Remote - Spring 2016 - (Page 6)

Feature Article Driving Real-Time Insight in the Oil and Gas Industry Charles Karran, Senior Director, Oil & Gas Industry Strategy Oracle Big Data drives every aspect of the oil and gas industry throughout its lifecycle, through the initial targeting of geographies, land acquisition and leasing, to exploration, production and operations. From seismic and yield analyses to reducing risk and increasing production, big data plays a vital role in producing real operational results. The raw data alone, though, does not provide the answers companies need to guarantee safety and increase profitability. It is necessary to be able to both choose and analyze the appropriate data to accelerate the speed with which decisions are made that affect the business. The true potential for big data, and the key for oil and gas companies to achieving an intelligent enterprise, is in being able to do just that. Increasingly, companies are focused on building increasingly intelligent operations to enable real-time analysis of drilling and production data streams. As they begin, many face challenges, such as disparate data sources and the lack of analytical capabilities within the enterprise. However, new approaches such as high performance data management, are now enabling companies to harness the power of big data to increase the speed to answer. Improving Insights Through Analysis The oil and gas industry has utilized business intelligence (BI) systems for many years. Traditional BI and analytics solutions have enabled companies to consolidate financial and operations data, replace extensive manual reports with dashboards to support all horizontal business processes, provide users with ad hoc reporting capabilities, and create a centralized financial budgeting process with increased expense visibility. While expanding insight into key performance indicators (KPI), these systems have not delivered the real-time, enterprise-wise insight needed by today's producers. As a result, companies have not yet been able to significantly accelerate speed to answer. As has been the case with many other industries, the oil and gas industry needs to improve its ability to capture immense amounts of data, provide insights through analysis of that data, and make better operational, tactical and strategic decisions as a result of those insights. Specifically, operations personnel would be able to use analysis-driven insights to optimize output, improve safety and reduce costs and non-productive time. The Challenges of Data Managing an oil or gas well requires many different disciplines and professionals: geoscientists, engineers, analysts, contractors working together. Their collective goal is to optimize revenue for the company by reducing non-productive time, maintaining output at the well's allowable level, and reducing costs while at the same time enhancing safety. Achieving these objectives efficiently and effectively, however, can be fraught with challenges: 1. 2. 3. Siloed Data Issues: Massive amounts of technical, operational and financial data are stored in separate, disconnected systems, each managed by different stakeholders. As long as the data from these systems is not connected across the enterprise, a 306° view of the operation is not possible. Lack of Expanded Analytical Capabilities: Isolated metrics and KPIs, such as production information, only provide a limited picture of the assets. Additionally, members of the asset team aren't usually data scientists or analysts, and therefore have a limited ability to analyze the data for actionable insights for optimizing drilling and production operations. Execution Challenges: Oil and gas companies are under growing pressure to make more real-time decisions about increasingly complex wells, and to do so with fewer, less experienced personnel. The siloed data issues mentioned earlier mean that stakeholders in the field and at corporate headquarters are often unable to leverage enterprise data to improve the timeliness and quality of well-level decisions. Combined, these issues lead to reactive, rather than proactive, decision-making, as asset team members are unable to effectively collaborate under these conditions. By preventing asset teams from achieving speed to answer for important drilling and production issues in real-time, these issues can impact performance across reservoir characterization and can prove costly in terms of financial performance, drilling and production. 6 www.RemoteMagazine.com http://www.RemoteMagazine.com

Table of Contents for the Digital Edition of Remote - Spring 2016

Editor's Choice
Driving Real-Time Insight in the Oil and Gas Industry
One Network to Rule Them All
Rolls-Royce Power Systems Protection Underground Data Center
Going Beyond Compliance: Using NERC CIP v5 as a Catalyst for a Greater Security Strategy
Different Hardware Platforms, Same HMI Software
Satellite Communications: Extending the Reach of Your Monitoring and Control Footprint
Key Elements to Designing an IoT Network for Remote Monitoring
4G LTE Versus Wi-Fi Versus Bluetooth: What Every Aspiring IoT Entrepreneur Needs to Know
SCADA
Networking
Security
Onsite Power
Industry News

Remote - Spring 2016