Have some bacn

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You might have noticed a lot of emails from Canadian companies recently, asking you to confirm that you wish to receive emails from them. This is because a key part of the 2010 anti-spam law comes into effect tomorrow. We haven't sent you anything, becase we have always complied with the spirit of the law.

What is spam?

We all know what spam is, and the Canadian government's definition is plain:

commercial electronic messages [received] without the recipient's consent

And here's a definition of bacn (pronounced 'bacon') from author Jonathon Keats:

Spam by personal request

This seems to contradict the first definition, but the idea is that bacn is better than spam, but still not as good as a personal email. It's commercial email that you asked for. (Aside: according to that same author, bacn from geologists is quakn.)

Email from Agile*

Because we want you to have as much control over your inbox as possible, I have just switched our email subscription service from Feedburner to MailChimp. One of the reasons is MailChimp's excellent and rigorous anti-spam policy enforcement. Their emails make it very clear who an email is from, and how to unsubscribe from them. 

If you receive our blog updates via email, I hope you see them as a service and not a nuisance. If you're unsure about subscribing because you fear receiving promotions and so on — I promise that all you will ever get is our blog posts. It's just a convenient way to read the blog for some people. 

Just to be clear:

  • We will never add you to a mailing list that you didn't expressly subscribe to.
  • We will always give you an easy way to unsubcribe.
  • We will never share your email address or name with anyone else.
  • We will only send you emails that have an obvious Unsubscribe option.

Other ways to read

Here are some other options for subscribing to our RSS feed, which you will find at /journal/rss.xml 

We want you to be able to easily find, read, interact with, and share our content. If there is some other way we can serve you, please let us know. 

The can of spam image is by Flickr's Clyde Robinson and licensed CC-BY.

Patents are slowing us down

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I visited a geoscience consulting company in Houston recently. Various patent awards were proudly commemorated on the walls on little plaques. It's understandable: patents are difficult and expensive to get, and can be valuable to own. But recently I've started to think that patents are one of the big reasons why innovation in our industry happens at a snail's pace, in the words of Paul de Groot in our little book about geophysics. 

Have you ever read a patent? Go and have a read of US Patent 8670288, by Børre Bjerkholt of Schlumberger. I'll wait here.

What are they for?

It is more or less totally unreadable. And Google's rendering, even the garbled math, is much nicer than the USPTO's horror show. Either way, I think it's safe to assume that almost no-one will ever read it. Apart from anything else, it's written in lawyerspeak, and who wants to read that stuff?

Clearly patents aren't there to inform. So why are they there?

  • To defend against claims of infringement by others? This seems to be one of the main reasons technology companies are doing it.
  • To intimidate others into not trying to innovate or commercialize an innovation? With the possible unintended consequence of forcing competitors to avoid trouble by being more inventive.
  • To say to Wall Street (or whoever), "we mean business"? Patents are valuable: the median per-patent price paid in corporate acquisitions in 2012 was $221k.
  • To formalize the relationship between the inventor (a human, given that only humans have the requisite inventive genius) and the intellectual property owner (usually a corporation, given that it costs about $40k in lawyer's fees to apply for a patent successfully)?
  • Because all the cool kids are doing it? Take a look at that table. You don't want to get left behind do you?

I'm pretty sure most patents in our industry are a waste of money, and an unecessary impediment to innovation in our industry. If this is true then, as you see from the trend in the data, we have something to worry about.

A dangerous euphemism

That phrase, intellectual property, what exactly does that mean? I like what Cory Doctorow — one of Canada's greatest intellects — had to say about intellectual property in 2008:

the phrase "intellectual property" is, at root, a dangerous euphemism that leads us to all sorts of faulty reasoning about knowledge.

He goes on to discuss that intellectual property is another way of saying 'ideas and knowledge', but can those things really be 'property'? They certainly aren't like things that definitely are property: if I steal your Vibroseis truck, you can't use it any more. If I take your knowledge, you still have it... and so do I. If it was useful knowlege, then now it's twice as useful.

This goes some way to explaining why 2 weeks ago, the electric car manufacturer Telsa relinquished its right to sue patent infringers. The irrepressible Elon Musk explained::

Yesterday [11 June], there was a wall of Tesla patents in the lobby of our Palo Alto headquarters. That is no longer the case. They have been removed, in the spirit of the open source movement, for the advancement of electric vehicle technology.

