettered capitalism and the palpable threat of nuclear war. The hey-days of the oil industry were tainted by corruption and frequent environmental catastrophe. No-one wants to go back to those things.

If we think of ourselves as evolving beings, then maybe it helps to look at what’s happening around us as environmental pressure. It’s a nudge — or a series of nudges, and unusually big ones at the moment — to adapt. We (ourselves, our families, our employers, our technical societies) can choose to ignore them and try to get ‘back to normal’ for a while. Or we can pay attention and get ready for whatever is next.

Change you didn’t choose is uncomfortable, even scary. But much of the discomfort comes from shielding yourself from the change — waiting it out with gritted teeth — instead of adapting to it. Adaptation isn’t easy either, it takes daily effort to learn new ways to be productive, acquire new skills to help society, and keep on moving towards the things that bring fulfilment. And I think leaving behind the “back to normal” mindset is step 1.

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What do you think? Are you sticking to the ‘white knuckle’ strategy, or have you started adjusting course? Let us know in the comments.

The evolution of the Software Underground

The Software Underground started as a mailing list in 2014 with maybe twenty participants, in the wake of the first geoscience hackathons. There are now more than 2,160 “rocks + computers” enthusiasts in the Underground, with about 20 currently joining every week. It’s the fastest growing digital subsurface water-cooler in the world! And the only one.

The beating heart of the Software Underground is its free, open Slack chat room. Accessible to anyone, it brings this amazing community right to your mobile device or computer desktop. When it comes to the digital subsurface, it has a far higher signal:noise ratio than LinkedIn, Twitter, or Facebook. Here are some of the topics under discussion this week:

• The role of coding challenges in job interviews.

• Handling null values in 2D grids such as airborne gamma-ray.

• How to load an open seismic dataset into OpendTect.

• A new series of tutorials for the GeoStats.jl Julia package.

• Plenty of discussion about how to interpret negative oil prices!

But the Software Underground — or Swung as its population affectionately call it — is more than just a chatroom. It organizes events. It compiles awesome documents. And it has great ambitions.

Evolution

To better explore those ambitions, the Underground is evolving.

Until now, it’s had a slightly murky existence, or non-existence, operating in mysterious ways and without visible means of support. When we tried to get a ‘non-profit’ booth at a conference last year, we couldn’t because the Software Underground isn’t just a non-profit, it’s a non-entity. It doesn’t legally exist.

Most of the time, this nonexistence is a luxury. No committees! No accounts! No lawyers!

But sometimes it’s a problem. Like when you want to accept donations in a transparent way. Or take sponsorship from a corporation. Or pay for an event venue. Or have some accountability for what goes on in the community. Or make a decision without waiting for Matt to read his email. Sometimes it matters.

A small band of supporters and evangelists have decided the time has come for the Software Underground to stand up and be counted! We’re going legal. We’re going to exist.

What will change?

As little as possible! And everything!

The Slack will remain the same. Free for everyone. The digital subsurface water-cooler (or public house, if you prefer).

We’re taking on our biggest event yet in June — a fully online conference called TRANSFORM 2020. Check it out.

Soon we will exist legally, as we move to incorporate in Canada as a non-profit. Later, we can think about how membership and administration will work. For now, there will be some ‘interim’ directors, whose sole job is to establish the terms of the organization’s existence and get it to its first Annual General Meeting, sometime in 2021.

The goal is to make new things possible, with a new kind of society.

And you’re invited.

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.

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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.

Training digital scientists

Gulp. My first post in… a while. Life, work, chaos, ideas — it all caught up with me recently. I’ve missed the blog greatly, and felt a regular pang of guilt at letting it gather dust. But I’m back! The 200+ draft posts in my backlog ain’t gonna write themselves. Thank you for returning and reading this one.

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Recently I wrote about our continuing adventures in training; since I wrote that post in April, we’ve taught another 166 people. It occurred to me that while teaching scientists to code, we’ve also learned a bit about how to teach, and I wanted to share that too. Perhaps you will be inspired to share your skills, and together we can have exponential impact.

