Machine Learning in Oil & Gas - Thematic Research
Oil and gas industry is going through a challenging phase after having to face disruptions in the form of sluggish oil prices and opposition to hydrocarbon exploration and production from environmentalists. In such a scenario, oil and gas companies are increasingly turning towards digital technologies, such as machine learning, to improve operational efficiency while ensuring negligible impact to the environment. Real-time data generated from various industrial activities is being captured and analyzed using machine learning algorithms to enable field operators in taking informed decisions for achieving higher productivity and cost savings, while also ensuring the overall health and safety of the assets.
- The report provides impact of machine learning on the oil & gas industry.
- The report discusses how oil and gas industry is benefiting from machine learning techniques in predictive maintenance of equipment and scheduling maintenance programs to proactively fix the faults.
- The report analyses how oil and gas companies are transforming themselves by deploying machine learning and other digital technologies
- The report further shows the adoption of machine learning techniques in analysis of seismic data for detecting and quantifying hydrocarbon reserves.
- The report also shows how machine learning helps in efficiency improvement across various activities in the oil and gas industry.
Reasons to buy
- To understand emerging trends and applications for machine learning in the oil and gas industry.
- Know case studies demonstrating how oil and gas companies are using machine learning for enhanced operational performance and improved business competitiveness.
- To Know more about companies in the oil and gas sector, which have strong competitive position in the machine learning theme.
TECHNOLOGY BRIEFING 4
Ten key AI technologies 4
History of machine learning 5
How does deep learning work? 6
Technology trends 8
Macro-economic trends 10
Use case trends 12
Applications of Machine Learning in Oil & Gas 13
VALUE CHAIN 14
Hardware enablers 15
Optimised networking equipment 15
High end processors 16
Communication chips 17
Embedded chips 18
Software enablers 19
Master data management 19
AI engine 20
Developer tools (APIs and SDKs) 21
Software with embedded AI 22
INDUSTRY ANALYSIS 23
AI and ML likely to become widespread because too much is open sourced 25
AI and ML are transforming the semiconductors market 26
IMPACT OF MACHINE LEARNING ON OIL & GAS 30
Oil & gas case studies in ML 30
COMPANIES SECTION 32
Listed tech companies 32
Privately held tech companies 35
Oil & gas companies 36
APPENDIX: OUR THEMATIC RESEARCH METHODOLOGY 38
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