Quantifying the earth

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I am in Avon, Colorado, this week attending the SEG IQ Earth Forum. IQ (integrative and quantitative) Earth is a new SEG committee formed in reponse to a $1M monetary donation by Statoil to build a publicly available, industrial strength dataset for the petroleum community. In addition to hosting a standard conference format of podiums and Q and A's, the SEG is using the forum to ask delegates for opinions on how to run the committee. There are 12 people in attendance from consulting & software firms, 11 from service companies, 13 who work for operators, and 7 from SEG and academia. There's lively discussionafter each presentation, which has twice been cut short by adherence to the all important 2 hour lunch break. That's a shame. I wish the energy was left to linger. Here is a recap of the talks that have stood out for me so far:

Yesterday, Peter Wang from WesternGeco presented 3 mini-talks in 20 minutes showcasing novel treatments of uncertainty. In the first talk he did a stochastic map migration of 500 equally probable anisotropic velocity models that translated a fault plane within a 800 foot lateral uncertainty corridor. The result was even more startling on structure maps. Picking a single horizon or fault is wrong, and he showed by how much. Secondly, he showed a stocastic inversion using core, logs and seismic. He again showed the results of hundreds of non-unique but equally probable inversion realizations, each exactly fit the well logs. His point: one solution isn't enough. Only when we compute the range of possible answers can we quantify risk and capture our unknowns. Third, he showed an example from a North American resource shale, a setting where seismic methods are routinely under-utilized, and ironically, a setting where 70% of the production comes from less than 30% of the completed intervals. The geomechanical facies classification showed compelling frac barriers and non reservoir classes, coupled to an all-important error cube, showing the probability of each classification, the confidence of the method.

Ron Masters, from a software company called Headwave, presented a pre-recorded video demonstration of his software in action. Applause goes to him for a pseudo-interactive presentation. He used horizons as a boundary for scuplting away peripheral data for 3D AVO visualizations. He demostrated the technique of rotating a color wheel in the intercept-gradient domain, such that any and all linear combinations of AVO parameters can be mapped to a particular hue. No more need for hard polygons. Instead, with gradational crossplot color classes, the AVO signal doesn't get suddenly clipped out, unless there is a real change in fluid and lithology effects. Exposing AVO gathers in this interactive environment guards against imposing false distinctions that aren’t really there. 

The session today consisted of five talks from WesternGeco / Schlumberger, a powerhouse of technology who stepped up to show their heft. Their full occupancy of the podium today, gives a new meaning to the rhyming quip; all-day Schlumberger. Despite having the bias of an internal company conference, it was still very entertaining, and informative. 

Andy Hawthorn showed how seismic images can be re-migrated around the borehole (almost) in real time by taking velocity measurements while drilling. The new measurements help drillers adjust trajectories and mud weights entering hazardous high pressure which has remarkable safety and cost benefits. He showed a case where a fault was repositioned by 1000 vertical feet; huge implications for wellbore stability, placing casing shoes, and other such mechanical considerations. His premise is that the only problem worth our attention is the following: it is expensive to drill and produce wells. Science should not be done for the sake of it; but to build usable models for drillers. 

In a characteristically enthusiastic talk, Ran Bachrach showed how he incorporated a compacting shale anisotropic rock physics model with borehole temperature and porosity measurements to expedite empirical hypothesis testing of imaging conditions. His talk, like many before him throughout the Forum, touched on the notion of generating many solutions, as fast as possible. Asking questions of the data, and being able to iterate. 

At the end of the first day, Peter Wang stepped boldy back to the to the microphone while others has started packing their bags, getting ready to leave the room. He commented that what an "integrated and quantitative" earth model desperately needs are financial models and simulations. They are what drive this industry; making money. As scientists and technologists we must work harder to demonstrate the cost savings and value of these techniques. We aren't getting the word out fast enough, and we aren't as relevant as we could be. It's time to make the economic case clear.

The power of stack

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Multiplicity is a basic principle of seismic acquisition. Our goal is to acquite lots of traces—lots of spatial samples—with plenty of redundancy. We can then exploit the redundancy, by mixing traces, sacrificing some spatial resolution for increased signal:noise. When we add two traces, the repeatable signal adds constructively, reinforcing and clarifying. The noise, on the other hand, is spread evenly about zero and close to random, and tends to cancel itself. This is why you sometimes hear geophysicists refer to 'the power of stack'. 