Wanting to get better

As usual, it all started with not knowing how to do something, doing it anyway, then wanting to get better.

We started teaching in 2014 as rank amateurs, both as coders and as teachers. But we soon discovered the ‘teaching tech’ subculture among computational scientists. In particular, we found Greg Wilson and the Software Carpentry movement he started. By that point, it had been around for many, many years. Incredibly, Software Carpentry has helped more than 34,000 researchers ‘go digital’. The impact on science can’t be measured.

Eager as ever, we signed up for the instructor’s course. It was fantastic. The course, taught by Greg Wilson himself, perfectly modeled the thing it was offering to teach you: “Do what I say, and what I do”. This is, of course, critically important in all things, especially teaching. We accepted the content so completely that I’m not even sure we graduated. We just absorbed it and ran with it, no doubt corrupting it on the way. But it works for us.

What to read

I should preface what follows by telling you that I haven’t taken any other courses on the subject of teaching. For all I know, there’s nothing new here. That said, I have never experienced a course like Greg Wilson’s, so either the methods he promotes are not widely known, or they’re widely ignored, or I’ve been really unlucky.

The easiest way to get Greg Wilson’s wisdom is probably to read his book-slash-website, Teaching Tech Together. (It’s free, but you can get a hard copy if you prefer.) It’s really good. You can get the vibe — and much of the most important advice — from the ten Teaching Tech Together rules laid out on the main page of that site (box, right).

As you can probably tell, most of it is about parking your ego, plus most of your knowledge (for now), and orientating everything — every single thing — around the learner.

If you want to go deeper, I also recommend reading the excellent, if rather academic, How Learning Works, by Susan Ambrose (Northeastern University) and others. It’s strongly research-driven, and contains a lot of great advice. In particular, it does a great job of listing the factors that motivate students to learn (and those that demotivate them), and spelling out the various ways in which students acquire mastery of a subject.

How to practice

It goes without saying that you’ll need to teach. A lot. Not surprisingly, we find we get much better if we teach several courses in a short period. If you’re diligent, take a lot of notes and study them before the next class, maybe it’s okay if a few weeks or months go by. But I highly doubt you can teach once or twice a year and get good at it.

Something it took us a while to get comfortable with is what Evan calls ‘mistaking’. If you’re a master coder, you might not make too many mistakes (but your expertise means you will have other problems). If you’re not a master (join the club), you will make a lot of mistakes. Embracing everything as a learning opportunity is less awkward for you, and for the students — dealing with mistakes is a core competency for all programmers.

Reflective practice means asking for, and then acting on, student feedback — every day. We ask students to write it on sticky notes. Reading these back to the class the next morning is a good way to really read it. One of the many benefits of ‘never teach alone’ is always having someone to give you feedback from another teacher’s perspective too. Multi-day courses let us improve in real time, which is good for us and for the students.

Some other advice:

• Keep the student:instructor ratio to no more than ten; seven or eight is better.

• Take a packet of orange and a packet of green Post-It notes. Use them for names, as ‘help me’ flags, and for feedback.

• When teaching programming, the more live coding — from scratch — you can do, the better. While you code, narrate your thought process. This way, students are able to make conections between ideas, code, and mistakes.

• To explain concepts, draw on a whiteboard. Avoid slides whenever possible.

• Our co-teacher John Leeman likes to say, “I just showed you something new, what questions do you have?” This beats “Any questions?” for opening the door to engagement.

• “No-one left behind” is a nice idea, but it’s not always practical. If students can’t devote 100% to the class and then struggle because of it, you owe it to the the others to politely suggest they pick the class up again next time.

• Devote some time to the practical application of the skills you’re teaching, preferably in areas of the participants’ own choosing. In our 5-day class, we devote a whole day to getting students started on their own projects.

• Don’t underestimate the importance of a nice space, natural light, good food, and frequent breaks.

• Recognize everyone’s achievement with a small gift at the end of the class.

• Learning is hard work. Finish early every day.

