Like any other major industry, the oil and gas (O&G) sector is embracing initiatives to help ease its way through the rapid digital transformation that is defining the 21st century. One challenge currently being faced by key industry players is big data. How can the O&G giants analyse the vast amount of data in their business systems? And how can they use information-led solutions to deal with market fluctuations based on this data?
Simply put, big data is a compilation of data gathered from both traditional and digital sources from within and outside an organization. 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 must be sifted through and analysed before any meaningful action can take place.
Oil companies have taken essential steps, including downsizing, to mitigate the impact of falling prices. Globally, projects worth around $200 billion were cancelled in early 2016 due to the oil price slump—big data can play a fundamental role in understanding the impact of this.
When faced with information about price fluctuations, the rigorous analysis of this complex data can help companies arrive at better decisions and implement the correct strategies to respond to the effects of market fluctuations.
Introspection and a thorough review of operational inefficiencies are a must. Based on data analysis, operators may need to reduce their capital expenditure, look at alternative development solutions, re-tender projects 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 O&G businesses to streamline their operations.
By using big data analysis to calculate what efficiencies need to be made, businesses can optimize production and reduce operational costs by the necessary levels, to survive the tide of low oil prices.
Oil companies are turning to data tools such as sensor networks, algorithms, mobile technology and computing. They can then use analytics to fully understand labor rates, competition and market trends, which is 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, optimize rig utilization, and improve recovery factors.
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. Intelligence provided by this aggregate information could mean the difference between profit and loss.
Vinodkumar Raghothamarao is the Director for Consulting, Energy Wide Perspectives & Strategy, IHS Markit EMEA.