Drilling

Traditionally, the drilling industry has relied on high-fidelity thermal simulators to predict downhole temperature for different operational scenarios. Though accurate, these models are too slow for real-time applications. To overcome this limitation, a deep-learning solution is proposed that enables fast, accurate prediction of downhole temperatures under a wide ran…

The service giant shares how its new technology can sense rock properties 50 ft ahead of the bit in horizontal wells.

This paper describes the development of a method of predicting drillstring-friction coefficient during tripping operations that can be used for early warning of stuck pipe.

This paper proposes a time-series analysis approach to build a reliable, easy-to-use tool to automatically detect stuck pipe accurately and early.

This study aims to thoroughly assess the influence of various completions, fracturing stimulation, and intrinsic reservoir properties affecting the productivity of 10 major unconventional plays while uncovering insights and trends unique to each play.

This paper investigates condensate-banking effects on well performance by conducting field-modeling studies on Delaware Basin deep Wolfcamp condensate producers using compositional simulation models with hydraulic fractures.

This paper presents a novel methodology that merges principles of physics, data science, and uncertainty modeling to offer more-resilient and -precise solutions for managing real-time pipe-sticking occurrences

The agreement focuses on improving operational efficiency and consistency through advanced digital tools and real-time data integration.

An innovative approach uses a random-forest-based framework to link logging-while-drilling and multifrequencey seismic data to enable dynamic updates to lithology parameter predictions, enhancing efficiency and robustness of geosteering applications.

Oil and gas companies drilled 75 “high-impact” wells in 2024, representing 5.2 billion BOE.