Big data aids exploration firms to predict oilfield productivity, study finds

frost2Oil and gas firms are increasingly adopting big data solutions that can collect, integrate, analyse and visualise oilfield data to predict its productivity, according to market research firm Frost & Sullivan

The new report Emerging Upstarts and Market Transitions in the Global Digital Oilfield Data Management Market added that data analytics is the fastest growing segment as end users look to derive additional value from connected devices.

Rahul Vijayaraghavan, senior research analyst at Frost & Sullivan, said, “Challenges such as increased data traffic and data types from diverse assets onsite, changing reservoir dynamics that dampen recovery rates, equipment failures, production inefficiencies and high maintenance, repair and operational costs have created a push towards big data and analytics in oil and gas exploration activities.

“Post data capturing and sorting, end users can use application specific analytical platforms to extract actionable insights and validate key performance metrics, a growing requirement in today’s competitive and price sensitive environment.”

According to Vijayaraghavan, the shift from diagnostic to predictive analytics and more recently to prescriptive analytics has further resulted in an influx of niche solution providers offering state-of-the-art analytical platforms.

“High costs incurred from operational downtimes and the extra manpower required for repairs will continue pushing end users towards adoption of best-in-class predictive and preventive analytical platforms. For instance, predicting failure of electric submersible pumps deployed in oilwells and subject to high temperatures can reduce maintenance costs significantly,” noted the analyst.

While traditional methods employ periodic maintenance inspections, current analytical platforms collate vital data and use statistical models to predict the likelihood of failure more quickly.

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