data analytics

For organizations that do it well, data management provides a competitive edge in an increasingly digital oil field. But teams all too often are so busy managing all the moving parts of data management that they take their eye off of “the prize”—the payoff after you have put everything into place to sustain successful data management.

This article presents a new data-driven analysis to locate low-frequency seismic sources, referred to as near-infrasound or infrasound sources. Combining these infrasound signals with microseismicity signals allows for better characterization and monitoring of the stimulated reservoir volume.

The collaborative virtual asset and data management suite is designed to meet the needs of the offshore renewable energy market and oil and gas subsea asset owners.

As data sets collected in the field have grown exponentially, data management challenges have both evolved and compounded. This article addresses these pain points and presents strategies and solutions that should be implemented to ensure data compliance and entitlement and promote ease of accessibility, both internally and externally.

Whether buying or selling, quality, non-production data can help operators achieve improved margins and less downtime, unlocking the true potential of their wells.

This paper discusses how methane detection from oil and gas infrastructure using remote sensing technologies enables operators to quantify and minimize the emissions while gaining insight and an understanding of their operations through data analytics.

The company revealed programs for managing production and industrial asset performance. It also announced a collaboration aimed at enhancing rig visualization.

SPE Data Science and Engineering Analytics Technical Director Silviu Livescu and SPE Reservoir Technical Director Rodolfo Camacho address some of the challenges in the application of data analytics, artificial intelligence, and machine learning to several reservoir engineering problems.

Vision analytics is being used to extract insight information from video, with data inferred from existing cameras used to create a monitoring dashboard where supervisors can receive alerts at the worksite level or drill down to specific events.

The University of Texas at Austin will be home to a multidisciplinary research and education initiative, the Energy Emissions Modeling and Data Lab, which aims to address the growing need for accurate, timely, and clear accounting of greenhouse-gas emissions across global oil and natural gas supply chains.