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石油・ガス部門におけるAIの世界市場:2019年-2026年

Global AI in Oil and Gas Market - 2019-2026

発行 DataM Intelligence 商品コード 950563
出版日 ページ情報 英文
納期: 即日から翌営業日
価格
本日の銀行送金レート: 1USD=107.57円で換算しております。
石油・ガス部門におけるAIの世界市場:2019年-2026年 Global AI in Oil and Gas Market - 2019-2026
出版日: 2020年07月18日 ページ情報: 英文
概要

人工知能(AI)は、今後の石油・ガス部門の成長に多大な影響を及ぼすと予測されています。石油・ガス業界でも、自動化によって安全性と生産性を迅速に改善することができるため、AIの導入が加速しています。この業界では、探鉱開発にまつわる様々な課題に対処し、従業員へのリスクを軽減するため、重要なプロセスを半自動化したり、一部を完全に自動化する取り組みが進められています。Motorola Solutionsによると、 世界の石油セクターにおけるAIの需要は、2035年までに約33%増加するといいます。

当レポートは、世界の石油・ガス部門におけるAIの市場を調査したもので、市場の力学、業界の分析、タイプ別、機能別、用途別、地域別の分析、競合情勢、企業プロファイルなどの情報を提供しています。

目次

第1章 調査手法と範囲

  • 調査手法
  • 調査目的と範囲

第2章 市場の定義と概要

第3章 エグゼクティブサマリー

  • タイプ別市場
  • 機能別市場
  • 用途別市場
  • 地域別市場

第4章 市場の力学

  • 市場に影響を与える要因
    • 促進要因
    • 抑制要因
    • 影響分析
  • 市場機会
  • 動向

第5章 業界分析

  • ポーターのファイブフォース分析
  • サプライチェーン分析
  • 規制分析
  • 価格分析

第6章 市場分析:タイプ別

  • イントロダクション
    • 市場規模と前年比成長率の分析
    • 市場魅力指数
  • ハードウェア*
  • ソフトウェア
  • サービス

第7章 市場分析:機能別

  • イントロダクション
    • 市場規模と前年比成長率の分析
    • 市場魅力指数
  • 予知保全、機械検査*
  • 現場サービス
  • 材料移動
  • 品質管理
  • 再生
  • 生産計画

第8章 市場分析:用途別

  • イントロダクション
    • 市場規模と前年比成長率の分析
    • 市場魅力指数
  • 上流部門*
  • 中流部門
  • 下流部門

第9章 市場分析:地域別

  • イントロダクション
    • 市場規模と前年比成長率の分析
    • 市場魅力指数
  • 北米
  • 欧州
  • 南米
  • アジア太平洋
  • 中東・アフリカ

第10章 競合情勢

  • 競合シナリオ
  • 市場でのポジションとシェアの分析
  • 合併と買収の分析

第11章 企業プロファイル

  • IBM *
  • Intel
  • Google
  • Microsoft
  • Oracle
  • Sentient technologies
  • Inbenta
  • General Vision
  • Cisco
  • Hortonworks
  • List is not exhaustive

第12章 主な調査結果

第13章 DataM Intelligence について

目次

Market Overview

Artificial intelligence is projected to be a key influencing factor for the growth of the oil and gas sector in the upcoming years. The technology revolution in oil and gas industry is taking off because of improvising safety and productivity that can be achieved by automation. With increasing challenges faced by the oil and gas industry in the past for exploration and exploitation of hydrocarbons, a cross-disciplinary approach is being rendered which requires some critical processes to be semi-automated and some to be fully automated. It can also reduce the risk to human workers. According to Motorola Solutions, the demand for the AI in the global oil sector is expected to increase by about 33%, by 2035. The AI in Oil and Gas market valued USD XX million in 2018 and it is expected to grow at a CAGR of XX% to reach USD XX million by 2026.