Here's an example. There are 20 'traces' of 100-digit-long sequences of random numbers (white noise). The numbers range between –1 and +1. I added some signal to samples 20, 40, 60 and 80. The signals have amplitude 0.25, 0.5, 0.75, and 1. You can't see them in the traces, because these tiny amplitudes are completely hidden by noise. The stacked trace on the right is the sum of the 20 noisy traces. We see mostly noise, but the signal emerges. A signal of just 0.5—half the peak amplitude of the noise—is resolved by this stack of 20 traces; the 0.75 signal stands out beautifully.

Here's another example, but with real data. This is part of Figure 3 from Liu, G, S Fomel, L Jin, and X Chen (2009). Stacking seismic data using local correlation. Geophysics 74 (2) V43–V48. On the left is an NMO-corrected (flattened) common mid-point gather from a 2D synthetic model with Gaussian noise added. These 12 traces each came from a single receiver, though in this synthetic case the receiver was a virtual one. Now we can add the 12 traces to get a single trace, which has much stronger signal, relative to the background noise, than any of the input traces. This is the power of stack. In the paper, Liu et al. improve on the simple sum by weighting the traces adaptively. Click to enlarge.

The number of traces available for the stack is called fold. The examples above have folds of 20 and 12. Geophysicists like fold. Fold works. Let's look at another example.

Above, I've made a single digit 1 with 1% opacity — it's almost invisible. If I stack two 2s, with a little random jitter, the situation is still desperate. When I have five digits, I can at least see the hidden image with some fidelity. However, if I add random noise to the image, a fold of 5 is no longer enough. I need at least 10, and ideally more like 20 images stacked up to see any signal. So it is for seismic data: to see through the noise, we need fold.

Now you know a bit about why we want more traces from the field, next time I'll look at how much those traces cost, and how to figure out how many you need. 

Thank you to Stuart Mitchell of Calgary for the awesome analogy for seismic fold.  

Great geophysicists #4: Fermat

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This Friday is Pierre de Fermat's 411th birthday. The great mathematician was born on 17 August 1601 in Beaumont-de-Lomagne, France, and died on 12 January 1665 in Castres, at the age of 63. While not a geophysicist sensu stricto, Fermat made a vast number of important discoveries that we use every day, including the principle of least time, and the foundations of probability theory. 

Fermat built on Heron of Alexandria's idea that light takes the shortest path, proposing instead that light takes the path of least time. These ideas might seem equivalent, but think about anisotropic and inhomogenous media. Fermat continued by deriving Snell's law. Let's see how that works.

We start by computing the time taken along a path:

Then we differentiate with respect to space. This effectively gives us the slope of the graph of time vs distance.

We want to minimize the time taken, which happens at the minimum on the time vs distance graph. At the minimum, the derivative is zero. The result is instantly recognizable as Snell's law:

Maupertuis's generalization

The principle is a core component of the principle of least action in classical mechanics, first proposed by Pierre Louis Maupertuis (1698–1759), another Frenchman. Indeed, it was Fermat's handling of Snell's law that Maupertuis objected to: he didn't like Fermat giving preference to least time over least distance.

Maupertuis's generalization of Fermat's principle was an important step. By the application of the calculus of variations, one can derive the equations of motion for any system. These are the equations at the heart of Newton's laws and Hooke's law, which underlie all of the physics of the seismic experiment. So, you know, quite useful.

Probably very clever

It's so hard to appreciate fundamental discoveries in hindsight. Together with Blaise Pascal, he solved basic problems in practical gambling that seem quite straightforward today. For example, Antoine Gombaud, the Chevalier de Méré, asked Pascal: why is it a good idea to bet on getting a 1 in four dice rolls, but not on a double-1 in twenty-four? But at the time, when no-one had thought about analysing problems in terms of permutations and combinations before, the solutions were revolutionary. And profitable.

For setting Snell's law on a firm theoretical footing, and introducing probability into the world, we say Pierre de Fermat (pictured here) is indeed a father of geophysics.

Lower case j

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This morning I was looking over the schedule for the SEG IQ Earth Forum and a 35 minute block of time caught my eye. Did they not have enough talks to fill the morning? Perhaps. So instead a discussion: Do we need an Interpretation Journal?


