市場調查報告書
商品編碼
1126525
石油和天然氣中人工智能的全球市場規模、份額和行業趨勢分析報告:按運營(上游、中游、下游)、組件(解決方案、服務)、地區、2022-2028 年的展望和預測Global AI in Oil and Gas Market Size, Share & Industry Trends Analysis Report By Operation (Upstream, Midstream and Downstream), By Component (Solution and Services), By Regional Outlook and Forecast, 2022 - 2028 |
到 2028 年,全球石油和天然氣領域的人工智能市場規模預計將達到 52 億美元,在預測期內以 13.2% 的複合年增長率增長。
採礦、石油和天然氣以及建築行業的公司是數字化的後來者,但現在更多地依賴人工智能解決方案。石油和天然氣行業在 1970 年代首次探索使用人工智能,但直到最近才開始探索更積極地使用人工智能的前景。這是為了響應行業向“石油和天然氣 4.0”心態的轉變,這主要是通過尖端數字技術增加價值,以及人工智能能力的指數級增長。
對於石油和天然氣公司而言,人工智能(和其他數字化努力)的主要目的是提高效率,因為他們採用新技術的速度比他們試驗和改變業務戰略的速度要快得多。在實踐中,通常會降低風險並加快流程。在過去的十年中,人工智能 (AI) 和機器學習技術在石油和天然氣行業的應用受到了廣泛關注。
因此,該領域的人工智能市場正在擴大。過去油氣部門在油氣發現和生產方面的難度越來越大,導致跨部門戰略,需要一些關鍵任務的半自動化和全自動化。勘探過程的每個階段,包括地質學、地球物理學和油藏工程,都在通過人工智能實現自動化。
COVID-19 影響分析
由於 COVID-19 大流行和封鎖,對石油和天然氣的需求有所下降。例如,國際能源署估計,到 2020 年第二季度,石油需求將每天減少 100 萬桶。然而,在這種特殊情況下,人工智能在石油和天然氣領域的使用正在顯著擴大。這場危機對社會的許多方面產生了直接和間接的影響。對於病毒爆發的臨時監控和遏制,數字和人工智能行業可以成為寶貴的專業資源。
市場增長因素
分析和提煉數據並識別缺陷
在石油和天然氣行業,在定位管道中的不當螺紋和容易發生故障的設備中的缺陷方面存在許多挑戰。稍後在生產線上發現未發現的缺陷。因此,損害和損失很高,對企業來說是一個沉重的負擔。但在人工智能和基於計算機視覺的系統的幫助下,評估輸出質量變得更加容易。此外,它徹底討論了分析的缺點。
利用分析降低生產和維護成本並改進決策
石油和天然氣在開採後存儲在中央倉庫中。從那裡它將通過管道分發。溫度和天氣的差異會導致石油和天然氣成分變質和腐蝕,削弱管道的狀況,使螺紋變細。這是該領域的大問題之一。石油和天然氣企業必須主動解決這些問題,以防止產生不利後果。該行業或許能夠通過集成人工智能解決方案來阻止此類事件的發生。
市場限制
缺乏合格的人工智能技術專業人士
AI 處理器的操作是一種極其先進的解決方案,需要高級教育和技能。近年來,人工智能在人類中迅速傳播。從自動駕駛汽車到提供食物的餐廳機器人,世界各地的人們都在日常生活中使用人工智能應用程序。此外,機器人研究正在安全、醫療保健和太空開發等各個領域進行。
組件透視
基於組件,石油和天然氣市場中的人工智能被細分為解決方案和服務。到 2021 年,服務部門在石油和天然氣市場的人工智能中將獲得可觀的收入份額。 AI 服務是現成的機器學習驅動服務的集合,可簡化 AI 在開發人員的軟件和業務流程中的部署。
操作 Outlook
根據運營,油氣領域的AI市場分為上游、中游和下游。上游部分將在 2021 年佔據石油和天然氣領域人工智能市場的最大收入份額。這包括尋找可能埋在地下或海中的原料天然氣和原油,鑽探測試井,以及鑽探和操作井以將原料天然氣和原油帶到地表。
區域展望
按地區,分析了北美、歐洲、亞太地區和拉美地區的石油和天然氣市場中的人工智能。 2021 年,北美地區在石油和天然氣領域的人工智能市場中獲得了最高的收入份額。石油和天然氣行業對人工智能的需求受到該地區強勁經濟、油田運營商和服務提供商對人工智能技術的高度採用、領先的人工智能軟件和系統提供商的強大存在以及研發活動的增長和發展的推動。預計它將受到政府和私人組織的合併和投資等因素的推動。
合作和收購是市場參與者採取的主要策略。根據 Cardinal Matrix 中的分析,Microsoft Corporation是石油和天然氣市場人工智能的先驅。Intel Corporation、Cisco Systems, Inc.、NVIDIA Corporation等公司是石油和天然氣領域人工智能市場的一些領先創新者。
The Global AI in Oil and Gas Market size is expected to reach $5.2 billion by 2028, rising at a market growth of 13.2% CAGR during the forecast period.