Market Dynamics:

Increasing safety concerns among the workforce, especially the maintenance of aging pipeline infrastructure is the major driving agent in the growth of the AI in Oil and Gas market. Additionally, the surging incidents of oil & gas leakage from storage tanks and pipelines at production facilities are expected to fuel the growth of the market. Organizations across the world are trying to make the exploration and the production processes more efficient and optimized. The operations in this field are the major factors that are driving the usage of AI in oil and gas companies. The AI tools can help oil and gas companies in digitizing records and can automate the analysis of the gathered geological data and charts, which can lead to potential identification of issues, such as pipeline corrosion or increased equipment usage. For instance, For instance, in Jan 2019, BP invested in a technology start-up: Belmont Technology to strengthen the company's AI capabilities by developing a cloud-based geoscience platform. The investment will be used to support BP's ongoing work in exploring the application of cognitive computing and machine learning in its global oil and gas business.

In the exploration and production space, it can be challenging making sense of extensive amounts of data for valve positions, pump speeds, pressures at different places in the system, temperatures and flow rates, etc. Decision-makers reviewing the data might be using it in a simplified manner or not at all. AI allows companies to review the data in a shorter amount of time, discover patterns that likely were not previously observable and determine the best course of action. For instance, the Oil and Gas Authority (OGA) is making use of AI in parallel ways, owing to the United Kingdom's first oil and gas National Data Repository (NDR), launched in March 2019, using AI to interpret data, which, according to the OGA anticipations, is likely to assist to discover new oil and gas forecast and permit more production from existing infrastructures. However, high capital investments for the integration of AI technologies, along with the lack of skilled AI professionals, could hinder the growth of the market. A recent poll validated that 56% of senior AI professionals considered that a lack of additional and qualified AI workers was the only biggest hurdle to be overcome, in terms of obtaining the necessary level of AI implementation across business operations.

Segment Analysis

The AI in Oil and Gas market is segmented based on the basis of type, function and application. By type segment the AI in oil and gas market is classified into hardware, software and services. For instance, Calgary-based Ambyint has developed intelligent High-Resolution Adaptive Controllers (HRACs) which integrate with the hardware and instrumentation, such as the motor, controller, variable frequency drive, and other moving parts of lift systems. The adaptive controllers can deliver real-time control and optimization capabilities at the well, leveraging edge computing capabilities to deliver both physics-based analytics and modern data science in real time. By function, the AI in oil and gas market is classified into predictive maintenance and machinery inspection, field services, material movement, quality control, reclamation, and production planning. Predictive maintenance and machinery inspection is the fastest growing segment in the AI in oil and gas market globally. By application, the market is classified into upstream, midstream, and downstream. The upstream segment is set to dominate the AI in oil and gas market globally.

The growth in the shale oil and gas production in the US is creating the need for an expanded midstream network of pipelines, rail, tankers, and terminals. AI is widely used in the midstream sector to gather data during the transportation process through pipelines and provide the same to the human-machine interface in order to control the process. In the Oil & Gas industry these tools have been used to solve problems such as pressure transient analysis, well log interpretation, reservoir characterization, and well selection for stimulation, among others.

Geographical Presentation

By region, the AI in Oil and Gas market is segmented into North America, South America, Europe, Asia-Pacific, Middle-East, and Africa. Among all of the regions, North America dominated the AI in Oil and Gas market due to the increasing adoption of AI technologies across the oilfield operators and service providers and the robust presence of prominent AI software and system suppliers, especially in the United States and Canada, the North American segment is anticipated to account for the largest share of the AI in the oil and gas market, over the forecast period. Moreover, Factors, such as the strong economy, the high adoption rate of AI technologies across the oilfield operators and service providers, robust presence of prominent AI software and system suppliers, and combined investment by government and private organizations for the development and growth of R&D activities are poised to drive the demand for AI in oil and gas sector, in the region.