Give it a try

If you’re interested in help people learn to code, the most obvious way to start is to offer to assist or co-teach in someone else’s class. Or simply start small, offering a half-day session to a few co-workers. Even if you only recently got started yourself, they’ll appreciate the helping hand. If you’re feeling really confident, or have been coding for a year or two at least, try something bolder — maybe offer a one-day class at a meeting or conference. You will find plenty of interest.

There are few better ways to improve your own skills than to teach. And the feeling of helping people develop a valuable skill is addictive. If you give it a try, let us know how you get on!

Feel superhuman: learning and teaching geocomputing

Diego teaching in Houston in 2018.

It’s five years since we started teaching Python to geoscientists. To be honest, it might have been premature. At the time, Evan and I were maybe only two years into serious, daily use of Python. But the first class, at the Atlantic Geological Society’s annual meeting in February 2014, was free so the pressure was not too high. And it turns out that only being a step or two ahead of your students can be an advantage. Your ‘expert blind spot’ is partially sighted not completely blind, because you can clearly remember being a noob.

Being a noob is a weird, sometimes very uncomfortable, even scary, feeling for some people. Many of us are used to feeling like experts, at least some of the time. Happy, feeling like a noob is a core competency in programming. Learning new things is a more or less hourly experience for coders. Even a mature language like Python evolves fast enough that it’s hard to keep up. Instead of feeling threatened or exhausted by this, I think the best strategy is to enjoy it. You’ll never be done, there are (way) more questions than answers, and you can learn forever!

One of the bootcamp groups at the Copenhagen hackathon in 2018

This week we’re teaching our 40th course. Last year alone we gave digital superpowers to 325 people, mostly geoscientists, Not all of them learned to code, as such — some people already could, and some found out theydidn’t like it… coding really isn’t for everyone. But I think all of them learned something new about technology, and how it can serve them and their science. I hope all of them look at spreadsheets, and Petrel, and websites differently now. I think most of them want, at some point, to learn more. And everyone is excited about machine learning.

The expanding community of quantitative earth scientists

This year we’ve already spent 50 days teaching, and taught 174 people. Imagine that! I get emotional when I think about what these hundreds of new digital geoscientists and engineers will go and do with their new skills. I get really excited when I see what they are already doing — when they come to hackathons, send us screenshots, or write papers with beautiful figures. If the joy of sharing code and collaborating with peers has also rubbed off on them, there’s no telling where it could lead.

Matt teaching in Aberdeen in October 2018

The last nine months or so have been an adventure. Teaching is not supposed to be what Agile is about. We’re a consulting company, a technology company. But for now we’re mostly a training company — it’s where we’re needed. And it makes sense... Programming is fundamentally about knowledge sharing. Teaching is about helping, collaborating. It’s perfect for us.

Besides, it’s a privilege and a thrill to meet all these fantastically smart, motivated people and to hear about their projects and their plans. Sometimes I wish it didn’t mean leaving my family in Nova Scotia and flying to Houston and London and Kuala Lumpur and Kalamazoo… but mostly I wish we could do more of it. Especially when we get comments like these:

“Given how ‘dry’ programming can be, it was DYNAMIC.”
”Excellent teachers with geoscience background.”
”Great instructors, so so approachable, even for newbies like me.”
”Great course [...] Made me realize what could be done in a short time.”
”My only regret was not taking a class like this sooner.”
”Very positive, feel superhuman.”

How many times have you felt superhuman at work recently?

The courses we teach are evolving and expanding in scope. But they all come back to the same thing: growing digital skills in our profession. This is critical because using computers for earth science is really hard. Why? The earth is weird. We’ve spent hundreds of years honing conceptual models, understanding deep time, and figuring out complex spatial relationships.

If data science eats the subsurface without us, we’re all going to get indigestion. Society needs to better understand the earth — for all sorts of reasons — and it’s our duty to build and adopt the most powerful analytical tools available so that we can help.

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Learning resources

If you can’t wait to get started, here are some suggestions:

• learnpython.org is a really nice resource for beginners, with interactive tutorials — and not just in Python!

• I took the Udacity CS 101 class with Dave Evans in 2012, and I loved it. I’ve since done other Udacity courses.

