Data Management for Oil & Gas: High Performance Computing

Data Management and Technology

The oil and gas industry is dealing with data management on a scale never seen before. One approach to quickly get at relevant data is with High Performance Computing (HPC).

HPC is dedicated to the analysis and display of very large amounts of data that needs to be processed rapidly for best use.

One application is the analysis of technical plays with complex folding. In order to understand the subsurface, three dimensional high definition images are required.

The effective use of HPC in unconventional oil and gas extraction is helping drive the frenetic pace of investment, growth and development that will provide international fuel reserves for the next 50 years. Oil and gas software supported by data intelligence drives productive unconventional operations.

Evolving Data Management Needs

As far back as 2008, the Microsoft High-Performance Computing Oil and Gas Industry Survey conducted by the Oil & Gas Journal Online Research Center indicated that many industry geoscientists and engineers have access to the computing performance levels they require.

However, computing needs are growing more complex, so significant room for improvement exists. NumerousOil and Gas: High Performance Computingrespondents believe that making HPC available to more people industry wide can increase production, enhance decision-making, reduce delays in drilling, and reduce the overall risk of oil and gas projects.

Chesapeake is the largest leasehold owner of Marcellus Shale Play, which reaches from Southern NY to West Virginia. They employ HPC  in their shales and tight sands operations.

3-D imaging enables technical staff to detect fine-scale fracturing and directional dependency characteristics. Seismic data provides a structural road map that helps identify dip changes, small faults and natural fracture orientation.

High Performance Computing in the Real World

Chesapeake routinely performs inversions of pre-stack and post-stack data management. Datasets for imaging and inversion support models that represent complex earth structures and physical parameters, where true inversion results are known.

Reservoir maps require constant updating. Advanced pre-stack 3-D techniques are used to extract detailed rock properties that aid in discriminating good rock from bad rock at Marcellus.

Focusing on pre-stack data management has significantly increased computational requirements. Depending on the acquisition method, collecting multicomponent 3-D data can increase data size by orders of magnitude.

Advanced algorithms provide results in a matter of days, making it possible to realistically deal with a lease schedule.

Clustered super-computing systems are becoming well priced and scalable. HPC options are not only realistic, but a requirement for independents who want to bring advanced processing capabilities in house.

Check out this blog post on how oil and gas companies are using data management to improve processes here…