Using big data to survive the oil price slump
Understanding and utilising data can help companies in the oil and gas industry get through a difficult period
Like any other major industry, the oil and gas sector is embracing initiatives to help ease its way through the rapid digital transformation that is defining the 21st century landscape.
Harnessing the latest technology helps oil and gas companies to gain strategic insight, which in turn can help them to proactively respond to crucial industry challenges and act with more prudence in their decision-making.
One challenge currently faced by key industry players is big data. How can the oil and gas giants analyse the vast amount of data in their business systems? And how can they deploy information-led technologies to deal with market fluctuations based on this data?
Simply put, big data is a compilation of the data gathered from both traditional (structured data) and digital (unstructured data) sources from within and outside an organisation.
It refers to all the data that resides in a company’s business systems, as well as the plethora of data coming from the web and social networks — sources of information that have to be sifted through and analysed before any meaningful action can take place.
To better understand the fundamental role of big data in the industry, let us take a closer look at the impact of low oil prices, a major issue to recently hit the oil and gas industry.
Sliding oil prices have particularly impacted the GCC region. According to an industry report, the GCC economies are expected to grow by just 3.7% in 2016 — lower than previous years.
Oil companies across the region have taken essential steps, including downsizing, to mitigate the impact of falling prices and globally, projects worth around $200bn were cancelled in early 2015 due to the oil price slump.
When faced with information about price fluctuations, it is the rigorous analysis of this complex data that can help companies make better decisions and implement the correct strategy to respond to the effects of market fluctuations. Introspection and a thorough review of operational inefficiencies are also a must.
Based on data analysis, operators may need to reduce their capital expenditure, look at alternative development tools, re-tender projects in order to cut down costs, and push back investment where possible.
Manpower reduction, lower expenditure on non-critical field maintenance and the adoption of best-in-class supply chain strategies may also help oil and gas businesses to streamline their operations. By using big data analysis to calculate what efficiencies need to be made, businesses can optimise production and reduce operational costs by the necessary levels, in order to survive the tide of low crude oil prices.
To help deploy the above strategies, oil companies are turning to data tools such as sensor networks, algorithms, mobile technology and computing. They can use analytics to fully understand labour rates, competition and market trends, especially important given the volatility in oil prices.
Major players can exploit big data to streamline their operational costs and use it to help them anticipate bit-wear, optimise rig utilisation, and improve recovery factors. The information can also determine how best to simulate a specific oil well, calculate the optimal water injection rate, and predict mechanical equipment failures across an oil field.
With plunging oil prices, large companies are using big data to manage risks, cut costs and increase revenues.
Deploying a robust enterprise resource planning (ERP) system helps the oil and gas giants to collate pertinent, timely information and standardise the processes so that the collected data is consistent. In an industry with so many units dispersed geographically, an enormous number of wells and complex supply chain demands, the standardisation which ERP provides plays an important role.
Additionally, strong ERP technologies for oil and gas firms offer a powerful yet easy way to manage project portfolios.
Using the right software, they can support project governance and financial planning by analysing costs and scheduling the impacts of mitigation scenarios, model risks, and determining the most-likely completion times.
Big data’s role in softening the impact of the oil price slump is just one aspect of how high-volume and high-velocity information assets can help the industry. Sophisticated analytics and forecasting tools can be used to produce data-driven decisions for higher profitability.
After all, the intelligence provided by this massive aggregate of information could mean the difference between profit and loss.