The recent Paris Agreement has created an unprecedented opportunity for countries worldwide to make real changes in the hopes of keeping global temperatures less than two degrees celcius above pre-industrial times.
We’re in the very early stages of this shift towards a low-carbon future.
But even as we face this transition, the oil and gas industry is still alive and well, and there is pressure on big oil to improve operational performance and efficiency, and maximize profitability.
A big step towards max efficiency in oil and gas production has been the integration of big data solutions to provide a consolidated view of organization-wide information.
Big data in oil and gas
The primary activities of any oil and gas company—activities like exploration, drilling, production, and maintenance—involve the generation of a large amount of data.
Weather data, seismic data, environmental sensors, production utilization, storage capabilities, cloud-based applications, location data, and transport and inventory data are just a few sources that need to be monitored and analyzed, and traditional data analysis techniques aren’t cutting it.
This is creating heightened demand for big data solutions and services in the oil and gas sector. The market for these solutions is expected to grow by $3.99 billion from 2015-2020, to reach a total value of $5.41 billion.
Big data initiatives in oil and gas sector
Source: Technavio, 2015
Exploration
Big data analytics is applied to a large amount of geological and operational data to identify any trace seismic signatures that might have been overlooked. The collaboration of data analytics could help reduce lag time, improve drilling parameters, and reduce technical risks.
Scientists are using pattern-based analysis of historical data, such as drilling and production data, in areas where new surveys are not possible due to environmental regulations.
Development
Big data analytics applied to news feeds, geospatial data, and BI reports could generate new development and competitive intelligence prospects.
Drilling
Analytics can help detect any abnormalities in drilling and could save millions in labor and equipment costs.
Production operations
Data analytics can be be applied to seismic, drilling, and production data to help oil and gas companies enhance their oil recovery, and improve their decision-making.
Maintenance
If applied to pressure, volume, and temperature data, big data generates results that can be used to prevent equipment failure and predict any potential failure of critical assets. It is also being used to maintain upstream operations in remote locations.
Enterprise
One of the major challenges faced by the oil and gas sector is the lack of skilled labor.
Big data can help oil and gas companies with knowledge management. For example, it can help these companies use social business for recruitment purposes. Also, enterprises can anticipate any security breaches by accessing data from various sources, and use these results to improve enterprise infrastructure.
Some big data projects currently being carried out in the oil and gas industry include:
- Seismic data processing by Chevron through the use of Hadoop and IBM Big Insights solutions
- Generation of seismic sensor data by Shell through the use of Amazon Virtual Private Cloud
- Seismic data project involving a seismic data server and a drilling data server carried out by Point Cross through the use of Hadoop and NoSQL
- Data acquisition project by the University of Stavanger through the use of Hadoop
- Surface sensor project by Royal Dutch Shell carried out using solutions from HP
