Seismic quality traffic light

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We like to think that our data are perfect and limitless, because experiments are expensive and scarce. Only then can our interpretations hope to stand up to even our own scrutiny. It would be great if seismic data was a direct representation of geology, but it never is. Poor data doesn't necessarily mean poor acquisition or processing. Sometimes geology is complex!

In his book First Steps in Seismic Interpretation, Don Herron describes a QC technique of picking a pseudo horizon at three different elevations to correspond to poor, fair, and good data regions. I suppose that will do in a pinch, but I reckon it would take a long time, and it is rather subjective. Surely we can do better?

Computing seismic quality

Conceptually speaking, the ease of interpretation depends on things we can measure (and display), like coherency, bandwidth, amplitude strength, signal-to-noise, and so on. There is no magic combination of filters that will work for all data, but I am convinced that for every seismic dataset there is a weighted function of attributes that can be concocted to serve as a visual indicator of the data complexity:

So one of the first things we do with new data at Agile is a semi-quantitative assessment of the likely ease and reliability of interpretation.

This traffic light display of seismic data quality, corendered here with amplitude, is not only a precursor to interpretation. It should accompany the interpretation, just like an experiment reporting its data with errors. The idea is to show, honestly and objectively, where we can trust eventual interpretations, and where they not well constrained. A common practice is to cherry pick specific segments or orientations that support our arguments, and quietly suppress those that don't. The traffic light display helps us be more honest about what we know and what we don't — where the evidence for our model is clear, and where we are relying more heavily on skill and experience to navigate a model through an area where the data is unclear or unconvincing.

Capturing uncertainty and communicating it in our data displays is not only a scientific endeavour, it is an ethical one. Does it change the way we look at geology if we display our confidence level alongside? 

Reference

Herron, D (2012). First Steps in Seismic Interpretation. Geophysical Monograph Series 16. Society of Exploration Geophysicists, Tulsa, OK.

The seismic profile shown in the figure is from the Kennetcook Basin, Nova Scotia. This work was part of a Geological Survey of Canada study, available in this Open File report.

What is Creative Commons?

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Not a comprehensive answer either, but much more brilliantI just found myself typing a long email in reply to the question, "What is a Creative Commons license and how do I use it?" Instead, I thought I'd post it here. Note: I am not a lawyer, and this is not a comprehensive answer.

Creative Commons depends on copyright

There is no relinquishment of copyright. This is important. In the case of 52 Things, Agile Geoscience is the copyright holder. In the case of an article, it's the authors themselves, unless the publisher gets them to sign a form relinquishing it. Copyright is an automatic, moral right (under the Berne Convention), and boils down to the right to be identified as the authors of the work ('attribution').

Most copyright holders grant licenses to re-use their work. For instance, you can pay hundreds of dollars to reproduce a couple of pages from an SPE manual for a classroom of students (if you are insane). You can reprint material from a book or journal article — again, usually for a fee. These licenses are usually non-exclusive, non-transferable, and use-specific. And the licensee must (a) ask and (b) pay the licensor (that is, the copyright holder). This is 'the traditional model'.

Obscurity is a greater threat than piracy

Some copyright holders are even more awesome. They recognize that (a) it's a hassle to always have to ask, and (b) they'd rather have the work spread than charge for it and stop it spreading. They wish to publish 'open' content. It's exactly like open source software. Creative Commons is one, very widespread, license you can apply to your work that means (a) they don't have to ask to re-use it, and (b) they don't have to pay. You can impose various restrictions if you must.

Creative Commons licenses are everywhere. You can apply Creative Commons licenses at will, to anything you like. For example, you can CC-license your YouTube videos or Flickr photos. We CC-license our blog posts. Almost everything in Wikipedia is CC-licensed. You could CC-license a single article in a magazine (in fact, I somewhat sneakily did this last February). You could even CC-license a scientific journal (imagine!). Just look at all the open content in the world!

Creative Commons licenses are easy to use. Using the license is very easy: you just tell people. There is no cost or process. Look at the footer of this very page, for example. In print, you might just add the line This article is licensed under a Creative Commons Attribution license. You may re-use this work without permission. See http://creativecommons.org/licenses/by/3.0/ for details. (If you choose another license, you'd use different wording.)

Creative_Commons.jpg

I recommend CC-BY licenses. There are lots of open licenses, but CC-BY strikes a good balance between being well-documented and trusted, and being truly open (though it is not recognized as such, on a technicality, by copyfree.org). The main point is that they are very open, allowing anyone to use the work in any way, provided they attribute it to the author and copyright holder — it's just like scientific citation, in a way.

Do you openly license your work? Or do you wish more people did? Do you notice open licenses?

