June 08, 2011
Although the oil and gas industry could make use of cloud computing for remote processing of mission-critical operations, it is not common to encounter a steady stream of case studies in this arena. While there might be a few stories that fall under the behind-the-firewall, private cloud model, it seems that public clouds or multitenant managed services are not, for some reason, gaining traction with oil and gas IT leaders.
Rigstar handles lifecycle communication services for the oil and gas industry via their handling of remote wide area network requirements, mostly for the industry’s North American customers. They recently partnered with Marlabs, Inc., a software and BPO services company to build a managed cloud platform that will begin by serving oil and gas customers in Canada. The service will be providing what Marlabs describes as “a completely customizable suite of cloud services, delivered within the footprint of a client’s private network with three core elements—a virtual data center in a box, cloud enablement, and custom application mobility services.”
Fossen and Holden claim that the challenges for oil and gas in the cloud are the same as in other areas but the key difference is the scope and intensity of some of the core challenges. They claim that the volume and value of hard-won proprietary data, trade secrets, process details and the like are all magnified in an industry with so much competition.
With regards to the public vs. private cloud debate, private models or limited tenancy (semi-public) set-ups are the norm mainly due to the security concerns mentioned earlier. In addition to the privacy issues, there are cross-border regulatory concerns that come into play when using the larger public cloud service providers.
They say that another area of concern for oil and gas in the public cloud model is availability and response time and in a lot of cases, the time sensitive nature of the data being processed. With such a dependence upon stringent response and availability targets as well as the need for iron-clad high speed continuance and recovery options the private cloud option is a much better fit for addressing these needs while still achieving some of the key efficiency & profitability benefits of the cloud.
One of the other challenges they pointed is recognizable, if not predictable, to anyone experimenting with HPC clouds—latency. The two oil and gas experts claimed that there are several factors compounding the mere issue of speed. Rapid growth of information requires some agility in terms of delivery and collaboration across borders, which constraints systems. This is coupled with a problem that is more industry-specific as the computation can take place in remote, inhospitable environments. They claim that this is one of the keys to their announcement; they can take advantage of Rigstar’s broadband infrastructure to mitigate latency issues and utilize Marlabs’ expertise in sustaining a platform that has been purpose-built with these very problems in mind.
They also noted that there is another challenge for this industry in particular as it looks to the cloud. There is a cultural resistance within the oil and gas industry to move to a service-based solution versus building and owning the infrastructure (i.e. keeping versus losing the perceived control). To counter this, however, they say that what is many times ignored in such arguments is that the long term impact of managing and maintaining those systems. The impact that ongoing opex has on ROI and TCO is undervalued and as a result, the other issues they identified are added to the list of problems with the oil and gas industry’s cloud model.
As the two told us, like every other industry there is an increased demand for cost-efficiency and heightened ROI expectations especially in relation to new ventures and remote exploration start-ups. Cloud based IT services offer an immediacy of access (off-the-shelf delivery) with known price points taking a lot of the guesswork out of those types of activities. On the fly, mobile access to computational power and centralization of those resources into standardized, monitored environments is another key selling point. It’s a lot easier to open a remote well when all you need is a thin-client or even a tablet and a network connection to commence business activities.
According to both Fossen and Holden, the low hanging fruit of easily accessible reservoirs is long gone in oil and gas. They claim that today’s exploration and extraction activities center on massive volumes of data involved in complex multi-dimensional reservoir modeling, monitoring and maintenance of advanced extraction equipment and other resource intense activities. To perform these activities in real-time in remote corners of the world requires a combination of scalable high performance computational power and reliable, “big pipe” delivery infrastructure.
The key to designing cloud solutions for these “computational wildebeests” is in establishing adaptive clusters that can dynamically allocate processor cores on demand within a static pool of resources (as is the case in a private cloud environment). The flexibility provided by large multi core processor OEM’s in combination with a robust virtual machine environment is critical to success in this area.
The two told us that there are times when indeed, despite any favorable arguments, clouds are not a good fit for oil and gas. As they told us in our email interview, “If your culture is not a collaborative, lean-forward environment then cloud computing is definitely not the right place for you to land. If you have a heavy reliance on legacy systems you are in for a world of hurt trying to make those applications deliverable in the cloud. It is not just a simple matter of creating some API’s and calling it a day. Most of these systems are not SOA compliant and will require significant upstream and downstream re-development and testing before they can play in the cloud. Getting your return out of that amount of development investment can be challenging.”
May 23, 2013 |
The study of climate change is one of those scientific problems where it is almost essential to model the entire Earth to attain accurate results and make worthwhile predictions. In an attempt to make climate science more accessible to smaller research facilities, NASA introduced what they call ‘Climate in a Box,’ a system they note acts as a desktop supercomputer.
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.