The fastest-growing general-purpose technology of the modern age is artificial intelligence (AI), which has enormous potential for growth and innovation. AI has already resulted in significant modifications and altered the competition rules in the fields of industrial, healthcare, transport, retail, media, and finance.
Companies in these sectors now generate value by utilizing AI solutions rather than depending on conventional, human-centered business processes. The value creation process is driven by sophisticated algorithms that have been trained on substantial and meaningful datasets and are constantly fed new data. However, businesses outside of those with a strong internet presence can also benefit from AI.
Companies in the mining, oil, gas, and construction industries were late adopters of digitization, but they now rely more and more on AI solutions. Although the oil and gas sector first investigated using AI in the 1970s, the sector only recently began to seek more aggressive AI application prospects. It corresponds with the industry's shift toward the Oil and Gas 4.0 idea, whose main objective is to increase value through cutting-edge digital technology, and the exponential rise of AI capabilities.
Oil and gas businesses' main goal with AI (and other digitalization efforts) is to increase efficiency because they adopt new technologies much more quickly than they experiment with and alter their business strategies. In actuality, that usually means reducing risks and speeding up processes. The application of artificial intelligence (AI) and machine learning technologies in the oil and gas industry has attracted a lot of attention during the last ten years.
This has caused the market for artificial intelligence in this sector to expand. Due to the rising difficulties, the oil and gas sector has had in the past when it comes to the discovery and production of hydrocarbons, a cross-disciplinary strategy is being used, necessitating the semi-automation and complete automation of several crucial operations. Every step of the exploration process, including geology, geophysical, and reservoir engineering, is being automated with artificial intelligence.
COVID-19 Impact Analysis
Demand for oil and gas decreased as a result of the COVID-19 pandemic and lockdowns. For instance, the International Energy Agency estimates that the oil demand declined by million barrels per day by the second quarter of 2020. However, in these exceptional conditions, AI use in the oil and gas sector has greatly expanded. In many facets of society, this crisis had several direct and indirect repercussions. To monitor and contain the virus pandemic in the interim, the digital and artificial intelligence industries can be a valuable professional resource.
Market Growth Factors
The Analysis And Improvement Of Data, As Well As The Identification Of Faults
The oil and gas business encounters numerous difficulties in identifying improper threading in pipes and flaws in devices that are prone to error. The production line later discovers the flaws that were not discovered before. This results in greater damages and losses and comes at a high cost to a business. However, it becomes simple to assess the quality of output when using AI and implementing a computer-vision-based system. Additionally, it offers thorough details on analytics flaws.
Utilize Analytics To Lower Production And Maintenance Costs And Improve Decision-Making
Oil and gas are kept in a central repository after extraction. It is then distributed by pipelines from there. Different temperatures and weather conditions cause oil and gas components to deteriorate and corrode, which can weaken the condition of the pipeline and result in faded threading. One of the main issues facing the sector is this. To prevent unfavorable outcomes, the oil and gas business must proactively address these concerns. The industry may help to stop any such incidents from happening by integrating AI solutions.
Market Restraining Factors
Lacking Competent Professionals In Ai Technology
An extremely advanced solution, the AI processor demands a high level of education and skills to operate. Artificial intelligence has quickly become popular among humans in recent years. People throughout the world use applications of artificial intelligence in their daily lives, such as self-driving automobiles and restaurant robots that serve food. For instance, robotic research is used in many different fields, such as security, healthcare, space exploration, and a plethora of other scientific fields.
