Spending on big data and analytics in the oil and gas industry is increasing at a rate of about 75 percent per year, as companies rapidly dispense with in-house IoT management to go with big cloud providers instead. Analyst house ABI Research said the oil and gas sector will invest $712.7 million on IoT analytics by the end of 2026, up from $156 million in 2020.
The sector’s investment in third-party IoT expertise has been climbing steadily, already; the annual spending figure was about $90 million in 2018, and has increased by 36.8 percent per year since then. ABI Research explained the oil and gas sector remains “deeply challenged” in its mission to connect and transform operations by “complex system integrations, siloed data, and supervisory control and data acquisition (SCADA) management systems”.
Kateryna Dubrova, research analyst at ABI Research, commented: “In-house analytics is no longer a sustainable and cost-effective IoT option, and oil and gas firms have widely recognized the expertise of IoT cloud platform- and software-as-a-service vendors… More and more enterprises are turning to suppliers [for] advanced analytics and AI as-a-service offerings enabled through extensive cross-industry collaborations.”
A new report cites a number of high profile partnerships around cloud IoT and AI in the sector; notably, between Total Oil and Google Cloud, BP and Microsoft Azure, and Saudi Aramco and Seeq. “Azure and Amazon Web Services (AWS) are the “leading end-to-end solutions with basic public cloud toolkits”, said Dubrova. The likes of Seeq, Foghorn, Falkonry, Manna, and Uptake provide “more advanced” industry-focused analytics, she said.
The report also highlights the work of DataRobot, Noodle.ai, and Dataiku as “powerful” AI engines offering machine-learning integration and low-to-no-code solutions, and the roles of Nokia, C3.ai, Teradata, KX, and GE as system integrators offering “overall digital transformation services” in the sector. Oil and gas enterprises and vendors are focusing on the “green” market, said Dubrova, driving demand for “green” analytics use cases and applications.
Dubrova commented: “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.”
