With digital technologies responsible for transforming the business processes of almost every industry, oil and gas must adapt or fall behind. In particular, artificial intelligence (AI) is giving companies the tools to increase their productivity and efficiency, and is lowering costs. According to Tata Consultancy Services’ (TCS) Global Trend Study on AI, more than 90% of companies in five industries already use AI in their day-to-day operations.
The uptake of digital transformation in the oil and gas industry has been slow, however. In an era of lower oil prices, where we are unlikely to see prices reach the heady heights of a few years ago any time soon, these efficiencies will do much to boost the industry’s fortunes.
Pockets of innovation
That said, there exist pockets of innovation within oil and gas, particularly around enhancing productivity and efficiency.
The TCS Global Trends Study revealed that, in the world of oil drilling, AI has the potential to address efficiency problems.
NVIDIA and Baker Hughes, a GE company (BHGE), are using AI to dramatically reduce the cost of finding, extracting, processing and delivering oil.The two companies have partnered on a project to use AI and GPU-accelerated computing to help the oil and gas industry distill the reams of data they collect every second – production and sensor data such as pump pressures, flow rates and temperatures – in real time.
“Using deep learning and machine learning algorithms, oil and gas companies can determine the best way to optimize their operations as conditions change,” says the company.
Oil drilling supplier National Oilwell Varco uses artificial intelligence to automate the drilling process.
Digital sensors collect well conditions in real time, and the firm’s software adjusts drilling techniques accordingly – 40% faster than oil field engineers could do it.
Along more analytical lines, Woodside Petroleum (the largest operator of oil and gas production in Australia) is using AI to analyze 30 years of engineering data, aiming to improve decision making, business processes, and operational performance.
Of the 23 companies surveyed in the study (in oil and gas production, energy distribution, and energy retailing), the most cited functional area for AI projects was IT (mentioned by 74%), followed by distribution and logistics (39%).
The use of robotics within oil and gas is increasing thanks to a drive to enhance productivity as well as to reduce offshore manning.
In a recent Oil and Gas Industry Roundtable event hosted by TCS, the opportunities offered by tetherless remotely operated underwater vehicles (ROVs) were debated during a discussion about the technology available in the industry today.
While subsea systems, or ocean robotics, have been in operation for over 40 years, the limitations of underwater communication meant that they had very little functionality. But after years of development work, new models are emerging such as Subsea 7’s autonomous inspection vehicle (AIV).
The AIV has been performing untethered subsea inspections for Shell in the North Sea. It is able to submerge up to 3,000m, venture on 40km excursions and has a 24-hour dive time, depending on the mission.
The technology behind the AIV will continue as more research and development funding is poured into this area.
For instance, a new research center focused on offshore robotics and led by the University of Edinburgh launched this year with nearly US$19 million (£14.3 million) in funding from the UK Industrial Strategy Challenge Fund (ISCF).
The Offshore Robotics for Certification of Assets (ORCA) Hub will develop robotics and AI technologies for use in extreme and unpredictable environments. The hub will work to develop robot-assisted asset inspection and maintenance technologies, which can make autonomous and semi-autonomous decisions and interventions across aerial, topside and marine domains.
Looking to the future
According to the TCS Global study, when it comes to executing AI projects successfully, the key elements to getting it right include employees learning and adopting new processes and systems, while ensuring strong security and trust in the new cognitive systems.
With safer operations and cost savings on the line, in addition to increased productivity, the industry can no longer afford to shy away from the digital future.