With global consumers increasingly demanding more energy, oil and gas industries have little room for overestimations and under-delivery. However, these companies have found themselves facing ever-higher production costs. Fluctuating prices are also a challenge to corporations in the oil and gas markets.
The industries are becoming more dependent on big data to help them analyze production, defaults, and opportunities. Analysts are expecting the big data market in the oil and gas industries to increase at a compound annual growth rate (CAGR) of 30.67% from 2016 through 2020.
Using big data processors, these companies can monitor large amounts of data efficiently and make better decisions regarding business processes, which will result in lower production costs and a reduction in missed profits.
During a study in June and August of 2016, Kimberlite interviewed 50 oil and gas operators regarding unplanned downtime due to maintenance issues. The operators suggested using big data analytics and solutions as a digital approach. These digital prediction solutions will decrease the amount of unplanned downtime, which currently costs offshore oil and gas companies an average of $49 million per year.
These predictions will not only reduce unnecessary costs for oil and gas organizations but also improve performance.
How Big Data Works in the Oil and Gas Industries
Organizations are investing in more hardware options designed to collect data in oil and gas industries as well as hiring employees with analytic backgrounds to run these digital technologies. Companies are purchasing tough and functional industrial computers to analyze operations on rigs and in hazardous areas. This hardware are a large investment, but with big data solutions, companies are looking to maximize profits while reducing production costs in general.
Companies are also retrofitting equipment with sensors to predict when maintenance repairs are due. This equipment reduces the unplanned downtime after a machine stops working and needs to be serviced. By knowing ahead of time of any potential issues, oil and gas operators can prepare appropriately. Currently, only 3-5% of equipment in the oil and gas industries is wirelessly connected.
The retrofitted sensors use wireless technology to transmit logistics issues. Operators need specialized training in the types of sensors used and where to install them on the equipment. Not only will companies continue to hire engineers in petroleum and gas engineering, but more organizations will need engineers with degrees in analytics and logistics. Current employees can receive training through certification programs to improve efficiency using big data solutions.
Although the industry does have some sensors retrofitted to the equipment, many of those do not relay the data that is useful for decision-making in the industry. Companies, like GE, are designing software that can access this amount of information so oil and gas organizations can make informed data-driven decisions. By using data collected in the cloud, these companies will improve productivity and efficiency as well as maintenance.
The Future of Big Data in the Oil and Gas Industries
Oil and gas organizations can reduce their bottom line by predicting and diagnosing technological issues early using big data solutions. Operators can access the data collected by the new software to analyze patterns and make better decisions regarding their processes.
The Kimberlite study showed that operators able to use predictive data-driven software were able to drop their company’s bottom line by $17 million on average with 36 percent less unplanned downtime due to maintenance issues.
Just like with other global markets, the oil and gas industries need to increase their big data analytics and equipment for cost-effectiveness in order to stay competitive in today’s marketplace.