What a cool idea! The book versus the machine. Deliberate and community-supported penmanship for scientists to connect with their work. A hand-crafted symbol of romantic scripture in the midst of the sound and fury of a working realm infested with white noise and draining digital abstractions. Old school fights back against tech. Getting back in touch with the analog world, chronicling observations, geologic doodles, jotting down questions and nonsense precisely at the teachable moment.

The da Vinci of seismic interpretation?

I wondered how many other interpreters might be longing for the same thing. Surely if it is to take up a slot in the conference agenda, there must be some ample demand from the geophysical workforce. I want to be a part of it. I start early. I built a wiki page, a series of notes to corral group action and discussion, somewhat naïvely anticipating roaring praise for my inititiative. Most folks have notebooks with shopping lists, and phone messages. But a dedicated, deliberate interpretation journal is refreshing. Just me, my thoughts, and my project. Me getting back in touch with my cursive.

Just now, I realize, while instant-messaging with Matt on Skype, that it is not a Diary the conference organizers are after, it's a Journal. Capital J. As in publication entity. A Journal for Interpreters. Huh. Well, I guess that'd be good too.

The image of Leonardo da Vinci's journal was modified from an original photograph by user Twid on Flickr. Click the image to view the original.

When to use vectors not rasters

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In yesterday's post, I looked at advantages and disadvantages of various image formats. Some chat ensued in the comments and on Twitter about making drawings and figures and such. I realized I hadn't been very clear: when I say 'image', I really mean 'raster' or 'bitmap'. That is, a discretized (pixel-based) grid of data.

What are vector graphics?

Click to enlarge — see a simulation of the difference between vector and raster art.What I was not writing about was drawings and graphics combining text, lines, and images. Such files usually contain vector graphics. Vector graphics do not contain descriptions of pixels, but instead they contain descriptions and positions of text, paths, and polygons. Example file formats are:

  • SVG — Scalable Vector Graphics, an open format and web standard
  • AI — a proprietary format used by Adobe Illustrator
  • CDR — CorelDRAW's proprietary format
  • PPT — pictures in Microsoft PowerPoint are vector format
  • SHP — shapefiles are a (mostly) generic vector format for GIS

One of the most important properties of vector graphics is that you can rescale it without worrying about changing the resolution — as in the example (right).

What are composite formats?

Vector and raster graphics can be combined in all sorts of ways, and vector files can contain raster images. They can therefore be used for very large displays like posters. But vector files are subject to interpretation by different software, may be proprietary, and have complex features like guides and layers that you may not want to expose to someone else. So when you publish or share your work it's often a good idea to export to either a high-res PNG, or a composite page description format:

  • PDF — Portable Document Format, the closest thing to an open, ubiquitous format; stable and predictable.
  • EPS — Encapsulated PostScript; the precursor to PDF, it's rarely called for today, unless PDF is giving you problems.
  • PS — PostScript is a programming and page description language underlying EPS and PDF; avoid it.
  • CGM — Computer Graphics Metafiles are best left alone. If you are stuck with them, complain loudly.

What software do I need?

Any time you want to add text, or annotation, or anything else to a raster, or you wish to create a drawing from scratch, vector formats are the way to go. There are several tools for creating such graphics:

Judging by figures I see submitted to journals, some people use Microsoft PowerPoint for creating vector graphics. For a simple figure, this may be fine, but for anything complex — curved or wavy lines, complicated filled objects, image effects, pattern fills — it is hard work. And the drawing tools listed above have some great advantages over PowerPoint — layers, tracing, guides, proper typography, and a hundred other things.

Plus, and perhaps I'm just being a snob here, figures created in PowerPoint make it look like you just don't care. Do yourself a favour: take half a day to teach yourself to use Inkscape, and make beautiful figures for the rest of your career.

How to choose an image format

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Choosing a file format for scientific images can be tricky. It seems simple enough on the outside, but the details turn out to be full of nuance and gotchas. Plenty of papers and presentations are spoiled by low quality images. Don't let yours be one! Get to know your image editor (I recommend GIMP), and your formats.

What determines quality?

The factors determining the quality of an image are:

  • The number of pixels in the image (aim for 1 million)
  • The size of the image (large images need more pixels)
  • If the image is compressed, e.g. a JPG, the fidelity of the compression (use 90% or more)
  • If the image is indexed, e.g. a GIF, the number of colours available (the bit-depth)

Beware: what really matters is the lowest-quality version of the image file over its entire history. In other words, it doesn't matter if you have a 1200 × 800 TIF today, if this same file was previously saved as a 600 × 400 GIF with 16 colours. You will never get the lost pixels or bit-depth back, though you can try to mitigate the quality loss with filters and careful editing. This seems obvious, but I have seen it catch people out.