Component Outlook
On the basis of Components, the AI in Oil and Gas Market is segmented into Solutions and Services. The service segment witnessed a significant revenue share in the AI in Oil and Gas Market in 2021. AI Services is a group of services with ready-made machine learning that simplify the deployment of AI to software and business processes for developers.
Operation Outlook
Based on the Operation, the AI in Oil and Gas Market is divided into Upstream, Midstream, and Downstream. The upstream segment garnered the largest revenue share in the AI in Oil and Gas Market in 2021. It involves looking for possible raw natural gas and crude oil reserves that are underground or beneath the sea, drilling test wells, and then drilling and running the wells that will bring the raw natural gas or crude oil to the surface.
Regional Outlook
Region-wise, the AI in Oil and Gas Market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America region procured the highest revenue share in the AI in Oil and Gas Market in 2021. Due to the demand for AI in the oil and gas industry is anticipated to be driven by elements including the region's robust economy, the high adoption rate of AI technologies among oilfield operators and service providers, a strong presence of leading AI software and system providers, and merged investment by government and private organizations for the growth and development of R&D activities.
The major strategies followed by the market participants are Partnerships and Acquisitions. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation are the forerunners in the AI in Oil and Gas Market. Companies such as Intel Corporation, Cisco Systems, Inc., NVIDIA Corporation are some of the key innovators in AI in Oil and Gas Market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, Oracle Corporation, Intel Corporation, IBM Corporation, Cisco Systems, Inc., Accenture PLC, NVIDIA Corporation, Cloudera, Inc., C3.ai, Inc. and FuGenX Technologies (USM Business Systems, Inc.).
Recent Strategies Deployed in AI in Oil and Gas Market
Partnerships, Collaborations and Agreements:
Apr-2022: Microsoft came into a partnership with Bharat Petroleum Corporation, the leading oil and Gas Company in India. Together, the companies aimed to open the possibilities that Microsoft's cloud delivers to manage the special difficulties of the oil and gas sector, allowing BPCL to boost the modernization of its tech architecture. Additionally, this would improve and redefine the consumer experience.
Mar-2022: Cloudera partnered with Kyndryl, American multinational information technology. Through this partnership, the companies aimed to support consumers allow and push their mission-critical multi-cloud, hybrid cloud, and edge computing data industries. Additionally, a joint innovation center to create combined industry keys and delivery abilities developed to enable consumers to boost their motion and migration to the cloud platform and environment of their choice.
Nov-2021: IBM joined hands with Amazon Web Services, a subsidiary of Amazon. Together, the companies aimed to integrate the advantages of IBM Open Data for Industries for IBM Cloud Pak for Data and the AWS Cloud to benefit energy consumers. Additionally, This complete solution is developed on Red Hat OpenShift and would run on the AWS Cloud, streamlining the capacity for consumers to operate workloads in the AWS cloud and on-premises.
Sep-2021: C3 AI came into a partnership with Baker Hughes, an energy technology company. Through this partnership, the companies aimed to deploy the BHC3 Production Optimization enterprise AI application at MEG Energy, an Alberta, Canada -based energy firm, to enhance operational effectiveness, and productivity, and to nicely envision threats across the company's upstream production procedures. Moreover, BHC3's advanced business AI-based solutions would further promote the differentiated, proprietary technology leverage to secure safe, sustainable production of energy.
Jun-2021: C3 AI formed a partnership with Snowflake, the Data Cloud Company. This partnership aimed to integrate Snowflake's unique architecture which permits consumers to run their data platforms smoothly across numerous clouds and regions at scale. Additionally, with C3 AI's robust corporation AI development offering and family of industry-specific firm AI, applications businesses can instantly boost and emanate economic value from their data and business AI ambitions.
Apr-2021: Accenture joined hands with Bharat Petroleum Corporation, the greatest oil and gas company in India. Through this collaboration, the companies aimed to convert India's second-largest oil and gas business by digitally reimagining its comprehensive sales and distribution network. Moreover, Accenture would use its abilities in artificial intelligence, data, and cloud technologies to design, build, and execute a digital platform, called IRIS.
