The oil & gas industry continues to be a hotbed of innovation, with activity driven by the need to improve productivity, minimise downtime, and enhance safety, which have led to the growing importance of technologies such as machine learning and AI. In the last three years alone, there have been over 534,000 patents filed and granted in the oil & gas industry, according to GlobalData’s report on Artificial Intelligence in Oil & Gas: AI for workflow management. Buy the report here.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
150+ innovations will shape the oil & gas industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the oil & gas industry using innovation intensity models built on over 256,000 patents, there are 40+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, sensor guided flow mixing, AI-assisted cheminformatics, and intelligent embedded systems are disruptive technologies that are in the early stages of application and should be tracked closely. Automated drilling tools, AI for workflow management, and AI-assisted CAD are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are mixing ratio control techniques and wellbore drilling optimisation, which are now well established in the industry.
Innovation S-curve for artificial intelligence in the oil & gas industry
AI for workflow management is a key innovation area in artificial intelligence
According to engineering terminology, data preparation, modelling, simulation and testing, and deployment are the four processes that form the AI in workflow management concept. To create a complete AI-driven workflow, developers need to consider all the above four steps.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 40+ companies, spanning technology vendors, established oil & gas companies, and up-and-coming start-ups engaged in the development and application of AI for workflow management.
Key players in AI for workflow management – a disruptive innovation in the oil & gas industry
‘Application diversity’ measures the number of different applications identified for each relevant patent and broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to AI for workflow management
|Company||Total patents (2010 - 2022)||Premium intelligence on the world's largest companies|
|State Grid Corporation of China||546||Unlock Company Profile|
|China Southern Power Grid||165||Unlock Company Profile|
|Siemens||152||Unlock Company Profile|
|General Electric||104||Unlock Company Profile|
|Halliburton||88||Unlock Company Profile|
|Honeywell International||79||Unlock Company Profile|
|Johnson Controls International||66||Unlock Company Profile|
|3M||59||Unlock Company Profile|
|China Southern Power Grid||53||Unlock Company Profile|
|Fanuc||52||Unlock Company Profile|
|Schlumberger||42||Unlock Company Profile|
|Mitsubishi Heavy Industries||35||Unlock Company Profile|
|Rockwell Automation||32||Unlock Company Profile|
|Saudi Arabian Oil||31||Unlock Company Profile|
|Schneider Electric||29||Unlock Company Profile|
|Yokogawa Electric||21||Unlock Company Profile|
|Baker Hughes||16||Unlock Company Profile|
|Asahi Kasei||15||Unlock Company Profile|
|Henkel||15||Unlock Company Profile|
|Caterpillar||14||Unlock Company Profile|
|China Petrochemical||13||Unlock Company Profile|
|Deere & Co||13||Unlock Company Profile|
|Exxon Mobil||13||Unlock Company Profile|
|IHI||12||Unlock Company Profile|
|Korea Electric Power||11||Unlock Company Profile|
|Dow||10||Unlock Company Profile|
|Kurita Water Industries||10||Unlock Company Profile|
|Epiroc||10||Unlock Company Profile|
|Hyundai Motor Group||9||Unlock Company Profile|
|China National Petroleum||8||Unlock Company Profile|
|Formosa Plastics Group||8||Unlock Company Profile|
|Komatsu||8||Unlock Company Profile|
|State Grid Hubei Electric Power||8||Unlock Company Profile|
|Smiths Group||8||Unlock Company Profile|
|State Grid Jibei Electric Power||8||Unlock Company Profile|
|AMETEK||7||Unlock Company Profile|
|ABB||7||Unlock Company Profile|
|Enel||7||Unlock Company Profile|
|China Railway Signal & Communication||6||Unlock Company Profile|
|Lincoln Electric Holdings||6||Unlock Company Profile|
|China National Offshore Oil||5||Unlock Company Profile|
|Showa Denko||5||Unlock Company Profile|
|China Huaneng Group||5||Unlock Company Profile|
|Centrica||5||Unlock Company Profile|
|China Energy Investment||5||Unlock Company Profile|
|Itron||5||Unlock Company Profile|
Source: GlobalData Patent Analytics
Siemens is one of the leading patent filers in AI-driven workflow management, and its Xcelerator software package enables rapid digital transformation. The package assists with data collection, analysis, and visualisation. Siemens recently released NX software, a part of the Xcelerator package, that uses AI to improve process and helps engineers, designers, and manufacturers to innovate more rapidly.
The DS365.ai cloud solution from Halliburton uses machine learning and AI models to assist its customers in optimising their digital transformation through intelligent automation. The service aids in improving productivity, efficiency, and asset value in industries.
AI is expected to become vital over the coming years as companies increasingly adopt workflow automation in their businesses. The benefits include improving communication and rapid development of processes through features such as drag-and-drop and easy to use interfaces.
To further understand how artificial intelligence is disrupting the oil & gas industry, access GlobalData’s latest thematic research report on AI in Oil & Gas.