JPG is only for photographs

Click on the image to see some artifacts.The problem with JPG is that the lossy compression can bite you, even if you're careful. What is lossy compression? The JPEG algorithm makes files much smaller by throwing some of the data away. It 'decides' which data to discard based on the smoothness of the image in the wavenumber domain, in which the algorithm looks for a property called sparseness. Once discarded, the data cannot be recovered. In discontinuous data — images with lots of variance or hard edges — you might see artifacts (e.g. see How to cheat at spot the difference). Bottom line: only use JPG for photographs with lots of pixels.

Formats in a nutshell

Rather than list advantages and disadvantages exhaustively, I've tried to summarize everything you need to know in the table below. There are lots of other formats, but you can do almost anything with the ones I've listed... except BMP, which you should just avoid completely. A couple of footnotes: PGM is strictly for geeks only; GIF is alone in supporting animation (animations are easy to make in GIMP). 

All this advice could have been much shorter: use PNG for everything. Unless file size is your main concern, or you need special features like animation or georeferencing, you really can't go wrong.

There's a version of this post on SubSurfWiki. Feel free to edit it!

News of the month

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Our semi-regular news round-up from the greenbelt between geoscience and technology.

OpendTect 4.4

Our favourite volume interpretation tool, OpendTect, moved to version 4.4 in June. It seems to have skipped 4.3 completely, which never made it into a stable release. With the new version come 3 new plug-ins: Seismic Net Pay, Seismic Feature Enhancement, and Computer Log Analysis Software (right)—we're looking forward to playing with that.

The cutting edge of interpretation

A new SEG event aimed especially at quantitative interpreters is coming later this month — the SEG IQ Earth Forum. Have a look at the technical program. Evan will be there, and is looking forward to some great discussion, and finding out more about Statoil's open Gullfaks dataset. On the last day, he will be talking about Agile's workflow for interpreting seismic in geothermal fields... stay tuned.

Geoscience freeware

We read in OilIT that US consultancy Ryder Scott has updated its Reservoir Solutions tools for Excel. These include Volumetrics, QuickLook Economics, Gas Material Balance, and LogWizard. If you try them out, do let us know what you think of them!

New iPad apps

Geoscience is perhaps a little slow picking up on the tablet revolution, but mobile apps are trickling out. We love seeing experiments like Pocket Seis, by Houston-based geoscientist-developer Jacob Foshee. And it's interesting to see what the more established software-makers do on these platforms... we think Landmark's OpenWells Mobile app looks rather tame.

This regular(ish) news feature is for information only. We aren't connected with any of these organizations, and don't necessarily endorse their products or services. Except OpendTect, which we do endorse, cuz it's awesome. The screenshot from CLAS is a low-res fair-use image for illustration only, and copyright of dGB Earth Sciences. 

What technology?

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This is my first contribution to the Accretionary Wedge geology themed community blog. Charles Carrigan over at Earth-like Planet is hosting this months topic where he posts the question, "how do you perceive technology impacting the work that you do?" My perception of technology has matured, and will likely continue to change, but here are a few ways in which technology works for us at Agile. 

My superpower

I was at a session in December where one of the activities was to come up with one (and only one) defining superpower. A comic-bookification of my identity. What is the thing that defines you? The thing that you are or will be known for? It was an awkward experience for most, a bold introspection to quickly pull out a memorable, but not too cheesy, superpower that fit our life. I contemplated my superhuman intelligence, and freakish strength... too immodest. The right choice was invisibility. That's my superpower. Transparency, WYSIWYG, nakedness, openness. And I realize now that my superpower is, not coincidentally, aligned with Agile's approach to technology. 

For some, technology is the conspicuous interface between us and our work. But conspicuous technology constrains your work, ordains it even. The real challenge is to use technology in a way that makes it invisible. Matt reminds me that how I did it isn't as important as what I did. Making the technology seem invisible means the user must be invisible as well. Ultimately, tools don't matter—they should slip away into the whitespace. Successful technology implementation is camouflaged. 

