Executive Viewpoint

Vol. 233 No. 6

“Big data” needed more than ever

The upstream industry has opened up more new opportunities in the last five years than at any time in its history. With new unconventional plays, companies are breaking new ground in a host of areas as they drill and produce. Data has always been important to the industry, but with these new plays, data, especially what is now called Big Data, have become even more critical for operators.

What is Big Data? Big Data contains four key components:

• Volume. Chevron’s Jay Pryor said at CERA Week, “Chevron manages as much data as Google.” At Chevron, a large offshore field will generate over 10 gigabytes of data per day. A large refinery will have 1 terabyte of raw data per day. Chevron is growing at 2 terabytes per day; in 1997, there were only 5 terabytes for the entire company.
• Velocity. A large offshore field will have 5,000 input/output points in half-second intervals. A large refinery can have 30,000 input/output points.
• Variety. Oil and gas companies are grappling with unfamiliar, new data types, such as microseismic data, complicated by a lack of integration between semi-structured and unstructured data, such as drilling approvals, contracts and regulatory approvals.
• Value. Get the right data to the right people, at the right time.

Industry’s Big Data challenge. Companies need to reduce lag time between data capture and analysis, and between data analysis and implementation of resulting decisions. They also need to analyze massive amounts of data in real time.

To be proactive, operators need to eliminate the impact of disconnected, manual systems that prevent information from being used to execute decisions. They require systems that capture real-time operational data, analyze the data to make “right-time” decisions and execute these decisions seamlessly. And, this framework must be implemented across a company’s reservoir characterization, drilling and production divisions.

Industry’s Big Data vision. The vision for operators is to implement a solution to analyze massive amounts of real time data, and to make intelligent recommendations based on what they know about the asset. Deploying it at a low, total ownership cost, and using industry standards to promote internal and external collaboration, is also important.

Employing this solution enables companies to quickly react to drilling, production or other operational data. Analysis is further enhanced by leveraging data stored in the enterprise data warehouse that contains static and real-time data across existing and historical wells, as well as enterprise information, such as financial data. These data will provide context that enables the asset team to generate proactive operational recommendations. The drilling or production data coming in, and the analysis results, can then be uploaded into the data warehouse to continuously enrich that data’s value. This provides the foundation for a continuous improvement loop.

Furthermore, the enterprise data warehouse should contain its own analysis capabilities, which the asset team can leverage to drive tactical and strategic decisions. The familiar, master, datastore types—such as seismic data, logs, well tests, PVT analysis and more—will always be used in drilling and production surveillance workflows. However, being able to analyze a multi-well archive of real-time data in the same environment, using the same analysis tools, will allow new types of analysis on a longer timeframe.

Achieving Big Data excellence. To meet the big data challenge, an operator’s IT department will need:

• A scalable infrastructure. An operator must be able to store large volumes of high-density data in both the depth and time domains, and create a base platform to allow high-end analytics and provide real-time advice during planning and execution of a well. 
• The ability to integrate information flow from field to central functions. Upstream companies need to leverage leading standards: the Professional Petroleum Data Management (PPDM) standards, Energistics Wellsite Information Transfer Standard Markup Language (WITSML) and Production Markup Language (PRODM). Aligning all of this information will facilitate communication within the enterprise and across multiple enterprises. 
• Close the gap in planning capabilities. “Triangulation” of CAPEX / OPEX operational and production data is extremely difficult. A change in one planning cycle component drives significant misalignment in other components, as no automatic adjustments are enabled. Upstream companies need to align to meet the requirements of ever-changing operations. With tools that provide deeper access and insight into operational planning, financial decisions become smarter.

High-performance data management (HPDM). To achieve Big Data excellence and close the gap between the vast amounts of data available and the ability to turn these data into meaningful information, companies are adopting “high-performance data management” solutions. An HPDM solution leverages real-time asset information from multiple sources, in conjunction with sophisticated analytical tools and risk management techniques, to continuously optimize oil field performance. It can help companies to optimize reservoir characterization, drilling and production operations by delivering a Big Data solution that improves their ability to capture massive amounts of data, provide insights through data analysis, and make better decisions.