What is the IIoT?

First things first –  the term IIoT refers to the industrial internet of things, a network of smart sensors and analysis tools which enhance ongoing production processes by leveraging data. You may also have heard the term Industry 4.0, which is pretty much the same thing: the end of the era of so-called dumb machines, and the rise of smart, interconnected industrial equipment.

Conversations about the IIoT often stray into discussions about Big Data, machine learning, and predictive analytics – all of which can aid the proper use of the data gathered through machine-to-machine communication.

Back to the beginnings of IIoT

In their latest information technology report, Gartner have revealed that 53 per cent of oil and gas companies have failed to implement IIoT technology, and are not planning to do so. This is a massive issue for the oil and gas industry, with billions of dollars worth of revenue stuck in uncommunicative plants. With the majority of companies yet to jump on the bandwagon, the real changes in IIoT will occur in two places: with those companies at the forefront of the Fourth Industrial Revolution, and with those yet to be persuaded to commit to it.

Reading all this as a decision-maker in a company without a robust IIoT strategy may feel like being presented with an insurmountable obstacle – but beginning to work with IIoT is a simple transition. Many solution providers have entry-level packages available, and often, this is no more complicated than simply implementing a system of sensors and processors to allow equipment to communicate. The data provided by this system can then be stored, analysed, and accessed on an interface that is also connected to the network of sensors.

The IIoT tug-of-war

The evolving nature of IIoT’s leading edge is both a blessing and a curse for those oil and gas companies looking to implement new strategies. On the one hand, the ever-changing operating models mean that older and simpler technologies are becoming more comprehensive and affordable. On the other, many models are becoming obsolete at a faster and faster rate. Perhaps this constant drive to succeed is one of the reasons that so many companies, all of whom are aware of the IIoT, are simply refusing to start their journeys.

Without IIoT in place, decision-making units within oil and gas companies are relying on smaller data sets, which can often involve a significant amount of guesswork. Even within companies with huge volumes of data, the inability to properly leverage that information can significant stymie attempts to improve business processes.

Building up IIoT connections

We’ve already discussed the implementation of sensors as the first step in an IIoT strategy – but once you’ve connected all your assets – from those out in the field to those in your main facility – what happens next?

With remote and automatic monitoring now possible, the next step is to establish a cloud environment that is sufficient to manage the data and provide some insights that would otherwise be difficult to arrive at. Predictive analytics within your enterprise should now be functioning holistically, with most of your equipment connected to your cloud or IT system.

However, as soon as materials, products, or fuel leave your facility – your IIoT strategy becomes obsolete. Connecting the entire supply chain should be the next priority. Predictive analytics can then apply to everything from the schedule according to which replacement parts are ordered, to when fuel transports should depart. The ultimate goal should be complete connectivity, including offshore plants, vehicles, logistics, and intercontinental data transfer.

The Cloud: an IIoT bastion

With data at the centre of all decision-making processes within any type of company, data should be centrally-accessible from all points along the chain. Once the glut of industrial data can be managed to the extent that IIoT applications can make recommendations on the back of it, the benefits to the operation should become swiftly apparent. Process implementation will take place in a fraction of the time, analytics engines will be able to work with multiple often seemingly-incomparable data types, and storing vast amounts of data for auditing and regulatory purposes far simpler.

According to Gartner’s report, some businesses are only harnessing 30 per cent of the value inherent to their collected and stored data – due primarily to not being able to asses their business processes supported by data. An easier way to describe this problem is that of data lakes becoming stagnant data swamps: bigger isn’t necessarily better – it depends on how you use it.

IIoT and the bottom line

We’ve already seen the extent to which IIoT can unlock revenue trapped in badly-utilised data. According to McKinsey, the total value that could be released in the next five years if all O&G make efforts to employ IIoT is somewhere between four and 11 trillion US dollars. So in what other ways can IIoT help release this?

Oft-overlooked, HS&E can cost companies a vast amount of money if improperly managed – not counting the enormous human price of serious breaches of health and safety. Oil and gas is frequently referred to as the most dangerous industry in which to work, and the remote nature of so many sites only exacerbates the risk to life, and the cost of safeguarding employees and assets. One major benefit of the IIoT is that predictive maintenance functions can completely negate costly, high-risk inspection journeys – and help plan the safest and most timely points during the year that travel should be attempted. With hundreds of incidents around extraction sites every year, minimising the human element as much as possible protects workers, those responsible for them, and the company coffers.

Transportation is another key area for IIoT improvements, as tracking the progress and location of vehicles can not only help with predictive analytics such as departures and fuel consumption, but can also help combat fuel adulteration and theft – as it becomes impossible for products to go off-grid. Real-time updates supported by multiple connections such as GPS and mobile, can also minimise downtime during failures and ensure maintenance and repair occurs as soon as possible.

IIoT classifications

As an all-encompassing, company-wide initiative, an IIoT strategy is often split into separate departments or areas. There are, of course, no consistent breakdowns, but a common distinction that we at Oil & Gas IQ use is as follows:

Intelligent maintenance

Intelligence maintenance is the element of IIoT that prioritises the management systems used to reduce unexpected downtime and minimise breakdown frequency. This usually applies to pre-existing management systems and assets.

Automation

This can apply both to buildings and machines, from auto-heating and lighting to increasing precision during production. New solutions have been able to monitor temperature and humidity in both workspaces and pipelines, as well as transportation and wells: there really is no part of the business that cannot benefit from automation.

Machine-machine communication

This subset deals with the communication between assets without human intervention. With the rise of mobile devices and the mechanisms now in place for data transmission across a series of networks, technologies such as telemetry, robotics, and low-code are now far more prevalent.

Logistics

Rather than simply relying on human discretion, or inferences drawn from incomplete data sets – IIoT can fully transform the logistics process – from orders of components and lubricants to predicting the point of failure and replacement of heavy machinery.

So, why do we need to invest in the IIoT?

Of all industries, oil and gas is one of the most asset-heavy and data-rich. It is high-risk, employs tens of thousands of people within individual companies, and has some of the longest supply chains in the world. Data is constantly being pulled and collected in hugely-varying packets from myriad sources, making it extremely difficult to standardise and analyse. IIoT strategies can provide data virtualisation to homogenise data sets and can store vast amounts of information on the Cloud.

Many of the greatest risks to both life and profits in oil and gas are time sensitive, but without the IIoT, it is impossible for solutions to be effectively implemented. The adoption of IIoT applications will improve business efficiency, safety, capex and opex, and reduce the negative effects of having assets spread over a wide area. It’s an inevitable transformation – let’s just hope none of us gets left behind.

If you enjoyed this guide, then you may be interested in our upcoming digital event IIoT in Oil & Gas: Online 2019.