Digital transformation is no longer simply a future option for oil and gas companies. It’s an urgent necessity.  With competition fierce, capital more scrutinised, prices volatile and trade wars taking place, operators can’t afford to be ‘leaving money on the table’ or throwing it away by encountering delays in bringing assets online or seeing unplanned downtime of all assets dig into profits.

Today, data is inexpensive to collect, richer in context, and in fact, exploding in quantity.  But executives see less than 10% of the data they have paid to inform their business with, and the data they do see is often too complicated to support agile decision making.  Worse, staff are telling the executive team they need to recruit scarce data-scientists to make sense of it all.  There is, however, a better and smarter way.

With rapid advances in industrial value available by use of artificial intelligence (AI), machine learning and multivariate analytics, further enabled by advances in computing speed and mobility, process companies can begin to address previously unsolvable issues, without turning themselves into technology experts.

They can start to generate deeper insights from data to drive digital transformation projects, to extend asset life; maximise return on capital employed and drive additional profit. The ability to detect patterns and opportunities across a business can save vast sums and create competitive advantage.  Avoiding a compressor failure at a well site, gas pipeline, or oil refinery, through early detection and diagnosis, for example, can avoid downtime losses running into millions of pounds.

The good news is that the message is starting to get through. Oil and gas companies are increasingly looking to embrace digitalisation. But in doing so they face a problem.  How do they prioritise the multitude of available/possible digital initiatives without potentially reducing the chance of success? How do they distinguish between science projects and compelling initiatives, how do they take the best advantage of their current staff?  In short, where do they begin?

How to achieve technology innovation in the oil and gas industry

Many industries have exploited the exciting opportunities to create new products and markets, but the oil and gas sector has lagged behind and has resulted in the oil and gas industry failing to exploit the potential of new technologies

While they should never try to do everything at once, that does not have to mean going after small problems or profit opportunities; businesses can be pragmatic around a significant problem that represents major value.

BPCL, a leading Indian oil refinery in Mumbai, defined success criteria and selected and deployed an early project creating a sophisticated digital twin for improving their sulfur recovery system.  This achieved a major corporate and national KPI, namely reducing SOX emissions six-fold.  They used data, existing models, and new-age analytics combined to empower their existing team.  All without hiring data scientists. This simple success has created massive momentum to move ahead with other similar projects across their enterprise.  Sustainability is the single most visible objective handed down to BPCL by the Indian government.

In a similar way, Italian energy provider, Saras, took this approach at its 300,000-barrel-per-day refinery in the Mediterranean, applying machine learning to key equipment areas that are symptomatic of refinery downtime. They got their digital effort up and running in just a matter of weeks and were soon able to accurately identify warning signs of breakdown, with a level of sophistication beyond human ability to detect.

This capability has empowered them to predict failures with lead times of 24-45 days, and Saras also expects to reduce unplanned shutdowns by up to 10 days, increase revenue by 1% to 3% and reduce refinery maintenance costs and operating expenses by 1% to 5% meaning a competitive advantage in a hyper-competitive market.

Very similar approaches are being applied also in upstream drilling and oil production.

Embracing hybrid cloud services in traditional industries

Due to the many commercial benefits and the world of possibilities, cloud computing is now a mainstream model being adopted for the IT savvy business that has growth on its agenda

Building blocks of success

To achieve a similar result, organisations in this sector need to begin by clearly defining the business strategies amenable to improvement through the application of technology.  Then, understanding both the integrity and quality of available data but also the foundation of strategic technology systems on which advanced approaches can be applied.  Finally, assessing the readiness of an organisation to embrace new approaches, which will impact both the nature of the work and in fact the way each person in an organisation contributes to making decisions.  (Think of it as “democratisation of decision making”).

Having mapped the business needs to technology opportunity, the best short-term projects can be selected and operators can then create more value by leveraging data analytics capabilities. This is key in identifying equipment faults; predicting and preventing subsequent breakdowns and driving up the bottom line.

Another characteristic is that such digital technology projects will drive impacts beyond the immediate goal.  For instance, prevention of failures in mechanical equipment will eliminate accidents and the potential impact on health, safety and environment (HSE). Digital technologies will also play a critical role in driving sustainability and environmental responsibility, which will continue to be a top priority.

With the incorporation of AI and machine learning, today’s technology solutions can also provide cognitive guidance to engineers, operators and maintenance personnel across the sector to make faster and more accurate decisions about raw materials and make jobs in energy more interesting to young workers.

Autonomous drones in the oil and gas industry

As drone technology advances the applications for their use increase. In this case, the 24/7 autonomous surveillance oil and gas lines is a possibility

A refinery, for instance, might want to run 1,000 scenarios to identify the optimum crude oil slate for processing by taking advantage of the computing power available in the cloud. However, planning personnel can’t possibly sift through all these in the time they need to decide and capture their position in the marketplace. Applying advanced analytics to those scenarios can help to quickly narrow the options down to the few that are optimal.

These technologies will enhance decision-making and serve as valuable support tools for the experts working in the plant.

The time is now

Why would you not join the digital revolution? The tools, services and solutions needed to overcome complexity and achieve new levels of reliability and profitability are now available and accessible to any business. And the investment community is looking to energy companies to increase their productivity and agility to respond to market turbulence.

By asking the right questions and targeting these digital technologies to their needs, organisations can achieve the highest possible impact and return over the entire lifecycle. The oil and gas industry has been talking about digitalisation for decades. Enabling technologies have converged to tackle advanced optimisation, process degradation and equipment failure in real-time. This level of analysis opens a whole new area of value creation and reliability improvement for owner-operators.   And most important of all, the best of these new technology solutions are “low touch” for an organisation, building the data science into the energy solution, so that your organisation can stay focused on your core competency of converting energy to value.

Written by Ron Beck, Energy Industry Director, AspenTech