For instance, ExxonMobil, one of the leading oil producers in the country, announced its plans to increase the production activity in the Permian Basin of West Texas, by producing more than 1 million barrels per day (BPD) of oil-equivalent by as early as 2024. This is equivalent to an increase of nearly 80 percent compared to the present production capacity.

Competitive Analysis

Key players operating in the market are IBM, Intel, Google, Microsoft, Oracle, Sentient technologies, Inbenta, General Visio and Cisco (United States) are some of the key players profiled in the study. Additionally, the Players which are also part of the research are FuGenX Technologies, Infosys, Hortonworks and Royal Dutch Shell. Leading multinational players dominate the market and hold substantial market share, thereby, presenting tough competition to new entrants. Key players focus on various strategic initiatives such as merger & acquisition, geographical expansion, new product launch and increasing R&D expenditure to stay competitive in the market. For instance, in February 2020, Royal Dutch Shell PLC has been expanding an online program that teaches its employees artificial intelligence skills, part of an effort to cut costs, improve business processes, and generates revenue. Artificial intelligence enables the company to process the vast quantity of data across the businesses to generate new insights, which can keep the ahead of the competition.

In October 2019, Microsoft announced the collaboration with energy industry tech company Baker Hughes and AI developer C3.ai to bring enterprise AI technology to the energy industry via its Azure cloud computing platform. It would allow customers to streamline the adoption of AI designed to address issues like inventory, energy management, predictive maintenance and equipment reliability.

Why Purchase the Report?

  • Visualize the composition of the AI in Oil and Gas market products in terms of data type, business function, component, deployment model, organization size, and industrial vertical highlighting the critical commercial assets and players.
  • Identify commercial opportunities in the AI in Oil and Gas market by analyzing trends and co-development deals.
  • Excel datasheet with thousands of data points of global AI in Oil and Gas market-level4/5segmentation.
  • PDF report with the most relevant analysis cogently put together after exhaustive qualitative interviews and in-depth market study.
  • *The global AI in Oil and Gas market report will provide access to approximately 61 Market data tables, 49 figures, and 178 pages

Target Audience

  • AI manufacturers and suppliers
  • AI system providers
  • Environmental research institutes
  • Government and research organizations
  • Institutional investors
  • National and local government organizations
  • Research organizations and consulting companies
  • Technology providers

Table of Contents

1. Global AI in Oil and Gas Market Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Global AI in Oil and Gas Market-Market Definition and Overview

3. Global AI in Oil and Gas Market-Executive Summary

  • 3.1. Market Snippet by Type
  • 3.2. Market Snippet by Function
  • 3.3. Market Snippet by Application
  • 3.4. Market Snippet by Region

4. Global AI in Oil and Gas Market-Dynamics

  • 4.1. Market Impacting Factors
    • 4.1.1. Drivers
    • 4.1.2. Restraints
    • 4.1.3. Impact Analysis
  • 4.2. Opportunity
  • 4.3. Trends

5. Global AI in Oil and Gas Market-Industry Analysis

  • 5.1. Porter's Five Forces Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Regulatory Analysis
  • 5.4. Pricing Analysis

6. Global AI in Oil and Gas Market - By Type

  • 6.1. Introduction
    • 6.1.1. Market Size Analysis, and Y-o-Y Growth Analysis(%), By Type
    • 6.1.2. Market Attractiveness Index, By Type
  • 6.2. Hardware *
    • 6.2.1. Introduction
    • 6.2.2. Market Size Analysis,USDMn,2017-2026 and Y-o-Y Growth Analysis(%),2018-2026
  • 6.3. Software
  • 6.4. Services

7. Global AI in Oil and Gas Market - By Function

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis, and Y-o-Y Growth Analysis(%), By Function
    • 7.1.2. Market Attractiveness Index, By Function
  • 7.2. Predictive Maintenance & Machinery Inspection *
      • 7.2.1.1. Introduction
      • 7.2.1.2. Market Size Analysis,US$Mn,2016-2025 and Y-o-Y Growth Analysis(%),2018-2026
  • 7.3. Field Services
  • 7.4. Material Movement
  • 7.5. Quality Control
  • 7.6. Reclamation
  • 7.7. Production Planning