This is bold, but smart — Tesla knows that its best chance of dominating a large electric vehicle industry depends on there being a large electric vehicle industry. And they've just made that about 10 times more likely.

What will we choose?

I think one of the greatest questions facing our industry, and our profession, is: How can we give ourselves the best chance of maintaining the ability to find and extract petroleum in a smart, safe, ethical way, for as long as humanity needs it? By seeking to stop others from applying a slightly new velocity model building algorithm? By locking up over 2000 other possibly game-changing ideas a year? Will society thank us for that?

Cross sections into seismic sections

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We've added to the core functionality of modelr. Instead of creating an arbitrarily shaped wedge (which is plenty useful in its own right), users can now create a synthetic seismogram out of any geology they can think of, or extract from their data.

Turn a geologic-section into an earth model

We implemented a color picker within an image processing scheme, so that each unique colour gets mapped to an editable rock type. Users can create and manage their own rock property catalog, and save models as templates to share and re-use. You can use as many or as few colours as you like, and you'll never run out of rocks.

To give an example, let's use the stratigraphic diagram that Bruce Hart used in making synthetic seismic forward models in his recent Whither seismic stratigraphy article. There are 7 unique colours, so we can generate an earth model by assigning a rock to each of the colours in the image.

If you can imagine it, you can draw it. If you can draw it, you can model it.

Modeling as an interactive experience

We've exposed parameters in the interface and so you can interact with the multidimensional seismic data space. Why is this important? Well, modeling shouldn't be a one-shot deal. It's an iterative process. A feedback cycle where you turn knobs, pull levers, and learn about the behaviour of a physical system; in this case it is the interplay between geologic units and seismic waves. 

A model isn't just a single image, but a swath of possibilities teased out by varying a multitude of inputs. With modelr, the seismic experiment can be manipulated, so that the gamut of geologic variability can be explored. That process is how we train our ability to see geology in seismic.

Hart's paper doesn't specifically mention the rock properties used, so it's difficult to match amplitudes, but you can see here how modelr stands up next to Hart's images for high (75 Hz) and low (25 Hz) frequency Ricker wavelets.

There are some cosmetic differences too... I've used fewer wiggle traces to make it easier to see the seismic waveforms. And I think Bruce forgot the blue strata on his 25 Hz model. But I like this display, with the earth model in the background, and the wiggle traces on top — geology and seismic blended in the same graphical space, as they are in the real world, albeit briefly.

Subscribe to the email list to stay in the loop with modelr news, or sign-up at modelr.io and get started today.

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Seismic models: Hart, BS (2013). Whither seismic stratigraphy? Interpretation, volume 1 (1). The image is copyright of SEG and AAPG.

Slicing seismic arrays

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Scientific computing is largely made up of doing linear algebra on matrices, and then visualizing those matrices for their patterns and signals. It's a fundamental concept, and there is no better example than a 3D seismic volume.

Seeing in geoscience, literally

Digital seismic data is nothing but an array of numbers, decorated with header information, sorted and processed along different dimensions depending on the application.

In Python, you can index into any sequence, whether it be a string, list, or array of numbers. For example, we can index into the fourth character (counting from 0) of the word 'geoscience' to select the letter 's':

>>> word = 'geosciences'
>>> word[3]
's'

Or, we can slice the string with the syntax word[start:end:step] to produce a sub-sequence of characters. Note also how we can index backwards with negative numbers, or skip indices to use defaults:

>>> word[3:-1]  # From the 4th character to the penultimate character.
'science'
>>> word[3::2]  # Every other character from the 4th to the end.
'sine'

Seismic data is a matrix

In exactly the same way, we index into a multi-dimensional array in order to select a subset of elements. Slicing and indexing is a cinch using the numerical library NumPy for crunching numbers. Let's look at an example... if data is a 3D array of seismic amplitudes:

timeslice = data[:,:,122] # The 122nd element from the third dimension.
inline = data[30,:,:]     # The 30th element from the first dimension.
crossline = data[:,60,:]  # The 60th element from the second dimension.

Here we have sliced all of the inlines and crosslines at a specific travel time index, to yield a time slice (left). We have sliced all the crossline traces along an inline (middle), and we have sliced the inline traces along a single crossline (right). There's no reason for the slices to remain orthogonal however, and we could, if we wished, index through the multi-dimensional array and extract an arbitrary combination of all three.

