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 2…

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.


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

Openness is a two-way street

Last week the Data Analysis Study Group of the SPE Gulf Coast Section announced a new machine learning contest (I’m afraid registration is now closed, even though the contest has not started yet). The task is to predict shear-wave sonic from other logs, similar to the SPWLA PDDA contest last year. This is a valuable problem in the subsurface, because shear sonic log is essential for computing elastic properties of rocks and therefore in predicting rock and fluid properties or processing seismic. Indeed, TGS have built a business on predicted logs with their ARLAS product. There’s money in log prediction!

The task looks great, but there’s one big problem: the dataset is not open.

Why is this a problem?

Before answering that, let’s look at some context.

What’s a machine learning contest?

Good question. Typically, an organization releases a dataset (financial timeseries, Netflix viewer data, medical images, or whatever). They invite people to predict some valuable property (when to sell, which show to recommend, how to treat the illness, or whatever). And they pick the best, measured against known labels on a hidden dataset.

Kaggle is one of the largest platforms hosting such challenges, and they often attract thousands of participants — competing for large prizes. TGS ran a seismic salt-picking contest on the platform, attracting almost 74,000 submissions from 3220 teams with a $100k prize purse. Other contests are more grass-roots, like the one I ran with Brendon Hall in 2016 on lithology prediction, and like this SPE contest. It’s being run by a team of enthusiasts without a lot of resources from SPE, and the prize purse is only $1000 — representing about 3 hours of the fully loaded G&A of an oil industry professional.

What has this got to do with reproducibility?

Contests that award a large prize in return for solving a hard problem are essentially just a kind of RFP-combined-with-consulting-job. It’s brutally inefficient: hundreds or even thousands of people spend hours on the problem for free, and a handful are financially rewarded. These contests attract a lot of attention, but I’m not that interested in them.

Community-oriented events like this SPE contest — and the recent FORCE one that Xeek hosted — are more interesting and I believe they are more impactful. They have lots of great outcomes:

  • Lots of people have fun working on a hard problem and connecting with each other.

  • Solutions are often shared after, or even during, the contest, so that everyone learns and grows their toolbox.

  • A new open dataset that might even become a much-needed benchmark for the task in hand.

  • Researchers can publish what they did, or do later. (The SEG ML contest tutorial and results article have 136 citations between them, largely from people revisiting the dataset to show new solutions.)

A lot of new open-source machine learning code is always exciting, but if the data is not open then the work is by definition not reproducible. It seems especially unfair — cheeky, even — to ask participants to open-source their code, but to keep the data proprietary. For sure TGS is interested in how these free solutions compare to their own product.

Well, life’s not fair. Why is this a problem?

The data is being shared with the contest participants on the condition that they may not share it. In other words it’s proprietary. That means:

  • Participants are encumbered with the liability of a proprietary dataset. Sure, TGS is sharing this data in good faith today, but who knows how future TGS lawyers will see it after someone accidentally commits it to their GitHub repo? TGS is a billion-dollar company, they will win a legal argument with you. (Having said that, there’s no NDA or anything, just a checkbox in a form. I don’t know how binding it really is… but I don’t want to be the one that finds out.)

  • Participants can’t publish reproducible papers on their own work. They can publish classic oil-indsutry, non-reproducible work — I did this thing but no-one can check it because I can’t give you the data — but do we really need more of that? (In the contest introductory Zoom, someone asked about publishing plots of the data. The answer: “It should be fine.” Are we really still this naive about data?)

If anyone from TGS is reading this and thinking, “Come on, we’re not going to sue anyone — we’re not GSI! — it’s fine :)” then my response is: Wonderful! In that case, why not just formalize everything by releasing the data under an open licence — preferably Creative Commons Attribution 4.0? (Unmodified! Don’t make the licensing mistakes that Equinor and NAM have made recently.) That way, everyone knows their rights, everyone can safely download the data, and the community can advance. And TGS looks pretty great for contributing an awesome dataset to the subsurface machine learning community.

