How Big Data Analytics is Used in Oil and Gas Refineries
Big data analytics is transforming the oil and gas refinery industry. Oil and gas refineries generate large amounts of data that include equipment insights, maintenance reports, performance measurements, and more. Those monumental volumes of data must be processed and analyzed in order to deliver value. While refineries have been using organizational and analytical tools for a very long time, big data oil and gas offers innovative solutions that can make the industry more efficient and profitable. In light of volatile changes in supply and demand, oil and gas big data analytics can help companies improve their operations and sustain a competitive advantage. For refineries, big data analytics can enhance and improve the process control systems, manufacturing processes, emergency shutdown systems, equipment interfaces, laboratory information system, online analyzers, asset management systems, and more.
Benefits of Adopting Big Data Analytics in Oil and Gas Refineries
There are many benefits of adopting big data analytics in the oil and gas industry. An oil refinery driven by technology can see benefits such as enhanced integration, cost savings, risk reduction, operational efficiency increases, and price optimization. Oil and gas enterprises can employ big data predictive analytics to reduce downtimes and maintenance costs of the refining equipment, thus improving asset management. The performance of the equipment is analyzed by comparing its historical and current operating data.
Enhanced Integration
Oil refineries typically have several distinct applications that each have their own databases in the form of flat files or relational databases. Through big data analytics, the disparate systems and applications can be integrated into a metadata structure so that a user only needs to look at a single platform to gain system-wide insights.
Cost Savings
Adopting big data analytics allows oil and gas refineries to manage the extreme volumes of data in a cost-effective manner. Using traditional methods of layered architectural systems can be a laborious and expensive way to collect, process, analyze, and store the massive amounts of information involved in oil and gas refineries. Relying on the refinery historian to single-handedly manage the mountains of data is an expensive endeavor with a limited cap on productivity. Big data oil and gas activates real-time analysis technologies that are efficient, cut costs, and expand the opportunities for profit.
Risk Reduction
Adopting big data analytics allows oil and gas refineries to instantaneously tap into vast amounts of data critical to operations. The innovations of data science enable refineries to conduct reliability analysis and gather critical insights about equipment performance, environmental conditions, supply chain logistics, and more. To maximize the quality and quantity of insights, big data can be used to analyze hazards and risks and oversee regulatory compliance standards. The ease of access to information increases the accuracy of tactical and strategic decisions to ultimately reduce risk.
Operational Efficiency Increases
Oil refining is a continuous process that requires machines to perform for long hours in extreme conditions. Big data analytics can be used to monitor the machines and ensure proper and efficient performance. Machines can be easily equipped with smart sensors that collect performance metrics that describe the reliability of particular pumps, the frequency of maintenance, conditions that prompt failure, lifespan, and more. The data can be compared to aggregated measurements. These insights can facilitate optimal part replacement so that both downtime and risk are minimized. Additionally, big data insights can be used to improve the effectiveness of maintenance procedures. All of these strategies increase operational efficiencies and improve accuracy.
Price Optimization
In the oil and gas refining industry, pricing is volatile and dynamic. Supply and demand fluctuates greatly for both products and crudes. In the wholesale and retail markets, price optimization can be a challenge for oil refineries. Big data analytical tools can streamline the pricing process and help refineries achieve competitive advantage as they acquire crude oil and move products into distribution.
Considerations in Using Big Data Analytics in Oil and Gas Refineries
Big data is a popular and powerful tool for many industries, and with special considerations, the oil and gas refining industry can certainly benefit from optimized data applications. Oil and gas refineries have been utilizing data and analytics in some form, to apply the benefits of big data, the companies need to understand how these innovations can complement and evolve existing architectures. By integrating data systems, boosting operational efficiencies, mitigating risk, and optimizing pricing, oil and gas refineries can fuel improvements that maximize revenue.
Get Advice from Analytical Experts at TechStar
Thankfully for oil and gas companies, TechStar is the one-stop-shop for quality instrumentation, analytical devices, training, and application solutions. For over 20 years, TechStar has been a trusted partner. Their signature consultative approach, unparalleled dedication to customer service, state of the art training programs and facilities, and expert innovations are highly sought after by companies worldwide. If you need advice for implementing big data analytics in your oil and gas refinery, TechStar is here for you. To learn more, contact the TechStar analytical expert team today!