8. Global AI in Oil and Gas Market - By Application

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis, and Y-o-Y Growth Analysis(%), By Application
    • 8.1.2. Market Attractiveness Index, By Application
  • 8.2. Upstream*
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis, US$ Mn, 2016-2025 and Y-o-Y Growth Analysis (%), 2018-2026
  • 8.3. Midstream
  • 8.4. Downstream

9. Global AI in Oil and Gas Market-By Region

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis, andY-o-Y Growth Analysis(%),By Region
    • 9.1.2. Market Attractiveness Index, By Region
  • 9.2. North America
    • 9.2.1. Introduction
    • 9.2.2. Key Region-Specific Dynamics
    • 9.2.3. Market Size Analysis, and Y-o-Y Growth Analysis(%), By Type
    • 9.2.4. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Function
    • 9.2.5. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Application
    • 9.2.6. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Country
      • 9.2.6.1. U.S.
      • 9.2.6.2. Canada
      • 9.2.6.3. Mexico
  • 9.3. Europe
    • 9.3.1. Introduction
    • 9.3.2. Key Region-Specific Dynamics
    • 9.3.3. Market Size Analysis, and Y-o-Y Growth Analysis(%), By Type
    • 9.3.4. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Function
    • 9.3.5. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Application
    • 9.3.6. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Country
      • 9.3.6.1. Germany
      • 9.3.6.2. U.K.
      • 9.3.6.3. France
      • 9.3.6.4. Rest of Europe
  • 9.4. South America
    • 9.4.1. Introduction
    • 9.4.2. Key Region-Specific Dynamics
    • 9.4.3. Market Size Analysis, and Y-o-Y Growth Analysis(%), By Type
    • 9.4.4. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Function
    • 9.4.5. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Application
    • 9.4.6. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Country
      • 9.4.6.1. Brazil
      • 9.4.6.2. Argentina
      • 9.4.6.3. Rest of South America
  • 9.5. Asia Pacific
    • 9.5.1. Introduction
    • 9.5.2. Key Region-Specific Dynamics
    • 9.5.3. Market Size Analysis, and Y-o-Y Growth Analysis(%), By Type
    • 9.5.4. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Function
    • 9.5.5. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Application
    • 9.5.6. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Country
      • 9.5.6.1. China
      • 9.5.6.2. India
      • 9.5.6.3. Japan
      • 9.5.6.4. Australia
      • 9.5.6.5. Rest of Asia Pacific
  • 9.6. Middle East and Africa
    • 9.6.1. Introduction
    • 9.6.2. Key Region-Specific Dynamics
    • 9.6.3. Market Size Analysis, and Y-o-Y Growth Analysis(%), By Type
    • 9.6.4. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Function
    • 9.6.5. Market Size Analysis, and Y-o-Y Growth Analysis(%),By Application

10. Global AI in Oil and Gas Market Competitive Landscape

  • 10.1. Competitive Scenario
  • 10.2. Market Positioning/Share Analysis
  • 10.3. Mergers and Acquisitions Analysis

11. Global AI in Oil and Gas Market Company Profiles

  • 11.1. IBM *
    • 11.1.1. Company Overview
    • 11.1.2. Form Portfolio and Description
    • 11.1.3. Key Highlights
    • 11.1.4. Financial Overview
  • 11.2. Intel
  • 11.3. Google
  • 11.4. Microsoft
  • 11.5. Oracle
  • 11.6. Sentient technologies
  • 11.7. Inbenta
  • 11.8. General Vision
  • 11.9. Cisco
  • 11.10. Hortonworks
  • List is not exhaustive

12. Global AI in Oil and Gas Market-Premium Insights

13. Global AI in Oil and Gas Market-DataM

  • 13.1. Appendix
  • 13.2. About Us and Services
  • 13.3. Contact Us