Operational Technology Viewpoints

With today’s gradually improving prices, ARC has observed an increased focus on offshore and subsea drilling.  Renewed investments in deep water and ultra-deepwater projects by major oil & gas companies should help drive a recovery in the market for subsea control systems.  

Today’s gradually increasing oil prices have helped drive economic growth in energy-producing nations and supported renewed growth in the global operational technology (OT) industry.  However, rising energy prices have not been so good to countries such as India, which – while a major energy consumer – is neither a major energy producer or global OT supplier.  In fact, the rising fuel prices are putting additional pressure on India’s falling rupee.

Digital transformation has become an imperative for industrial companies and infrastructure operators.

One of the challenges facing industrial process manufacturing is the growing number of data sources. Examples of these data sources could be shift reports, process data historians, laboratory information management systems, or manufacturing execution systems. Being able to easily connect disparate data sources for decision-making is a key challenge in the age of IIOT. The lack of connection of these data sources and the creation of data silos is one version of the “big data” problem we hear about.

In most process plants, it is impossible to install all necessary automation components in safe, non-hazardous areas. As a result, some form of protection is required to prevent fires and explosions that could occur when a hazardous gas and energy source combine. Fortunately, there are standards and associated products that, if properly designed, installed, and maintained, virtually eliminate the risk of an accidental explosion in hazardous areas.

Establishing appropriate metrics provides a foundation for continuous performance improvements. Quarterly performance reports typically contain metrics such as unscheduled downtime, production-per-unit-cost, quality-per-unit, or energy consumed-per-unit-produced. Unfortunately, these metrics are after-the-fact averages. Using them can be compared to trying to drive an automobile while looking in the rear-view mirror.

With the slow, but steady recovery in oil prices and increasing investments in alternative renewable energy sources, oil and gas companies need to innovate to stay competitive. New digital technologies to support smart drilling and blockchain distributed databases could help the global oil & gas industry evolve into a seamless, inter-operable connected environment. This is digital disruption at its best!

Alliteration adds confidence. There is something about a string of repeated characters that suggest the listed words are more related than they may actually be. Doug Laney’s proposition back in 2000 that big data is defined by volume, variety and velocity, for example, is - to me - artificially convincing. This becomes obvious when consultants got hold of it and start stringing on a fourth (“value”), fifth (“veracity”), and sixth (“validity”) V-word to differentiate their perspectives. Trailing the three Vs of big data, the three Ps of maintenance (planned maintenance, preventive maintenance, and predictive maintenance) are a distant second but show up more frequently as new analytics offerings accelerate access to predictive insights.

After months of preparation, checking the itinerary, getting speaker resumes and presentations we get set for our annual India forum. Most of the presentations at ARC’s 16th India forum were on the digital transformation journey. Although the behind-the-scenes work process is the same, there is that niggling anxiety about a zillion things that range from a speaker’s flight being delayed to the mike/laser pointer not working properly. Once the delegates begin to trickle in and the sessions begin smoothly, the team heaves a collective sigh of relief. Those at the registration desk constantly check the number of attendees who come in against earlier confirmations.

Real-time operations and business operations have different data requirements. SCADA data users need real-time data to make decisions. According to Don Morrison, Real Time Data Engineer at Devon Energy, the company’s SCADA system was designed to support operations. However, SCADA data often has abnormalities. For example, when a sensor fails or is brought off line for maintenance, data averages can become inaccurate. In cases such as these, the data must be cleansed by removing abnormalities. Devon Energy has found that advanced analytics improves operations data. They achieve this by combining the real-time system and Seeq metrics to remove some of the abnormalities and improve data quality. Once this is done, the company incorporates the cleansed data into real-time operational dashboards to support drilling and production users as well as business users. For operations users, these dashboards typically provide both basic monitoring information and higher level operational status.