Hundreds of thousands of sensors,
thousands of wireless points and petabytes of data make CeNSE for Shell
At 0800 GMT today, Shell and HP announced
the first major project that will demonstrate the fundamental concepts behind
(Central Nervous System for the Earth) was
conceived by Stan
Williams, Senior HP Fellow and director of HP' Information and Quantum
Systems Lab (IQSL) where
revolutionary technology is being developed in anticipation of trillions of
sensors that will eventually be an integral part of every aspect of our lives,
our work, and eventually our earth.
project announced by Shell and HP focuses the fundamentals of CeNSE on the
practical application of finding and producing petroleum. Together, the
two companies are bringing together complementary capabilities to drive
innovation by developing a wireless sensing system to acquire extremely
high-resolution seismic data on land. The result will be a significant
leap forward in oil and gas exploration & production.
The system begins with a very small MEMS accelerometer created in the IQSL
lab by Pete
Hartwell and announced
last November. (Check out the Scientific American article, "World
Changing Ideas" in the December 2009 edition, page 58, featuring Pete and
his sensor.) Not only is this sensing device small, rugged, low power and
inexpensive, it is also sensitive - 1000 times more so than the sensor in the
accelerometer in your Wii controller or the air bag of your car. And that
makes it perfectly suited to measure very minute vibrations with extreme
accuracy - which in turn makes it the perfect sensor upon which to build an
entirely new seismic imaging device.
The resolution of a seismic image is greatly impacted by the quality and the
density of data retrieved during a seismic survey. Because of their MEMS
heritage, Shell will be able to deploy hundreds of thousands of sensor nodes
(compared to tens of thousands for current systems) within the same weight,
cost, and crew size constraints of current seismic surveys. That,
combined with the superior sensing range and accuracy, will result in
subsurface images that will be vastly superior (think HDTV compared to a
standard TV picture) and will transform Shell's ability to pinpoint abundant
new oil and gas reserves.
But just as the CeNSE vision encompasses a system of capabilities, the
sensor in the HP-Shell system will be only one part of the total HP-Shell
solution. All of those sensors need to communicate with a
state-of-the-art monitoring and control system - and in this next-generation
approach the answer is "lose the cables" and "take to the
air". Traditional seismic sensors are connected by cables that snake
across the survey area. The HP-Shell solution being pursued uses wireless
communications to tie it all together, not only creating a much more flexible
and resilient solution, but also one that is safer for the employees who deploy
it (less weight to heft and fewer 'cable trips').
Then there is the data collected. Hundreds of thousands of sensor
nodes will generate orders of magnitude more data than the massive amounts now
collected resulting in petabytes of data, each byte needing to be validated,
stored and then sent to data centers where high performance computers turn the
raw data into better decisions. Watch this video to understand
how these sensing solutions can open our eyes to a new world of possibilities.
And this system for land-based seismic imaging won't be effective without
the innovations in seismic survey methods and processes being brought to the
collaboration by Shell. It takes a systems view with a critical
rethinking or everything conventional to create outcomes that are
revolutionary, not evolutionary.
CeNSE is a terrific vision of the future. It knits together technology
advancements, emerging personal and business demands, and new skills and
thinking to create a vision that is not only plausible, but highly
probable. The HP-Shell collaboration to build the next generation of
land-based, seismic sensing capabilities demonstrates that the CeNSE vision can
be translated into a practical solution which will produce superior, high value
business outcomes. For Shell, this means gaining a competitive advantage
in exploring difficult oil and gas reservoirs and fully realizing the potential
of Shell's processing and imaging technology on land-based exploration and
Welcome to the brighter energy future of sensors and seismic imaging - it
all makes good CeNSE.
In the January 2010 IEEE Computer magazine there is an article Fulfilling the Vision of Autonomic Computing (unfortunately only the abstract is available for free). This articles looks at the progress that's been made since 2001 when IBM published an article on the need to automate computer management.
This new article discusses how in 2001 there were many unfilled jobs in the IT space and that at the rate things were targeted to grow, we'd never keep up and how clearly in 2010 that is not the case. There are many ways that we manage computers. We use virtualization techniques on the small scale today, things that were only done on the largest scales in 2001. It isn't the same autonomic approach that IBM proposed but it was "good enough".
On the other hand, we do have much more power and data that can be applied, and if it can be applied to the computing environment it can be applied to the enterprise as a whole. When we overcome the relatively arbitrary distinction between the business and the IT departments and address the problems from an "and not or" perspective, it is inevitable.
The IEEE article talks about a couple of examples where autonomic techniques are gaining traction:
"The main cost for the operator of a data center is power, thus provisioning of systems to match the workloads and service-level obligations becomes a critical business success factor. Because workload demands change minute by minute, no human operator can provision services with sufficient efficiency"
"Applications like environmental sensing cause the network to meet the real world in ways that preclude direct human management. The viability of environmental sensing - essential for efficient science and policymaking - therefore depends on sensor systems' ability to self-manage in the face of a changing environment"
If you change the first example to "plant floor" instead of "data center" and "enterprise" instead of "network" in the second example, it is equally valid. As we increase our abilities in IT to use these techniques, the real high value return will be to apply them for the enterprise as a whole.
Granted we'll not eat the elephant whole, but I'm sure there will be more autonomous progress for the enterprise in this decade than there was for computing in the last.
Earlier this week I was the keynote speaker for the Toronto Innovation Showcase. One of the things the mayor announced was the Toronto Open project. This activity opens up much of the cities information for the residents of Toronto to mashup into applications. They also announced an effort to coordinate the release of even more information.
By end of the first set of presentations there were already applications created for the iphone using some of the data.
The Toronto residents are being asked:
- What matters to you?
- What data do you want to access?
- What datasets and applications would you find useful?
- What's missing from this site?
This project is definitely looking to tap into the creativity the focus in Toronto can apply to problems on those cold winter nights. Here is another blog post on the event.