The upstream oil and gas industry has a great opportunity these days to look for ways to be more efficient in its operations. Improved efficiency and higher asset performance translates to increased profitability, which can help take the sting out of the current market value of this industry’s product and best position the companies in this industry for excellence once the price of oil rebounds.
Big Data and the Industrial Internet of Things (IIoT) are concepts and toolsetsthat are being implemented by companies to achieve these improved efficiencies. The tools required to realize this promise, however, must provide the ability to collect, index and analyze data in real time to ultimately improve the company’s decision-making capabilities across the entire enterprise.
The computational power of today’s systems provide amazing data indexing (ever think about what makes Google’s search engine so accurate?) as well as analytical and modeling programs with visualization abilities that provide insight into a process that was never before achievable. When used properly, these tools can predict an outcome well before it happens, allowing for appropriate action to be taken that favorablychanges the outcome. A recent ARC Advisory Group report, “IIoT Strategies in Upstream Oil & Gas,” provides an example of an offshore company replacing a suspect seal on a water injection pump prior to failure, saving the company $7.5 million in unplanned downtime.
Though this opportunity sounds great to the C-level executives of these companies and the market analysts they speak to, the key task underlying this opportunity is data collection—and not just any kind of data collection. Many of the powerful Big Data applications that are available come from the IT world, where data collection has typically involved ingesting log files from IT systems. This is not the case with upstream oil and gas operations, where industrial data is not so easy to acquire. These operations are often remote and involve several different types of sensors, controllers, RTUs and flow computers—often from different companies—that house the data needed by these applications. Plus, some of the equipment in the field is ancient—a result of the “if it ain’t broke, don’t fix it” mindset; and, given the time period in which much of this equipment was created, it wasn’t designed to share data well. On top of this, communications to these remote sites are often limited, relying on wireless telemetry systems like radio, cellular and satellite that have limited bandwidth and high latency.
Luckily, new technology is emerging that alleviates the challenge of data collection. For example, KEPServerEX from Kepware supports more than 150 communication drivers for data collection and uses the OPC UA standard to link to SCADA, HMI and other automation systems. It forwards this information via the Industrial Data Forwarder for Splunk Plug-Into Big Data technology from Splunk (a platform for collecting and indexing machine data) for optimized searching, monitoring, alerting, analyzing and reporting. KEPServerEX enables Splunk Enterprise and Splunk Cloud to securely and reliably collect, forward and store information from meters and sensors for problem identification and statistical analysis.
By incorporating Big Data technologies into their operating and business systems, upstream oil and gas companies can leverage information to anticipate problems, reduce costs and coordinate resources in one effective process.
To read more from Sponseller on the Industrial Internet of Things, visit info.kepware.com/blog.