News of the week

Dips from pics

In collaboration with the Geological Survey of Canada, Pangaea Software have built a very nifty tool, Orion, for computing dip from satellite images and digital elevation models. With these two pieces of data, and some assumptions about scale, it's possible to deduce the dip of strata without getting your boots muddy. Matt heard all about this tool from the GSC collaborator, Paul Budkewitsch, at the 3P Arctic conference in Halifax last week; here's their abstract. 

Ocean bottom investment

CGGVeritas has made a commitment to manufacture 800 new Trilobit four-component deepwater nodes for seismic acquisition, to add to its existing pool. The device has three oriented accelerometers plus a hydrophone in addition to an onboard battery and recording system. This all-in-one design can be deployed on the seabed by most ROVs, making it easy to place near platforms and other infrastructure that towed streamer and cable systems cannot access. 

Arguably the industry leader in cableless systems is FairfieldNodal, who are already deploying more than a thousand nodes. It's great to see a big player like CGGVeritas coming to compete with this potentially transformative technology.

Update for Insight Earth

Colorado-based software company TerraSpark has just announced the release of Insight Earth 1.6, an integrated volume interpretation tool. Enhancements include a more interactive data import and export interface, improved velocity modeling, and upgrades to the automated fault extraction. In a January post, Evan highlighted an article by Stan Hammon of TerraSpark on the computational and psychological factors affecting intellegent design. It's inspired stuff.

Re-introducing SubSurfWiki

AgileWiki is now SubSurfWiki, at subsurfwiki.org. Please change your bookmarks! We felt that it was a little too Agile-centric and want to appear as open web-space for anything subsurface. We want it to grow, deepen and diversify, and above all be useful. So check it out and let us know if you have any feedback on utility, appearance and content.

More news... If you like this, check out previous news posts from Agile*

Orion is a trademark of Pangaea Software. Insight Earth is a trademark of TerraSpark. SubSurfWiki is a trademark of Agile Geoscience. The satellite image is copyright of Google. This regular news feature is for information only. We aren't connected with any of these organizations, and don't necessarily endorse their products or services.

Beyond the experts

I presented a poster at the 1IWRP, and it was certainly a change in tone from the technical rigor of most other talks. Since I had a good discussion at the break with a number of people, I thought I would make a video out of it. If you've got six minutes, you can check it out:

In the video I make reference to a few other topics we've touched on earlier on the blog:

• AgileWiki,
• doing science on a phone, 
• why we should embrace openness,
• our cheatsheets and,
• our mobile apps

I hope to be getting into making more videos soon, so let me know if you like the format, and if you have any suggestions. 

Tuning geology

It's summer! We will be blogging a little less often over July and August, but have lots of great posts lined up so check back often, or subscribe by email to be sure not to miss anything. Our regular news feature will be a little less regular too, until the industry gets going again in September. But for today... here's the motivation behind our latest app for Android devices, Tune*.

Geophysicists like wedges. But why? I can think of only a few geological settings with a triangular shape; a stratigraphic pinchout or an angular unconformity. Is there more behind the ubiquitous geophysicist's wedge than first appears?

Seismic interpretation is partly the craft of interpreting artifacts, and a wedge model illustrates several examples of artifacts found in seismic data. In Widess' famous paper, How thin is a thin bed? he set out a formula for vertical seismic resolution, and constructed the wedge as an aid for quantitative seismic interpretation. Taken literally, a synthetic seismic wedge has only a few real-world equivalents. But as a purely quantitative model, it can be used to calibrate seismic waveforms and interpret data in any geological environment. In particular, seismic wedge models allow us to study how the seismic response changes as a function of layer thickness. For fans of simplicity, most of the important information from a wedge model can be represented by a single function called a tuning curve.

