The Oil & Gas (O&G) IoT Analytics market garners heavy investment, yet it is deeply challenged by complex system integrations, siloed data, and Supervisory Control and Data Acquisition (SCADA) management systems. In-house analytics is no longer a sustainable and cost-effective IoT option, and oil & gas firms have widely recognized the expertise of IoT cloud Platform-as-a-Service (PaaS)/SaaS vendors. According to global tech market advisory firm ABI Research, spending on big data and analytics in the oil and gas industry totaled US$156 million in 2020, an annual increase of 36.8% from 2018. Over the next 6 years, the oil & gas IoT core analytics service revenue will grow to US$712.7 million.
“Instead of developing analytics capabilities in-house, more and more enterprises are turning to supplier advanced analytics and Artificial Intelligence (AI) PaaS/SaaS offerings enabled through extensive cross-industry collaborations. Partnership examples include Total Oil and Google Cloud, BP and Azure, and Seeq and Saudi Aramco. Simultaneously, the leading IoT vendors are continually competing for the top O&G contracts by offering an end-to-end solution and expanding their marketplace portfolios toward the edge,” explains Kateryna Dubrova, Research Analyst at ABI Research.
Azure and Amazon Web Services (AWS) are positioned as leading end-to-end solutions with basic public cloud toolkits. While Seeq, Foghorn, Falkonry, Manna, and Uptake, provide more advanced, specialized oil & gas analytics solutions. DataRobot, Noodle.ai, and Dataiku provide IoT ML integration services, with powerful AI engines and low-to-no-code solutions. Simultaneously, Nokia, C3.ai, Teradata, KX, and GE are positioning themselves firmly as offering system integration and overall digital transformation services for the oil & gas sector.
The diversification of the investment portfolios toward green energy and emission monitoring technologies is among the top trends in the oil and gas analytics market. The O&G enterprises and vendors are focusing their efforts on the “green” market, driving the demand for “green” analytics use cases and applications. “Advanced analytics for upstream and downstream oil and gas operations is more or less solidified, so monitoring carbon emissions, lowering carbon footprints, and related green energy activities, are expected to become popular for advanced analytics monetization,” says Dubrova.
O&G enterprises are showcasing rapid adoption of the cloud and cloud-native analytics applications as components of their digital transformation model. “Cloud-based applications are available through subscription-based plans up to fully-managed services.. In such cases, there are considerable cost savings on infrastructure, including improving efficiencies and lowering the production costs,” Dubrova concludes.
These findings are from ABI Research’s IoT Analytics Services for Oil and Gas Markets application analysis report. This report is part of the company’s M2M, IoT & IoE research service, which includes research, data, and analyst insights. Based on extensive primary interviews, Application Analysis reports present in-depth analysis on key market trends and factors for a specific technology.