Questions involving well logs (a 1D matrix), cross sections (2D), and geomodels (3D) can all be addressed with the rigours of linear algebra and digital signal processing. An essential step in working with your data is treating it as arrays.

View the notebook for this example, or get the get the notebook from GitHub and play with around with the code.

Sign up!

If you want to practise slicing your data into bits, and other power tools you can make, the Agile Geocomputing course will be running twice in the UK this summer. Click one of the buttons below to buy a seat.

Eventbrite - Agile Geocomputing, Aberdeen

Eventbrite - Agile Geocomputing, London

More locations in North America for the fall. If you would like us to bring the course to your organization, get in touch.

Great geophysicists #11: Thomas Young

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Painting of Young by Sir Thomas LawrenceThomas Young was a British scientist, one of the great polymaths of the early 19th century, and one of the greatest scientists. One author has called him 'the last man who knew everything'¹. He was born in Somerset, England, on 13 June 1773, and died in London on 10 May 1829, at the age of only 55. 

Like his contemporary Joseph Fourier, Young was an early Egyptologist. With Jean-François Champollion he is credited with deciphering the Rosetta Stone, a famous lump of granodiorite. This is not very surprising considering that at the age of 14, Young knew Greek, Latin, French, Italian, Hebrew, Chaldean, Syriac, Samaritan, Arabic, Persian, Turkish and Amharic. And English, presumably. 

But we don't include Young in our list because of hieroglyphics. Nor  because he proved, by demonstrating diffraction and interference, that light is a wave — and a transverse wave at that. Nor because he wasn't a demented sociopath like Newton. No, he's here because of his modulus. 

Elasticity is the most fundamental principle of material science. First explored by Hooke, but largely ignored by the mathematically inclined French theorists of the day, Young took the next important steps in this more practical domain. Using an empirical approach, he discovered that when a body is put under pressure, the amount of deformation it experiences is proportional to a constant for that particular material — what we now call Young's modulus, or E:

This well-known quantity is one of the stars of the new geophysical pursuit of predicting brittleness from seismic data, and a renewed interested in geomechanics in general. We know that Young's modulus on its own is not enough information, because the mechanics of failure (as opposed to deformation) are highly nonlinear, but Young's disciplined approach to scientific understanding is the best model for figuring it out. 

Sources and bibliography

Footnote

¹ Thomas Young wrote a lot of entries in the 1818 edition of Encyclopædia Britannica, including pieces on bridges, colour, double refraction, Egypt, friction, hieroglyphics, hydraulics, languages, ships, sound, tides, and waves. Considering that lots of Wikipedia is from the out-of-copyright Encyclopædia Britannica 11th ed. (1911), I wonder if some of Wikipedia was written by the great polymath? I hope so.

The nonlinear ear

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Hearing, audition, or audioception, is one of the Famous Five of our twenty or so senses. Indeed, it is the most powerful sense, having about 100 dB of dynamic range, compared to about 90 dB for vision. Like vision, hearing — which is to say, the ear–brain system — has a nonlinear response to stimuli. This means that increasing the stimulus by, say, 10%, does not necessarily increase the response by 10%. Instead, it depends on the power and bandwidth of the signal, and on the response of the system itself.

What difference does it make if hearing is nonlinear? Well, nonlinear perception produces some interesting effects. Some of them are especially interesting to us because hearing is analogous to the detection of seismic signals — which are just very low frequency sounds, after all.

Stochastic resonance (Zeng et al, 2000)

One of the most unintuitive properties of nonlinear detection systems is that, under some circumstances, most importantly in the presence of a detection threshold, adding noise increases the signal-to-noise ratio.

I'll just let you read that last sentence again.

Add noise to increase S:N? It might seem bizarre, and downright wrong, but it's actually a fairly simple idea. If a signal is below the detection threshold, then adding a small Goldilocks amount of noise can make the signal 'peep' above the threshold, allowing it to be detected. Like this:

I have long wondered what sort of nonlinear detection system in geophysics might benefit from a small amount of noise. It also occurs to me that signal reconstruction methods like compressive sensing might help estimate that 'hidden' signal from the few semi-random samples that peep above the threshold. If you know of experiments in this, I'd love to hear about it.

