Cellular Connectivity: Powering the Future of Oil and Gas

Artificial intelligence (AI) and machine learning (ML) are gaining acceptance in the oil and gas industry. Between 2018 and 2020, the percentage of companies that deployed these technologies more than doubled, from 13% to 32%.[1] Today, 50% of oil and gas executives say they have already started using AI to help solve problems in their organizations, and 92% are currently investing in AI or planning to do so in the next two years.[2]

While these technologies have primarily been operationalized for specific use cases or particular processes, they are increasingly integrated into a multitude of systems and software to improve efficiency, productivity, and profitability. And the potential impact is significant: International Data Corporation estimates that the benefits enabled by AI and ML can reduce an organization’s total costs by up to 20%, improve asset availability by 20%, and extend life. machine life of several years.[3]

Here we explore four key industrial applications for these technologies, as well as the critical role that private cellular networks play in harnessing them successfully.

Technology enables transformation

It’s not AI and ML in and of themselves that make the difference. These are the abilities they unlock when applied in combination with other technologies, as illustrated by the following applications.

  • Security Monitoring

    High-resolution video drones and robotic devices can use AI to perform site inspections and recommend actions for oil rigs, pipelines and other hazardous work sites with greater speed and accuracy while keeping humans out of potential danger.

  • Proactive asset maintenance

    By applying ML-enabled asset condition monitoring to pumps and compressors, operators can detect equipment failures before they occur, eliminating unplanned downtime and extending the life of expensive machinery .

  • Upstream automation:

    Imagine smart drill bits with sensors behind the cutter wheel that capture real-time data about the formations being drilled, sending that data to the Edge Cloud for comparison and interpretation with huge seismic datasets – all jobs drilling records – to help direct drilling operations. We implemented this solution in the mining industry, where we pioneered autonomous mining with connected Pit Vipers.

  • Process Automation

    From upstream applications such as borehole modeling and geospatial data analysis to midstream and downstream applications such as inventory management and hazardous emissions monitoring, opportunities for automation powered by AI and ML in the oil and gas sector are almost limitless.

Connectivity enables technology

Just as the above applications rely on AI and ML to function, neither can AI and ML operate in a vacuum. They require large amounts of near real-time, high-quality data to fuel innovations. And advanced cellular connectivity is the fastest, most reliable and cost-effective way to capture and manage that data.

Additionally, 5G’s low latency and high capacity allow AI processing to be distributed between the device, edge cloud, and central cloud, enabling flexible system solutions for better efficiency, enhanced privacy , improved performance and new levels of automation.

Leveraging our industry-leading 5G private network technology, Ericsson is working with industry ecosystem partners to bring AI and ML applications to life in oil and gas companies, creating agility, improving efficiency and unleashing intelligence. Download our case summary to see how we help top industry leaders harness the power of cellular connectivity to optimize business operations with data-driven insights.

[1] “CIO Agenda 2021: An Oil and Gas Perspective.” Gartner. December 2020. https://www.gartner.com/en/documents/3994056/2021-cio-agenda-an-oil-and-gas-perspective

[2] “Applying AI in Oil and Gas.” Ernest and Young. https://www.ey.com/en_om/applying-ai-in-oil-and-gas

[3] Manish Chawla. “Applying IIoT and AI to Midstream Asset Management.” Oil and gas engineering. September 2021. https://www.oilandgaseng.com/articles/applying-iiot-and-ai-to-midstream-asset-management/

Norma A. Roth