Creative Commons graphic by Flickr user Michael Porter. The cartoon is from Nerdson, and licensed CC-BY. 'Obscurity is a greater threat than piracy' is paraphrased from a quote by Tim O'Reilly, publishing 2.0 legend. 

Back to work

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This post first appeared as a chapter in 52 Things You Should Know About Geophysics (Agile Libre, 2012 — also at Amazon). To follow up on Back to school on Tuesday, I thought I'd share it here on the blog. It's aimed at young professionals, but to be honest, I could do with re-reading it myself now and again...

Five things I wish I'd known

For years I struggled under some misconceptions about scientific careers and professionalism. Maybe I’m not particularly enlightened, and haven't really woken up to them yet, and it's all obvious to everyone else, but just in case I am, I have, and it's not, here are five things I wish I'd known at the start of my career.

Always go the extra inch. You don't need to go the extra mile — there often isn't time and there's a risk that no one will notice anyway. An inch is almost always enough. When you do something, like work for someone or give a presentation, people only really remember two things: the best thing you did, and the last thing you did. So make sure those are awesome. It helps to do something unexpected, or something no one has seen before. It is not as hard as you'd think — read a little around the edges of your subject and you'll find something. Which brings me to...

Read, listen, and learn. Subscribe to some periodicals, preferably ones you will actually enjoy reading. You can see my favourites in J is for Journal. Go to talks and conferences, as often as you reasonably can. But, and this is critical, don't just go — take part. Write notes, ask questions, talk to presenters, discuss with others afterwards. And learn: do take courses, but choose them wisely. In my experience, most courses are not memorable or especially effective. So ask for recommendations from your colleagues, and make sure there is plenty of hands-on interaction in the course, preferably on computers or in the field. Good: Dan Hampson talking you through AVO analysis on real data. Bad: sitting in a classroom watching someone derive equations.

Write, talk, and teach. The complement to read, listen, and learn. It's never too early in your career to start — don't fall into the trap of thinking no one will be interested in what you do, or that you have nothing to share. Even new graduates have something in their experience that nobody else has. Technical conference organizers are desperate for stories from the trenches, to dilute the blue-sky research and pseudo-marketing that most conferences are saturated with. Volunteer to help with courses. Organize workshops and lunch-and-learns. Write articles for Recorder, First Break, or The Leading Edge. Be part of your science! You'll grow from the experience, and it will help you to...

Network, inside and outside your organization. Networking is almost a dirty word to some people, but it doesn’t mean taking people to hockey games or connecting with them on LinkedIn. By far the best way to network is to help people. Help people often, for free, and for fun, and it will make you memorable and get you connected. And it's easy: at least 50 percent of the time, the person just needs a sounding board and they quickly solve their own problem. The rest of the time, chances are good that you can help, or know someone who can. Thanks to the Matthew Effect, whereby the rich get richer, your network can grow exponentially this way. And one thing is certain in this business: one day you will need your network.

Learn to program. You don't need to turn yourself into a programmer, but my greatest regret of my first five years out of university is that I didn't learn to read, re-use, and write code. Read Learn to program to find out why, and how.

Do you have any advice for new geoscientists starting out in their careers? What do you wish you'd known on Day 1?

Back to school

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My children go back to school this week. One daughter is going into Grade 4, another is starting kindergarten, and my son is starting pre-school at the local Steiner school. Exciting times.

I go all misty-eyed at this time of year. I absolutely loved school. Mostly the learning part. I realize now there are lots of things I was never taught (anything to do with computers, anything to do with innovation or entrepreneurship, anything to do with blogging), but what we did cover, I loved. I'm not even sure it's learning I like so much — my retention of facts and even concepts is actually quite bad — it's the process of studying.

Lifelong learning

Naturally, the idea of studying now, as a grown-up and professional, appeals to me. But I stopped tracking courses I've taken years ago, and actually now have stopped doing them, because most of them are not very good. I've found many successful (that is, long running) industry courses to be disappointingly bad — long-running course often seems to mean getting a tired instructor and dated materials for your $500 per day. (Sure, you said the course was good when you sis the assessment, but what did you think a week later? A month, a year later? If you even remember it.) I imagine it's all part of the 'grumpy old man' phase I seem to have reached when I hit 40.

But I am grumpy no longer! Because awesome courses are back...

So many courses

Last year Evan and I took three high quality, and completely free, massive online open courses, or MOOCs:

There aren't a lot of courses out there for earth scientists yet. If you're looking for something specific, RedHoop is a good way to scan everything at once.

The future

These are the gold rush days, the exciting claim-staking pioneer days, of massive online open courses. Some trends:

There are new and profound opportunities here for everyone from high school students to postgraduates, and from young professionals to new retirees. Whether you're into teaching, or learning, or both, I recommend trying a MOOC or two, and asking yourself what the future of education and training looks like in your world.

The questions is, what will you try first? Is there a dream course you're looking for?