• If you’re the book type, Learning With Python by Allen P. Downey is supposed to be great, and it’s free.

• Our X lines of Python blog series has several beginner-friendly lessons. My favourite is the one about wedges. You should also check out the Geophysical Tutorials series in The Leading Edge.

• You might like to get on the public, free Slack Software Underground — there are lots of geo-Python folks there.

Classroom courses are a big investment in dollars and time, but they can get you a long way really quickly. Our courses are built especially for subsurface scientists and engineers. As far as I know, they are the only ones of their kind. If you think you’d like to take one, talk to us, or look out for a public course. You can find out more or sign up for email alerts here >> https://agilescientific.com/training/

Last thing: I suggest avoiding DataCamp, because of sexual misconduct by an executive, compounded by total inaction, dishonest obfuscation, and basically failing spectacularly. Even their own trainers have boycotted them. Steer clear.

The new reality

In Calgary last week I heard the phrase "when the industry recovers" several times. Dean Potter even went so far as to say:

“Don’t believe anyone who says ‘It’s different this time’. It isn’t.”

He knows what he's talking about — the guy sold his company to Vermillion in 2014 for $427 million.

But I think he's dead wrong.

What's different this time?

A complete, or at least non-glacially-slow, recovery seems profoundly unlikely to me. We might possibly be through the 'everything burns to the ground' phase, but the frenzy of mergers and takeovers has barely started. That will take at least a couple of years. If and when any stability returns to operations, it seems highly probable that it will have these features:

1. It will be focused on shale. (Look at the Permian Basin today.)
2. It will need fewer geoscientists. (There are fewer geological risks.)
3. It will be driven by data. (We have barely started on this.)
4. It will end in another crash. (Hungry animals bolt their food.)

If you're a geoscientist and have never worked find-grained plays, I think the opportunities in front of you are going to be different from the ones you're used to. And by 'different', I mean 'scarcer'.

Where else can you look?

It may be time to think about a pivot, if you haven't already. (Pivot is lean-startup jargon for 'plan B' (or C). And I don't think it's a bad idea to think of yourself, or any business, as a start-up. Indeed, if you don't, you're headed for obsolescence.)

What would you pivot to? What's your plan B? If you think of petroleum geoscience as having a position in a matrix, think about our neighbours in that matrix. Industries are vertical; disciplines are horizontal.

Opportunities in neighbouring cells are probably within relatively easy reach. Think about:

• Near surface: archaeology, UXO detection, engineering geophysics.
• Geomatics, remote sensing, and geospatial analysis. Perhaps in mining or geothermal energy.
• Stepping out of industry into education or government. People with applied knowledge have a lot to offer.
• Making contacts in a new industry like finance or medicine. Tip: go to a conference. Talk to everyone you can find.

Think about your technical skills more broadly

I don't know where those new opportunities will come from, but I think it only takes a small shift in perspective to spot them. Think of your purpose, not your tasks. For example:

• Many geophysicists are great quantitative scientists. If you know linear algebra or geostatistics and write code too, you have much sought-after skills in any industry.
• Many geologists are great at spatial analysis. If you can wield geodatabases and GIS software like a wizard, you are a valuable asset to any industry.
• Many engineers are great at project management and analytics. If you have broken out of Excel and can drive Spotfire or Tableau, you are gold in any industry.

If you forgot to keep your skills up to date and are locked into clicking buttons in Petrel, or making PowerPoint maps of the Cardium, or fiddling with charts in Excel, I'm not sure what to tell you. Everyone has those skills. You're yesterday's geoscientist and you don't have a second to lose. 

Working without a job

I have drafted variants of this post lots of times. I've never published them because advice always feels... presumptuous. So let me say: I don't have any answers. But I do know that the usual way of 'finding work' doesn't work any more, so maybe the need for ideas, or just hope, has grown. 

Lots of people are out of work right now. I just read that 120,000 jobs have been lost in the oil industry in the UK alone. It's about the same order of magnitude in Canada, maybe as much as 200,000. Indeed, several of my friends — smart, uber-capable professionals — are newly out of jobs. There's no fat left to trim in operator or service companies... but the cuts continue. It's awful.