I is for iterate

Technology is not a source of ideas or insights, such as you'd find in the mind of an experienced explorationist or in a detailed cross-section or map. I'm sure you could draw a better map by hand. Technology is only a vehicle that can deliver the mind's inner constructs; it's not a replacement for vision or wisdom. Language or vocabulary has nothing to do with it. Technology is the enabler of iteration. 

So why don't we iterate more in our scientific work? Because it takes too long? Maybe that's true for a hand-drawn contour map, but technology is reducing the burden of iteration. Because we have never been taught humility? Maybe that stems from the way we learned to learn: homework assignments have exact solutions (and are done only once), and re-writing an exam is unheard of (unless you flunked it the first time around).

What about writing an exam twice to demonstrate mastery? What about reading a book twice, in two different ways? Once passively in your head, and once actively—at a slower pace, taking notes. I believe the more ways you can interact with your media, data, or content, the better work will be done. Students assume that the cost required to iterate outweighs the benefits, but that is no longer the case with digital workflows. Embracing technology's capacity to iterate seemlessly and reliably is what a makes a grand impact in our work.

What do we use?

Agile strives to be open as a matter of principle, so when it comes to software we go for open source by default. Matt wrote recently about the applications and workstations that we use. 

First class in India

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I wrote this post yesterday morning, sitting in the Indira Ghandi International Airport in Delhi, India.

Where am I?

I'm in India. Some quick facts:

I met some of these recent graduates last week, in an experimental corporate training course. Cairn India has been running a presentation skills course for several years, provided by a local trainer called Yadhav Mehra. Yadhav is a demure, soft-spoken man, right up until he stands up in front of his students. Then he becomes a versatile actor and spontaneous stand-up, swerving with the confidence of a Delhi cab driver between poignant personal stories and hilarious what-not-to-do impressions. I’ve been on the receiving end of plenty of courses before, but Yadhav really made me see ‘training’ as a profession in itself, with skills and standards of its own. I am grateful for that.

How did I end up here?

Serendipity is a wonderful thing. Last fall, Susan Eaton—whom I’d met in the pub after teaching for the first time—wrote a nice piece about my then-new writing course. One of my long-lost PhD supervisors, Stuart Burley, read this article in his office at Cairn India in Delhi, and it triggered a thought. He had Yadhav, a pro trainer, helping his super-bright geoscience and engineering grads with their presentation skills, but they also needed coaching in writing. 

Their education provides them with...

the traditional written communication vernacular employed in the physical sciences, in which exposition is lengthily embellished with extraneous verbiage, and the passivum, or passive voice in its not uncommon appellation, is unfailingly and rigorously exercised.

You get my point. Stuart’s thought was: let’s do combine the two courses!

What happened?

The great thing about Stuart is that, along with breadth of experience and penetrating geological insight, he’s practical—he gets stuff done. (Like almost everything else in my dim-witted student days, I didn’t appreciate how valuable this was at the time.) So the three of us planned a 3-day course that combined my day's worth of writing coaching with Yadhav's two-day presentation course. Yadhav brought some didactic rigour, and I brought some technical depth. Like all collectable first edition, it had some rough edges, but it went beautifully. Students wrote an extended abstract for a conference paper on Tuesday, then presented their paper on Thursday—they made a great effort, and all did brilliantly.

I hope we run the course again—I'd love to see it reach its full potential. 

In the meantime, if you're interested in exploring ways to get more people in your organization writing a little better, or a little more often, do get in touch! You can find out more here. 

The evolution of open mobile geocomputing

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A few weeks ago I attended the EAGE conference in Copenhagen (read my reports on Day 2 and Day 3). I presented a paper at the open source geoscience workshop on the last day, and wanted to share it here. I finally got around to recording it:

As at the PTTC Open Source workshop last year (Day 1, Day 2, and my presentation), I focused on mobile geocomputing — geoscience computing on mobile devices like phones and tablets. The main update to the talk was a segment on our new open source web application, Modelr. We haven't written about this project before, and I'd be the first to admit it's rather half-baked, but I wanted to plant the kernel of awareness now. We'll write more on it in the near future, but briefly: Modelr is a small web app that takes rock properties and model parameters, and generates synthetic seismic data images. We hope to use it to add functionality to our mobile apps, much as we already use Google's chart images. Stay tuned!

If you're interested in seeing what's out there for geoscience, don't miss our list of mobile geoscience apps on SubSurfWiki! Do add any others you know of.