In this figure, a seismic wedge model is shown for a 25 Hz Ricker wavelet. The effects of tuning (or interference) are clearly seen as variations in shape, amplitude, and travel time along the top and base of the wedge. The tuning curve shows the amplitude along the top of the wedge (thin black lines). Interestingly, the apex of the wedge straddles the top and base reflections, an apparent mis-timing of the boundaries.

On a tuning curve there are (at least) two values worth noting; the onset of tuning, and the tuning thickness. The onset of tuning (marked by the green line) is the thickness at which the bottom of the wedge begins to interfere with the top of the wedge, perturbing the amplitude of the reflections, and the tuning thickness (blue line) is the thickness at which amplitude interference is a maximum.

For a Ricker wavelet the amplitude along the top of the wedge is given by:

where R is the reflection coefficient at the boundary, f is the dominant frequency and t is the wedge thickness (in seconds). Building the seismic expression of the wedge helps to verify this analytic solution.

Wedge artifacts

The synthetic seismogram and the tuning curve reveal some important artifacts that the seismic interpreter needs to know about, because they could be pitfalls, or they could provide geological information:

Bright (and dim) spots: A bed thickness equal to the tuning thickness (in this case 15.6 ms) has considerably more reflective power than any other thickness, even though the acoustic properties are constant along the wedge. Below the tuning thickness, the amplitude is approximately proportional to thickness.

Mis-timed events: Below 15 ms the apparent wedge top changes elevation: for a bed below the tuning thickness, and with this wavelet, the apparent elevation of the top of the wedge is actually higher by about 7 ms. If you picked the blue event as the top of the structure, you'd be picking it erroneously too high at the thinnest part of the wedge. Tuning can make it challenging to account for amplitude changes and time shifts simultaneously when picking seismic horizons.

Limit of resolution: For a bed thinner than about 10 ms, the travel time between the absolute reflection maxima—where you would pick the bed boundaries—is not proportional to bed thickness. The bed appears thicker than it actually is.

Bottom line: if you interpret seismic data, and you are mapping beds around 10–20 ms thick, you should take time to study the effects of thin beds. We want to help! On Monday, I'll write about our new app for Android mobile devices, Tune*. 

Reference

Widess, M (1973). How thin is a thin bed? Geophysics, 38, 1176–1180. 

Well worth showing off

Have you ever had difficulty displaying a well log in a presentation? Now, instead of cycling through slides, you can fluidly move across a digital, zoomable canvas using Prezi. I think it could be a powerful visual tool and presentation aid for geoscientists. Prezi allows users to to construct intuitive, animated visualizations, using size to denote emphasis or scale, and proximity to convey relevance. You navigate through the content simply by moving the field of view and zooming in and out through scale space. In geoscience, scale isn't just a concept for presentation design, it is a fundamental property that can now be properly tied-in and shown in a dynamic way.

I built this example to illustrate how geoscience images, spread across several orders of magnitude, can be traversed seamlessly for a better presentation. In a matter of seconds, one can navigate a complete petrophysical analysis, a raw FMI log, a segment of core, and thin section microscopy embedded at its true location. Explore heterogeniety and interpret geology with scale in context. How could you use a tool like this in your work?

Clicking on the play button will steer the viewer step by step through a predefined set of animations, but you can break off and roam around freely at any time (click and drag with your mouse, try it!). Prezi could be very handy for workshops, working meetings, or any place where it is appropriate to be transparent and thorough in your visualizations.

You can also try roaming Prezi by clicking on the image of this cheatsheet. Let us know what you think!

Thanks to Burns Cheadle for Prezi enthusiasm, and to Neil Watson for sharing the petrophysical analysis he built from public data in Alberta.

Open seismic processing, and dolphins

Today was the first day of the Petroleum Technology Transfer Council's workshop Open software for reproducible computational geophysics, being held at the Bureau of Economic Geology's Houston Research Center and organized skillfully by Karl Schleicher of the University of Texas at Austin. It was a full day of presentations (boo!), but all the presentations had live installation demos and even live coding (yay!). It was fantastic. 