Better than Heisenberg (Oppenheim & Magnasco, 2012)

Denis Gabor realized in 1946 that Heisenberg's uncertainty principle also applies to linear measures of a signal's time and frequency. That is, methods like the short-time Fourier transform (STFT) cannot provide the time and the frequency of a signal with arbitrary precision. Mathematically, the product of the uncertainties has some minimum, sometimes called the Fourier limit of the time–bandwidth product.

So far so good. But it turns out our hearing doesn't work like this. It turns out we can do better — about ten times better.

Oppenheim & Magnasco (2012) asked subjects to discriminate the timing and pitch of short sound pulses, overlapping in time and/or frequency. Most people were able to localize the pulses, especially in time, better than the Fourier limit. Unsurprisingly, musicians were especially sensitive, improving on the STFT by a factor of about 10. While seismic signals are not anything like pure tones, it's clear that human hearing does better than one of our workhorse algorithms.

Isolating weak signals (Gomez et al, 2014)

One of the most remarkable characteristics of biological systems is adaptation. It seems likely that the time–frequency localization ability most of us have is a long-term adaption. But it turns out our hearing system can also rapidly adapt itself to tune in to specific types of sound.

Listening to a voice in a noisy crowd, or a particular instrument in an orchestra, is often surprisingly easy. A group at the University of Zurich has figured out part of how we do this. Surprisingly, it's not high-level processing in the auditory cortex. It's not in the brain at all; it's in the ear itself.

That hearing is an active process was known. But the team modeled the cochlea (right, purple) with a feature called Hopf bifurcation, which helps describe certain types of nonlinear oscillator. They established a mechanism for the way the inner ear's tiny mechanoreceptive hairs engage in active sensing.

What does all this mean for geophysics?

I have yet to hear of any biomimetic geophysical research, but it's hard to believe that there are no leads here for us. Are there applications for stochastic resonance in acquisition systems? We strive to make receivers with linear responses, but maybe we shouldn't! Could our hearing do a better job of time-frequency localization than any spectral decomposition scheme? Could turning seismic into music help us detect weak signals in the geological noise?

All very intriguing, but of course no detection system is perfect... you can fool your ears too!

References

Zeng FG, Fu Q, Morse R (2000). Human hearing enhanced by noise. Brain Research 869, 251–255.

Oppenheim, J, and M Magnasco (2013). Human time-frequency acuity beats the Fourier uncertainty principle. Physical Review Letters. DOI 10.1103/PhysRevLett.110.044301 and in the arXiv.

Gomez, F, V Saase, N Buchheim, and R Stoop (2014). How the ear tunes in to sounds: A physics approach. Physics Review Applied 1, 014003. DOI 10.1103/PhysRevApplied.1.014003.

The stochastic resonance figure is original, inspired by Simonotto et al (1997), Physical Review Letters 78 (6). The figure from Oppenheim & Magnasco is copyright of the authors. The ear image is licensed CC-BY by Bruce Blaus. 

Saving time with code

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A year or so ago I wrote that...

...every team should have a coder. Not to build software, not exactly. But to help build quick, thin solutions to everyday problems — in a smart way. Developers are special people. They are good at solving problems in flexible, reusable, scalable ways.

Since writing that, I've written more code than ever. I'm not ready to say that my starry-eyed vision of a perfect world of techs-cum-coders, but now I see that the path to nimble teams is probably paved with long cycle times, and never-ending iterations of fixing bugs and writing documentation.

So potentially we replace the time saved, three times over, with a tool that now needs documenting, maintaining, and enhancing. This may not be a problem if it scales to lots of users with the same problem, but of course having lots of users just adds to the maintaining. And if you want to get paid, you can add 'selling' and 'marketing' to the list. Pfff, it's a wonder anybody ever makes anthing!

At least xkcd has some advice on how long we should spend on this sort of thing...

All of the comics in this post were drawn by and are copyright of the nonpareil of geek cartoonery, Randall Munroe, aka xkcd. You should subscribe to his comics and his What If series. All his work is licensed under the terms of Creative Commons Attribution Noncommercial.

Lusi's 8th birthday

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Lusi is the nickname of Lumpur Sidoarjo — 'the mud of Sidoarjo' — the giant mud volcano in the city of Sidoarjo, East Java, Indonesia. This week, Lusi is eight years old.

Google MapsBefore you read on, I recommend taking a look at it in Google Maps. Actually, Google Earth is even better — especially with the historical imagery. 

