E&P Improves Vision with Analytics

gds-group-drilling-down-the-analytics-revolution-in-oil-and-gas
E&P Improves Vision with Analytics

Powerful applications place heavy demands on infrastructure. Higher return on assets and reduced risk are important rewards available to E&P companies that can successfully leverage advanced analytics to improve decision making and operations. As companies strive to increase production, improve ROI and bolster safety, they are implementing analytics applications that help them better understand what […]

Powerful applications place heavy demands on infrastructure.

Higher return on assets and reduced risk are important rewards available to E&P companies that can successfully leverage advanced analytics to improve decision making and operations.

As companies strive to increase production, improve ROI and bolster safety, they are implementing analytics applications that help them better understand what is happening underground — and inside their business.

Better analysis can yield significant improvements in capital allocation, cash flow predictions, asset valuation, competitiveness and risk management. And it can help improve hydrocarbon yields by several percentage points.

The potential business gains from better forecasting and asset management are considerable, but success is hardly assured, because the technological challenges can be overwhelming. Analytics applications leverage massive datasets measured in petabytes that place huge demands on storage and processing infrastructure. New seismic survey formats such as 3D, 4D and 4C use high resolution capture methods, and ubiquitous machine sensors generate massive streams of data. All this information must be ingested, stored and made available to the applications. For geoscientists and engineers to gain actionable insight, the applications and data must be well supported by storage infrastructure.

Infrastructure Commitment

The deployment of analytics represents a tremendous challenge for IT and leadership. E&P organizations are under constant pressure to marshal resources effectively and run efficient operations, including IT. At the same, they must support exploration and production teams to maximize the company’s competitive edge. To succeed with analytics, organizations must take a hard look at their technology infrastructure and commit to building a solid foundation from the data center up.

In exploration, the potential benefits from data analysis are immense. Exploration teams can conduct seismic surveys that produce detailed images of underground and undersea formations and then leverage powerful data visualization tools to enhance their interpretation of seismic data. By finding hidden signals that older applications could never detect, analytics helps geoscientists determine precise locations of oil and gas reservoirs and optimize field development strategies. When a single deep-water well can cost over $100 million, rapid and accurate analysis is a driver of tremendous business value.

Hydrocarbon production operations also benefit from effective analysis. Operators can leverage sophisticated data from machine sensors to increase production rates and drilling speeds, reduce downtime and make faster, better decisions that improve overall oilfield economics. They can also design wells more effectively, mitigate drilling issues and increase maintenance schedule efficiencies. Completion efficiency is improved through a better understanding of reservoir parameters, and engineers can identify the best wells for optimized workover strategies.

Integrating the Data

To enable these valuable improvements in E&P, IT must create a data management and storage infrastructure that can support immense loads. In exploration, seismic surveys that used to create a few thousand readings now typically create a million readings or more. New techniques such as 3D, 4D and 4C combined with Wide Azimuth and Full Azimuth data acquisition are generating many times more data to store and process than older technologies did.

Standard data center platforms are inadequate for these cutting-edge applications, and IT needs to deploy robust, scalable solutions that can keep complex data readily available to exploration teams. New data must also be merged with older data that might be inaccessible with traditional data management technologies.

Production analysis poses similar, new challenges for IT. Drilling operations in unconventional fields increasingly rely on sensors capturing detailed information, and engineers conduct comparative well-to-well analysis to inform drilling strategies. Datasets are large and must be highly available in real time.

One common impediment to effective use of analytics is a lack of integration in systems and data. E&P companies may be gathering major flows of useful data from seismic surveys and machine sensors and yet be stymied by an inability to integrate it with historical data for comprehensive analysis. New ultra-high 3D seismic surveys may be unwieldy to store for immediate processing, and old data may be siloed away in formats that don’t play well with modern applications.

Powerful analytics rely on datasets that are highly available to users. New storage architectures must scale easily and unify seismic data in one unified file system where it can be extracted readily. Storage solutions must offer high capacity and high density to keep large datasets available for extended periods of time. Architecture solutions such as data lakes are critical in supporting advanced E&P analytics. A data lake holds data in a flat architecture so that it is readily available to applications with robust throughput.

To stay ahead of the innovation curve and compete effectively, E&P companies need to commit to advanced analytics — and the infrastructure that supports it — as an essential driver of business value.

— By John MacKenna, freelance technology and business writer and the former Editor of Oil & Energy.

0 Comments

Leave a Comment

Please Post Your Comments & Reviews

Leave a Reply