Serial entrepreneur Alex Mihai Popovici, the CEO of Z-Terra, gave a great, very practical, overview of the relative merits of three major seismic processing packages: Seismic Unix (SU), Madagascar, and SEPlib. He has a very real need: delivering leading edge seismic processing services to clients all over the world. He more or less dismissed SEPlib on the grounds of its low development rate and difficulty of installation. SU is popular (about 3300 installs) and has the best documentation, but perhaps lacks some modern imaging algorithms. Madagascar, Alex's choice, has about 1100 installs, relatively terse self-documentation (it's all on the wiki), but is the most actively developed.

The legendary Dave Hale (I think that's fair), Colorado School of Mines, gave an overview of his Mines Java Toolkit (JTK). He's one of those rare people who can explain almost anything to almost anybody, so I learned a lot about how to manage parallelization in 2D and 3D arrays of data, and how to break it. Dave is excited about the programming language Scala, a sort of Java lookalike (to me) that handles parallelization beautifully. He also digs Jython, because it has the simplicity and fun of Python, but can incorporate Java classes. You can get his library from his web pages. Installing it on my Mac was a piece of cake, needing only three terminal commands: 

• svn co http://boole.mines.edu/jtk
• cd jtk/trunk
• ant

Chuck Mosher of ConocoPhillips then gave us a look at JavaSeis, an open source project that makes handling prestack seismic data easy and very, very fast. It has parallelization built into it, and is perfect for large, modern 3D datasets and multi-dimensional processing algorithms. His take on open source in commerce: corporations are struggling with the concept, but "it's in their best interests to actively participate".

Eric Jones is CEO of Enthought, the innovators behind (among other things) NumPy/SciPy and the Enthought Python Distribution (or EPD). His take on the role of Python as an integrator and facilitator, handling data traffic and improving usability for the legacy software we all deal with, was practical and refreshing. He is not at all dogmatic about doing everything in Python. He also showed a live demo of building a widget with Traits and Chaco. Awesome.

After lunch, BP's Richard Clarke told us about the history and future of FreeUSP and FreeDDS, a powerful processing system. FreeDDS is being actively developed and released gradually by BP; indeed, a new release is due in the next fews days. It will eventually replace FreeUSP. Richard and others also mentioned that Randy Selzler is actively developing PSeis, the next generation of this processing system (and he's looking for sponsors!). 

German Garabito of the Federal University of Parà, Brazil, generated a lot of interest in BotoSeis, the GUI he has developed to help him teach SU. It allows one to build and manage processing flows visually, in a Java-built interface inspired by Focus, ProMax and other proprietary tools. The software is named after the Amazon river dolphin, or boto (left). Dave Hale described his efforts as the perfect example of the triumph of 'scratching your own itch'.

Continuing the usability theme, Karl Schleicher followed up with a nice look at how he is building scripts to pull field data from the USGS online repository, and perform SU and Madagascar processing flows on them. He hopes he can build a library of such scripts as part of Sergey Fomel's reproducible geophysics efforts. 

Finally, Bill Menger of Global Geophysical told the group a bit about two projects he open sourced when he was at ConocoPhillips: GeoCraft and CPSeis. His insight on what was required to get them into the open was worth sharing: 

1. Get permission, using a standard open source license (and don't let lawyers change it!)
2. Communicate the return on investment carefully: testing, bug reporting, goodwill, leverage, etc.
3. Know what you want to get out of it, and have a plan for how to get there
4. Pick a platform: compiler, dependencies, queueing, etc (unless you have a lot of time for support!)
5. Know the issues: helping users, dealing with legacy code, dependency changes, etc.

I am looking forward to another awesome-packed data tomorrow. My own talk is the wafer-thin mint at the end!

Update on Saturday, June 18, 2011 at 8:34 PM by Matt Hall

You can read all about Day 2 of this workshop in this blog post.