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Hull fouling is a huge problem and is estimated to account for 9% of the global fleet’s fuel consumption every year. Initial theoretical, laboratory, and land-based tests supported by independent experts have led to promising results showing that ultrasound can prevent biofouling.

The deal follows an asset swap on the same acreage earlier in the year and increases Equinor’s natural gas holdings in the region.

The road to a low-carbon world is paved with more than just shiny new facilities and the promise to deliver impressive CO₂ reductions from the atmosphere. Without the software to site, monitor, and maintain those facilities, the drive for net zero would be stuck in neutral.

We reflect on the legacy and commitment made by a key member of the JPT team who is stepping down from his role of more than a decade and into retirement.

Undergraduate education in petroleum engineering has survived the latest downturn in the industry, and enrollment has started to show an uptick in numbers. However, a different trend is evident in graduate training and academic research: the number of researchers being trained in oil and gas topics is drastically dropping.

This case study outlines a methodology to optimize and control hydraulic fracturing parameters by achieving 100% cluster efficiency and overcoming formation leak-off.

There is no shortage of quantum technology applications in the upstream industry, from supply chain to well placement, making now the time to take it seriously.

Olivier Houzé discusses his views on SPE finances, including a historical perspective, the effects of downturns and the COVID-19 pandemic, ongoing recovery, and future plans.

What we’ve learned about faster drilling in oil and gas applied just as well to geothermal development—until we reached The Geysers.

Technology uptake aimed at optimizing resources, delivering consistency, and augmenting what humans can do.

This paper highlights a new online system for monitoring drilling fluids, enabling intelligent control of drilling-fluid performance.

This paper investigates the use of machine-learning techniques to forecast drilling-fluid gel strength.