Artificial Intelligence (AI) in Oil and Gas – Thematic Research
- Pages: 48
- Published: March 2021
- Report Code: GDOG-TR-S046
The oil and gas (O&G) industry faces many severe challenges. The shortage of easily accessible hydrocarbon reserves forces companies to use remote reserves that are hard to discover, costly, and risky. Moreover, sustainability concerns are shifting demand away from O&G toward cleaner sources, and COVID-19 has further suppressed the demand. Finally, as ever, huge operational expenses and the asset-heavy nature of the industry make adaptation slow and difficult.
GlobalData’s Emerging Technology Trends 2020 survey found that 84% of O&G executives expect artificial intelligence (AI) to help their company survive the COVID-19 crisis.
The pandemic will eventually relent, but the other challenges will not. Oil prices will not return to the highs of 2014 and before. Companies must resist conventional expense reduction measures and instead invest in technological transformation. The market has changed, and evolution is necessary. Companies that can become more efficient, more effective, and more aligned with the market’s direction will survive and thrive.
O&G companies collect exceptional quantities of data, but a large share of it goes unused. Harnessing the power of this data could deliver companies from the downturn and position them for long-term success. Artificial intelligence is the best tool for the job. The O&G AI platforms market was worth $2.1bn in 2020, and it will have doubled in size by 2024.
AI is already widely used in predictive maintenance models (which fortify asset integrity by pre-empting failures), hydrocarbon discovery, and operational streamlining. Companies cannot afford to forego the efficiency gains these popular use cases offer, but industry adoption is still inchoate. With O&G companies seeking carbon neutrality within the next three decades, industry-wide upheaval is inevitable. There is a profound opportunity for companies to excel by using AI in bold new ways.
Machine learning (ML) and data science are the most attractive investments. They are the most mature technologies, and their effectiveness has been proven by other industries. No companies in the O&G industry can hope to compete with the AI chips specialist foundries are producing. Conversational platforms, computer vision, smart robots, and context-aware computing show promise but are still nascent.
Comprehensive AI value chain. Identification of the seven key AI technologies, explanation of what they are, how they are used, and how sophisticated they currently are. Identification of the leading AI vendors, specialist AI vendors, and leading oil & gas adopters for each of the seven technologies.
Explanation of how AI can help five key challenges facing the oil & gas industry: COVID-19, sustainability, resource availability, skill development, and operational cost reduction.
Listing of all AI-related M&A activity in oil & gas industry from 2018-present.
Extensive coverage and analysis of relevant companies’ relative positions in the AI theme: 8 oil & gas AI adopters, 17 leading AI vendors, and 12 specialist oil & gas AI vendors.
Forecast valuations of the AI platforms in oil & gas market up to 2024. AI platforms in oil & gas market share by country, 2020.
Data on oil & gas executive sentiment towards AI, on how COVID-19 has changed that sentiment, and on how many are already investing in AI.
Unique thematic scorecard that ranks oil & gas companies according to their positioning in the ten themes most important to the industry, of which AI is one.
According to GlobalData’s patents database, the oil & gas sector’s interest in AI is exploding. 2020 saw more than twice as many AI-related patents in 2020 (177 applications and grants) than 2016 (85) . Executives know that to survive the current downturn, and later thrive, is a matter of making the right investments.
AI helps O&G companies resolve the problem of resource availability. Most majors are already using AI to augment exploration. It reduces both time and cost. BP’s collaboration with Bluware improves subsurface data interpretation. ExxonMobil partnered with MIT’s AI lab to develop AI-powered, submersible exploration robots. Gazprom’s collaboration with IBM improves the analysis of geological and geophysical data.
The three most expensive disclosed AI-related acquisitions in O&G since 2018 were: ViaSat’s December 2020 acquisition of RigNet for $222m, Wartsilla’s March 2018 acquisition of Transas Marine for $258m, and Akka Technologies’ December 2019 acquisition of Data Respons for $457m.
Of the top 35 oil & gas companies globally, GlobalData assigns a maximum 5/5 score to three companies on the AI theme: Shell, Gazprom, and Rosneft. Seven companies receive a good score, six receive a neutral score, ten receive a lagging score, and nine receive a minimum 1/5 score.
One case study in the report concentrates on BP’s use of Kelvin’s sensors to reduce methane emissions. Kelvin specializes in automating physical systems using AI. Six months after implementation, a 74% reduction in methane leaks was observed. Production volumes increased by 20%, and operating costs decreased by 22%.
Reasons to buy
Survive the current downturn by understanding how AI can help navigate the problems presented by low oil prices, sustainability concerns, and COVID-19.
Identify leading AI vendors in oil & gas and shortlist potential partners based on their areas of expertise and historic partnerships.
Position yourself for future success by investing in the right AI technologies. Cut through the noise with GlobalData’s invest-explore-ignore ratings for each AI technology for each segment of the industry (upstream, midstream, downstream, and end customer).
Uncover the oil & gas companies excelling in AI implementation with GlobalData’s thematic scorecard. Understand and replicate their success with the extensive coverage of each leading company’s activity in the companies section.
Develop relevant and credible sales and marketing messages for O&G companies by understanding key industry challenges and which AI products are desired.
Identify attractive investment targets by understanding which companies are most advanced in the themes that will determine future success in the O&G industry.
Table of Contents
AI value chain
Oil & gas challenges
The impact of AI on oil & gas
Market size and growth forecasts
Mergers and acquisitions
Our thematic research methodology
List of Tables
The key challenges facing the oil & gas sector
Mergers and acquisitions
Leading AI adopters in oil & gas
Leading AI vendors
Specialist AI vendors in oil & gas
List of Figures
Key players in the AI value chain
The AI value chain
Big Tech is dominating ML
Machine learning: leaders and disruptors
Data science: leaders and disruptors
Virtual assistants are now part of everyday life, and they are getting more sophisticated
The enterprise landscape looks different from the consumer one
Conversational platforms: leaders and disruptors
There are four key CV software technologies
Computer vision: leaders and disruptors
There are several types of AI chips
AI chips: leaders and disruptors
Smart robots: leaders and disruptors
Context-aware computing: leaders and disruptors
The O&G sectors interest in AI is exploding
Thematic impact assessment
BP’s partnership with Kelvin produced significant results
O&G AI platform market size will reach $5.3bn by 2024, up from $1.8bn in 2019
84% of O&G executives expect AI to help their company survive the COVID-19 crisis
O&G companies are investing in AI, and sentiment is improving
The US, the Middle East, and China are the major markets
The AI story
Integrated oil & gas scorecard