Product Launches and Product Expansions:
Jun-2022: NVIDIA expanded its partnership with Siemens, a German multinational conglomerate corporation. This expansion aimed to allow the industrial metaverse and advance the utilization of AI-driven digital twin technology that would assist in obtaining industrial automation to a new deck. Additionally, The companies intend to combine Siemens Xcelerator, the open digital business platform, and NVIDIA Omniverse, a medium for 3D design and teamwork. Moreover, This would allow an industrial metaverse with physics-based digital samples from Siemens and real-time AI from NVIDIA in which businesses make conclusions faster and with improved confidence.
Mar-2022: NVIDIA introduced an update to its AI platform to unveil its AI Accelerated program. NVIDIA's AI platform is a software offering for advancing workloads, including recommender system, speech, and hyper-scale belief. Moreover, NVIDIA AI is the software toolbox of the world's AI society, from AI data scientists and researchers to data and machine learning procedures sections.
Nov-2021: Oracle introduced Oracle Cloud Infrastructure AI services, a cluster of services. The new OCI AI services provide designers the option of utilizing out-of-the-box models that have been prepared on business-based data or traditional training the services based on their firm's data.
Jun-2021: IBM along with Schlumberger unveiled the industry's first commercial hybrid cloud Enterprise Data Management Solution for the OSDU Data Platform. The new solution would deliver energy operators with complete interoperability, creating their data available by any application within their exploration to production conditions through the OSDU common data standard to allow comfortable sharing of information between teams. Additionally, the solution is engineered to decrease the time for data transfers between applications to provide smaller costs along with enhanced decision making.
Mar-2020: Accenture along with SAP unveiled SAP S/4HANA Cloud. The new SAP S/4HANA Cloud solution for lifts oil and gas helps customers to further enhance transparency into processes and cash flow. Additionally, the companies are providing a solution that conveys innovative technologies such as AI to provide greater visibility, real-time insights, and adequate decision-making.
Acquisitions and Mergers:
Aug-2022: Accenture completed the acquisition of Tenbu, a cloud data business that specializes in solutions for intelligent decision-making. This acquisition aimed to expand Accenture's abilities to assist businesses to steer new services, development, and stability by utilizing data from the cloud continuum for intelligent decision-making.
Mar-2022: Microsoft took over Nuance Communications, a leader in conversational AI and ambient intelligence. This acquisition would allow alliances across industries to boost their company goals with security-focused, cloud-based solutions ingrained with powerful, vertically optimized AI. Additionally, Consumers would profit from an improved clinician, patient, consumer, and employee experiences, and eventually enhanced productivity and financial performance.
Feb-2022: IBM completed the acquisition of Neudesic, a US-based cloud services consultancy. With this acquisition, the company aimed to extend IBM's offering of hybrid multi-cloud services and additional passage of the enterprise's AI strategy and hybrid cloud.
Oct-2021: Cisco completed the acquisition of Epsagon, a privately held, modern observability company. Through this acquisition, Epsagon's technology with Cisco's dream to allow businesses to provide unmatched application experiences via industry-leading solutions with serious industry context. Moreover, by linking and contextualizing visibility and insights around the complete stack, teams can enhance collaboration to better understand their systems, solve issues fast, optimize and ensure application incidents and satisfy their consumers.
Oct-2021: Accenture took over BRIDGEi2i, a Bengaluru-based AI and analytics company. Through this acquisition, the company aimed to further improve its AI skills and data science abilities to reinforce how enterprise global network provides value for consumers.
Mar-2021: Cisco took over Acacia Communications, an optical networking strategy, and technology business. This acquisition would strengthen Cisco's responsibility to optics as a crucial building block that would improve Cisco's Internet for the Future process with supreme coherent optical solutions for consumers, also allowing them to manage the unprecedented scale of current IT.
Geographical Expansions:
Jun-2022: Intel India expanded its geographical footprints by establishing the design and engineering of a new state-of-the-art building in Bengaluru. The new addition accommodates 2,000 workers and would help promote cutting-edge innovation and engineering work in client, artificial intelligence, data center, graphics, IoT, and automotive segments.
Market Segments covered in the Report:
By Operation
By Component
By Geography
Companies Profiled
Unique Offerings from KBV Research
List of Figures