The mud flow was [may have been; see comments below — edit, 26 June 2014] triggered by the Banjar Panji 1 exploration well, operated by Lapindo Brantas, though the conditions may have been set up by a deadly earthquake. Mud loss events started in the early hours of 27 May 2006, seven minutes after the 6.2 Mw Yogyakarta earthquake that killed about 6,000 people. About 24 hours later, a large kick was killed and the blow-out preventer activated. Another 22 hours after this, while fishing in the killed well, mud, steam, and natural gas erupted from a fissure about 200 m southwest of the well. A few weeks after that, it was venting 180,000 m³ every day — enough mud to fill 72 Olympic swimming pools.

Thousands of years

In the slow-motion disaster that followed, as hot water from Miocene carbonates mobilized volcanic mud from Pleistocene mudstones, at least 15,000 people — and maybe as many as 50,000 people — were displaced from their homes. Davies et al. (2011) estimated that the main eruption may last 26 years, though recent sources suggest it is easing quickly. Still, during this time, we might expect 95–475 m of subsidence. And in the long term? 

By analogy with natural mud volcanoes it can be expected to continue to flow at lower rates for thousands of years. — Davies et al. (2011)

So we're only 8 years into a thousand-year man-made eruption. And there's already enough mud thrown up from the depths to cover downtown Calgary...

References and further reading

Quite a bit has been written about LUSI. The Hot Mud Flow blog tracks a lot of it. The National University of Singapore has a lot of satellite photographs, besides those you'll find in Google Earth. The Wikipedia article links to a lot of information, as you'd expect. The Interweb has a few others, including this article by Tayvis Dunnahoe in E&P Magazine. 

There are also some scholarly articles. These two are worth tracking down:

Davies, R, S Mathias, R Swarbrick and M Tingay (2011). Probabilistic longevity estimate for the LUSI mud volcano, East Java. Journal of the Geological Society 168, 517–523. DOI 10.1144/0016-76492010-129

Sawolo, N, E Sutriono, B Istadi, A Darmoyo (2009). The LUSI mud volcano triggering controversy: was it caused by drilling? Marine & Petroleum Geology 26 (9), 1766–1784. DOI 10.1016/j.marpetgeo.2009.04.002

The satellite images in this post are © DigitalGlobe and Google, captured from Google Earth, and are used here in accordance with their terms of use. The maps are © OpenStreetMap and licensed ODbL. The seismic section is from Davies et al. 2011 and © The Geological Society of London and is used here in accordance with their terms of use. The text of this post is © Agile Geoscience and openly licensed under the terms of CC-BY, as always!

Are we alright?

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GeoConvention_2014_logo.png

This year's Canada GeoConvention tried a few new things. There was the Openness Unsession, Jen Russel Houston's Best of 2013 PechaKutcha session, and the On Belay careers session. Attendance at the unsession was a bit thin; the others were well attended. Hats off to the organizers for getting out of a rut.

I went to the afternoon of the On Belay session. It featured several applied geoscientists with less than 5 years of experience in the industry. I gather the conference asked them for a candid 'insider' view, with career tips for people like them. I heard 2 talks, and the experience left me literally shaking, prompting Ben Cowie to ask me if I was alright.

I was alright, but I'm not sure about us. Our community — or this industry — has a problem.

Don't be yourself

Marc Enter gave a talk entitled Breaking into Calgary's oil and gas industry, an Aussie's perspective.

Marc narrated the arc of his career: well site geology in a trailer in the outback, re-location to Calgary, being laid-off, stumbling into consultancy (what a person does when they can't find a real job), and so on. On this journey, Marc racked up hundreds of hours of interview experience searching for work in Calgary. Here are some of his learnings, paraphrased but I think they are accurate:

  • Being yourself is impossible in a unfamiliar place. So don't be yourself.
  • Interview experience is crucial to being comfortable, so apply for jobs you have no interest in, just for the experience.
  • If the job description doesn’t sound exactly right to you, apply anyway. It's experience.
  • Confidence is everything. HR people are sniffer dogs for confidence. If you don't have it, invent it.
  • On confidence: it is easier to find a job when you have a job.

What on earth are we teaching these young professionals about working in this industry? This is awful.

How to survive the workday 

Jesse Shoengut gave a talk entitled One man’s tips and tricks for surviving your early professional career. 