I hope TGS decides to release the data with an open licence. If they don’t, it feels like a rather one-sided deal to me. And with the arrangement as it stands, there’s no way I would enter this contest.

Are these the heroes we need?

First rule of criticism: balance it with something positive.

Technical societies — AAPG, SEG, SPE, EAGE, and the many others — do important work in our discipline. They publish some quality content, they organize a lot of meetings, and they help attract talent to work in subsurface science and engineering.

The door is wide open for them to play a central role in the change that’s coming to our lives as subsurface professionals.

Second rule of criticism: stick to the facts.

In spite of their central role in many scientists’ professional lives, and the magnitude of the changes that are underway, technical societies have struggled to maintain relevance and therefore members. It’s hard to know the extent of the problem, as AAPG doesn’t report how many members it has (it’s been “approximately 30,000” for years) and SEG stopped reporting numbers in 2017. Make of that what you will.

Anecdotally, many of my friends have let their memberships lapse. I have too.

Third rule of criticism: avoid negative language.

AAPG came up with a couple of cool superheroes. They commissioned some artwork: two fit, handsome geologists, ready for anything. Their names? Trap Mitchell and Alluvia Hunt.

AAPG_Trap_and_Alluvia.jpg

The laudable appearance of a woman — a non-white woman! — in this context rightly prompted praise:

How appalling is it that a geoscientist had to wait 23 years to see a female geoscientist take centre stage like this? I’m embarrassed by that. Kudos to AAPG for that decision.

Kudos which we have to partially revoke, unfortunately. Because the decision, if it was a decision, to change Alluvia’s skin colour in different situations is… well, it doesn’t look good. At best, it’s weird.

Fourth rule of criticism: be honest.

When I saw this dynamic duo, I rolled my eyes. Of course I did: I’m predisposed to criticize the technical societies and I’m a well-known marketing whiner. And as a scientist in Software Underground pointed out, it’s not targeted at me; she also found it uplifting. (Obvious in hindsight, but the whole point of my various privileges is that everything seems to be about me — it’s good to be reminded of our blindspots.)

But I’m trying to be positive here. I rolled my eyes because I think AAPG and the other societies can have a far-reaching and positive impact on our community, and on society. There is hard work to be done finding enough energy and raw materials for people to prosper.


The door is wide open

If AAPG wants to be part of the future, they have to figure out what ‘relevant’ means. Being relevant does not mean:

  • Promoting oil & gas exploration with dysmorphic Barbie & Ken super-hero cartoon characters.

  • Paywalled everything, especially journals and conference papers.

  • Awards named after men and given to mostly men. And don’t get me started on ‘Distinguished’ people.

  • Doing all the other things you’ve always done which have led you to feel ‘not relevant’ today.

I would urge AAPG and all technical societies to consider becoming more relevant in some new ways:

  • Understand that oil & gas, while certainly important to society today, needs to end. The sooner the better.

  • Realize that subsurface professionals can contribute to society, and industry, in hundreds of other ways.

  • See that this change is going to require a massive educational effort, both for us, and for society.

  • Believe that we need to massively broaden our community if we are to have the impact we can have.

  • Remove barriers to knowledge by committing to open access content and open data.

  • Remove barriers to participation by welcoming and representing everyone with equity and compassion.

The days of the hero explorer — tanned and lean, chiselled and serious, whacking stuff with hammers — are gone. Really, they never existed, or at least they were accompanied by a masculine monoculture and a total neglect for the environment.

The future can be different. Ms Hunt and Trap can be part of it. I believe we all can. But it’s going to require hard work, uncomfortable decisions, and abrupt, profound change. The door is wide open for AAPG, SEG, EAGE, and the other technical societies, if they would only notice.


What do you think? Are Trap & Alluvia just a bit of fun that might attract a new generation? Or do our technical societies need a lot more than cartoon heros and heroines? Let us know in the comments.