Improving Oil and Gas Operations with Big Data and Analytics

Big Data Solutions Executive

Big data presents important opportunities for enhancing the efficiency, safety, productivity and cost-effectiveness of oil and gas operations. Yet it comes with an array of operational technology challenges that often impede the use of big data for operational gains. For example, companies need ways to cleanse and verify data generated by sensors on equipment and in wells, as erroneous data can lead to poor conclusions during surveillance and impair decisions based on models.

Analysis of streaming data also plays a key role in addressing the challenges of advanced condition-based monitoring and maintenance. Sensor data from equipment and wells is critical for avoiding the downtime, costs and safety issues caused by equipment failures and the subsidence that often follows water-flooding or steam-injection processes. However, many organizations today use only a fraction of available data because they lack tools to effectively handle its volume and velocity.

The IBM big data platform can help by enhancing the veracity of data and the analytics based on SCADA and PLC data. Because the IBM big data platform does not require data storage, organizations can use it to cleanse data before it enters historians and control systems—opening up a larger amount of their big data for analysis while generating faster results. As a result, organizations gain insights to make real-time decisions about equipment and conditions that help improve the availability and utilization of assets, reduce downtime, increase production, reduce nonproductive drilling time and improve safety.


Analysis of streaming data enables organizations to refine the complex models used for drilling and for production. Typically, organizations run detailed physics-based models offline because they lack IT solutions that can apply large data volumes of streaming data to these sophisticated models. Consequently, model refinement is slow because it might take days or weeks to prepare in-and-out data, generate the results and tune the model.

With real-time adaptive analytics (RTAA) provided by the IBM big data platform, organizations can score streaming data (both structured and unstructured) against physics-based models in the field, in real time. By continually refining and updating models while monitoring processes, organizations can optimize drilling and production operations and improve productivity. The RTAA solution pattern can be used for a wide variety of subject areas including drilling optimization, production optimization, advanced condition monitoring and micro-seismic interpretation for unconventional resources.

The IBM big data platform offers a comprehensive array of capabilities for addressing the tremendous volume, variety, velocity and veracity of big data. With IBM solutions, oil and gas companies can analyze data streaming in from sensors and use insights to refine models, prevent and address problems and boost production. They can optimize operations for specific business goals. And they can mine a wide variety of data sources to enhance competitive decision making. The IBM big data platform helps organizations build a foundation that supports a digital oilfield designed to enhance efficiency, improve safety and maximize business performance.

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