Surviving. That's the word he chose. Might as well have been enduring. Tolerating. TGIF mindset. Like Marc, Jesse spoke about a haphazard transition from university into the working world. If you can't find a job after you finish your undergrad, you can always have a go at grad school. That's one way to get work experience, if all else fails.

Fine, finding work can be hard, and not all jobs are awesome. But with statements like, "Here are some things that keep me sane at work, and help get me through the day," I started to react a bit. C'mon, is that really what people in the audience deserve to hear? Is that really what work is like? It's depressing.

A broken promise

Listening to these talks, I felt embarrassed for our profession. They felt like a candid celebration of mediocrity, where confidence compensates for complacency. I don't blame these young professionals — students have been groomed, through summer internships and hyper-conventional careers events, to get their resumes in order, fit in, and follow instructions. We in industry have built this trap we're mired in. And we are continually seduced. Seduced by the bait of more-then-decent pay and plenty of other rewards. 

I talked to one fellow afterwards. He said, "Yeah, well, a lot of people are finding it hard to find a job right now." If these cynical, jaded young professionals are representative, I'm not surprised.

Were you at this session? Did you see other talks, or walk away with a different impression? I'd love to hear your viewpoints... am I being unfair? Leave a comment.

Mining innovation

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by Jelena Markov and Tom Horrocks

Jelena is a postgraduate student and Tom is a research assistant at the University of Western Australia, Perth. They competed in the recent RIIT Unearthed hackathon, and kindly offered to tell us all about it. Thank you, Jelena and Tom!

Two weeks ago Perth coworking space Spacecubed hosted a unique 54-hour-long hackathon focused on the mining industry. Most innovations in the mining industry are the result of long-term strategic planning in big mining companies, or collaboration with university groups. In contrast, the Unearthed hackathon provided different perspectives on problems in the mining domain by giving 'outsiders' a chance to work on industry problems.

The event attracted web-designers, software developers, data gurus, and few geology and geophysics geeks, all of whom worked together on data — both open and proprietary from the Western Australian Government and industry respectively — to deliver time-constrained solutions to problems in the mining domain. There were around 100 competitors divided into 18 teams, but just one underlying question: can web-designers and software developers create solutions that compete, on an innovative level, with those from the R&D divisions of mining companies? Well, according to panel of mining executives and entrepreneurs, they can.

Safe, seamless shutdown

The majority of the teams chose to work on logistic problems in mining production. For example, the Stockphiles worked on a Rio Tinto problem about how to efficiently and safely shut down equipment without majorly disturbing the overall system. Their solution used Directed Acyclic Graphs as the basis for an interactive web-based interface that visualised the impacted parts of the system. Outside of the mining production domain, however, two teams tackled problems focused on geology and geophysics...

Geoscience hacking

The team Ultramafia used augmented reality and cloud-based analysis to visualize geological mapping, with the underlying theme of the smartphone replacing the geological hammer, and also the boring task of joint logging!

The other team in this domain — and the team we were part of — was 50 Grades of Shale...

The team consisted of three PhD students and three staff members from the Centre for Exploration Targeting at the UWA. We created an app for real-time downhole petrophysical data analysis — dubbed Wireline Spelunker — that automatically classifies lithology types from wireline logs and correlates user-selected log segments across the drill holes. We used some public libraries for machine learning and signal analysis algorithms, and within 54 hours the team had implemented a workflow and interface, using data from the government database.

The boulder detection problem

The first prize, a 1 oz gold medal, was awarded to Applied Mathematics, who came up with an extraordinary use of accelerometers. They worked on Rio Tinto's 'boulder detection' problem — early detection of a large rocks loaded into mining trucks in order to prevent crusher malfunctions later in the process, which could ultimately cost $250,000 per hour in lost revenue. The team's solution was to detect large boulders by measuring the truck's vibrations during loading.

Second and third prizes went to Pit IQ and The Froys respectively. Both teams worked on data visualization problems on the mine site, and came up with interactive mobile dashboards.

A new role for Perth?

Besides having a chance to tackle problems that are costing the mining industry millions of dollars a year, this event has demonstrated that Perth is not just a mining hub but also has potential for something else.

This potential is recognized by event organizers Resources Innovation through Information Technology — Zane, Justin, Paul, and Kevin. They see potential in Perth as a centre for tech start-ups focused on the resource industry. Evidently, the potential is huge.

Follow Jelena on Twitter