This market is segmented on the basis of hardware into computational devices, storage devices, and networking devices. On the basis of services, the market is segmented into implementation tools (R, Python, Enterprise Control Language, Apache PIG, SAS, SPSS, and others), database (Mongo DB, Neo 4j, Apache Cassandra, Hypertable, Hyperdex, and others), software framework (Microsoft Upstream Reference Architecture, Apache Hadoop, Spark, High Performance Computing Cluster, and others), maintenance, and consulting. Lastly, on the basis of geography, the market has been segmented into North America, Europe, Africa, South and Central America, Asia-Pacific, and Middle East.
The most critical event of any oil & gas exploration process is drilling a well. This action requires a large amount of resources in terms of both personnel and equipment to be deployed at a remote location. The oil exploration and production work encompasses various activities, such as equipment maintenance, price optimization, production optimization, and safety & compliance. The chance of a failure simply manifolds the loss. The solution lies in the form of better data collection and improved analysis, which is possible through big data analysis.
Big data in the oil sector is captured from various sources, such as seismic reports, equipment monitoring, sensors, GPS services, historical data, weather patterns, and even social media. Some of the data is in the form of text, pictures, and multimedia, which may be structured or unstructured. The objective is also to reduce the challenges, so that the knowledge gap between the experienced and new oil workers is managed and the huge data collection through digital oilfield is streamlined.
Supervision and Data Acquisition (SCADA) is one of the most commonly used tools for data management. The advantage it presents is the ability to implement geological and scientific models for daily processes. Advanced subsurface models could be created and used for engineering service to identify prospective wells. Furthermore, the use of big data helps achieve higher efficiency through a better understanding of earths subsurface. To enable exploitation of data and generate required insights that are useful for business, multiple systems need to be utilized. A vast amount of data is generated during exploration due to the use of various sensors, such as 2D, 3D, and 4D seismic monitors. On an average, about 40,000 sensors are installed in a rig to measure various types of data including, acoustic, textual, and visual apart from numerical data. While only numerical data are used in traditional rig management systems, the other unstructured data is simply not used due to the lack of capability and infrastructure. Multiple solutions are available in the market to handle different challenges in big data platforms. These solutions are categorized under languages, databases, and frameworks.
Oil & gas exploration and production projects involve substantial investments and immense risk factors. So any technological attempt to increase efficiency and reduce cost is appreciated by the stakeholders. Enabling greater situational awareness requires real time gathering of data, which is ensured by the applications of big data. Oil companies around the world are facing the pressure of increasing exploration costs and any tool that helps in its reduction is appreciated. Furthermore, oil corporations have long standing challenges of ensuring safety of their employees, who operate in extreme locations and in hazardous conditions. Technology that reduces this worry is likely to be adopted by companies.
However, big data also faces the same pit falls associated with statistics as it is prone to misinterpretation at the hands of an uninitiated manager. The biggest issue that bothers companies using high technology is the availability of qualified personnel. The collection of huge quantity of data requires substantial investments in terms of both hardware and software. Another restraint for the use of big data is that most of it comes in various unstructured formats. New algorithms designed to be flexible enough to handle high volumes of unstructured data are needed to overcome this challenge.
Currently, the world market for big data is growing at a fast rate. New equipment are in the process of development and many are introduced into the market. The adopters of this technology have the chance to gain substantial competitive advantage. The benefits of big data include opportunity to create better asset utilization and high efficiency of operations.
Market analysis for the Global Big Data in Oil & Gas Exploration and Production Market, with region specific assessments and competition analysis on global and regional scales
Market definition along with the identification of key drivers and restraints
Identification of factors instrumental in changing the market scenarios, rising prospective opportunities, and identification of key companies that can influence this market on a global and regional scale
Extensively researched competitive landscape section with profiles of major companies along with their market shares
Identification and analysis of the macro and micro factors that affect the global big data in oil & gas exploration and production market on both global and regional scales
A comprehensive list of key market players along with the analysis of their current strategic interests and key financial information
A wide-ranging knowledge and insights about the major players in this industry and the key strategies adopted by them to sustain and grow in the studied market
Insights on the major countries/regions in which this industry is blooming and to also identify the regions that are still untapped
2. Research Methodology
3. Market Overview
3.2 Markets Covered
3.3 Market Demand till 2022
3.4 Recent Trends and Opportunities
3.5 Government Policies and Regulations
4. Market Dynamics
4.4 Big Data in Oil & Gas Exploration and Production (E&P) Value Chain Analysis
4.5 Porters Five Force Analysis
4.5.1 Bargaining Power of Supplier
4.5.2 Bargaining Power of Consumers
4.5.3 Threat of New Entrants
4.5.4 Threat of Substitute Products and Services
4.5.5 Degree of Competition
5. Big Data Technologies Classification in Oil & Gas Exploration and Production (E&P) Market
5.1.1 Computational Devices
5.1.2 Storage Devices
5.1.3 Networking Devices
5.2.1 Implementation Tools
220.127.116.11 Enterprise Control Language (ECL)
18.104.22.168 Apache PIG
22.214.171.124 Mongo DB
126.96.36.199 Neo 4j
188.8.131.52 Apache Cassandra
5.2.3 Software Framework
184.108.40.206 Microsoft Upstream Reference Architecture (MURA)
220.127.116.11 Apache Hadoop
18.104.22.168 High Performance Computing Cluster (HPCC)
6. Big Data in Oil & Gas Exploration and Production (E&P) Market Analysis, by Geography
6.1 North America
6.4 South and Central America
6.6 Middle East
7. Key Company Analysis
8. Competitive Landscape
8.1 Mergers & Acquisitions
8.2 Joint Ventures, Collaborations and Agreements
8.3 Market Share Analysis
9.1 Contact Us