The good news is that I think we can leave this downturn with a new, and much better, template for employment. The idea is to be more resilient for 'next time' (the coming mergers, the next downturn, the death throes of the industry, that sort of thing).

The tragedy of the corporate professional 

At least 15 years ago, probably during a downturn, our corporate employers started telling us that we are responsible for our own careers. This might sound like a cop-out, maybe it was even meant as one, but really it's not. Taken at face value, it's a clear empowerment.

My perception is that most professionals did not rise to the challenge, however. I still hear, literally all the time, that people can't submit a paper to a conference, or give a talk, or write a blog, or that they can't take a course, or travel to a workshop. Most of the time this comes from people who have not even asked, they just assume the answer will be No. I worry that they have completely given in; their professional growth curtailed by the real or imagined conditions of their employment.

More than just their missed opportunity, I think this is a tragedy for all of us. Their expertise effectively gone from the profession, these lost scientists are unknown outside their organizations.

Many organizations are happy for things to work out that way, but when they make the situation crystal clear by letting people go, the inequity is obvious. The professional realizes, too late, that the career they were supposed to be managing (and perhaps thought they were managing by completing their annual review forms on time) was just that — a career, not a job. A career spanning multiple jobs and, it turns out, multiple organizations.

I read on LinkedIn recently someone wishing recently let-go people good luck, hoping that they could soon 'resume their careers'. I understand the sentiment, but I don't see it the same way. You don't stop being a professional, it's not a job. Your career continues, it's just going in a different direction. It's definitely not 'on hold'. If you treat it that way, you're missing an opportunity, perhaps the best one of your career so far.

What you can do

Oh great, unsolicited advice from someone who has no idea what you're going through. I know. But hey, you're reading a blog, what did you expect? 

• Do you want out? If you think you might want to leave the industry and change your career in a profound way, do it. Start doing it right now and don't look back. If your heart's not in this work, the next months and maybe years are really not going to be fun. You're never going to have a better run at something completely different.
• You never stop being a professional, just like a doctor never stops being a doctor. If you're committed to this profession, grasp and believe this idea. Your status as such is unrelated to the job you happen to have or the work you happen to be doing. Regaining ownership of our brains would be the silveriest of linings to this downturn.
• Your purpose as a professional is to offer help and advice, informed by your experience, in and around your field of expertise. This has not changed. There are many, many channels for this purpose. A job is only one. I firmly believe that if you create value for people, you will be valued and — eventually — rewarded.
• Establish a professional identity that exists outside and above your work identity. Get your own business cards. Go to meetings and conferences on your own time. Write papers and articles. Get on social media. Participate in the global community of professional geoscientists. 
• Build self-sufficiency. Invest in a powerful computer and fast Internet. Learn to use QGIS and OpendTect. Embrace open source software and open data. If and when you get some contracting work, use Tick to count hours, Wave for accounting and invoicing, and Todoist to keep track of your tasks. 
• Find a place to work — I highly recommend coworking spaces. There is one near you, I can practically guarantee it. Trust me, it's a much better place to work than home. I can barely begin to describe the uplift, courage, and inspiration you will get from the other entrepreneurs and freelancers in the space.
• Find others like you, even if you can't get to a coworking space, your new peers are out there somewhere. Create the conditions for collaboration. Find people on meetup.com, go along to tech and start-up events at your local university, or if you really can't find anything, organize an event yourself! 
• Note that there are many ways to make a living. Money in exchange for time is one, but it's not a very efficient one. It's just another hokey self-help business book, but reading The 4-Hour Workweek honestly changed the way I look at money, time, and work forever.
• Remember entrepreneurship. If you have an idea for a new product or service, now's your chance. There's a world of making sh*t happen out there — you genuinely do not need to wait for a job. Seek out your local startup scene and get inspired. If you've only ever worked in a corporation, people's audacity will blow you away.

If you are out of a job right now, I'm sorry for your loss. And I'm excited to see what you do next.