Guest Editorial: Higher Capability, Lower Costs With Cloud Subsurface Data Management
- Joe Neely (Wipro Limited) | Vasuki Upadhya (Wipro Limited)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- July 2018
- Document Type
- Journal Paper
- 14 - 15
- 2018. Copyright is retained by the author. This document is distributed by SPE with the permission of the author. Contact the author for permission to use material from this document.
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Lower oil prices, lack of experienced personnel, and uncertainty about long-term global oil and gas demand are driving petroleum companies to seek new ways to improve operational capability and lower costs. Cloud subsurface data management has the potential to allow standardized data acquisition, improve data integration and quality, and catalyze data analytics—all at a lower cost than traditional methodologies.
Many challenges are involved in acquiring, analyzing, and managing subsurface data. Why is subsurface data so different from other domains? Subsurface comprises many complicated data types, including well logs, core analyses, geologic interpretations, and more.
Each data type is complex and requires an experienced subject matter expert (SME) to deal with data acquisition, formatting, and managing. In addition, the subsurface data must be aggregated into a business context to be useful to the daily operational business. IT and domain SMEs must collaborate to ensure that data are always correct, integrated, and accessible. To be effective, a subsurface data manager must have a strong blend of domain and technical capabilities.
The minimum level of qualification for a position in data management requires a degree in a relevant discipline such as geoscience, engineering, or information technology. Candidates must capably handle multiple operating systems such as Windows and Linux, and should understand company-specific software at a base level.
The technical requirements of subsurface data management are significant. Candidates should know how to script in AWK, sed, Perl, or Python, and additional scripting languages can’t hurt. Lastly, candidates must under-stand management from both a technical perspective—in understanding quality control and juggling multiple data bases—and from a people perspective, in possessing excellent communication skills and handling team personalities. With so much required of those in subsurface data management, the result is a complicated landscape that changes from one business unit to another and evolves through time.
With the advent of data analytics, the subsurface data manager’s responsibilities have increased. Analytics cannot thrive unless there is good data on which to act. The broadening subsurface workspace, coupled with the large legacy application set and increasing amounts of information, creates a critical problem. Continuing with the same issues and proprietary software is not the answer: A new way of thinking is required.
Why Cloud Platforms Work
Utilizing a cloud platform solution for subsurface data can lower infrastructure and support costs while simultaneously providing a platform for all structured and unstructured data along with a col-lection of best-in-class applications for managing and acting on the data to create business value.
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