Year: 2025
Type: article
Abstract: ABSTRACT Inadequate borehole cleaning is the primary cause of over 60% of downhole accidents in extended‐reach wells. Since the 1970s, researchers have been committed to experimental and theoretical studies on cuttings transport in extended‐reach wellbores, aiming to provide reliable experimental data and theoretical frameworks for the accurate prediction and diagnosis of borehole cleaning conditions. This paper systematically reviews the advancements in cuttings transport research, focusing on experimental setups, key influencing factors, and borehole cleaning evaluation methods. Despite extensive studies, existing experimental flow loops have limitations in replicating field conditions, and traditional predictive models struggle to capture the nonlinear interactions between drilling parameters. The review highlights the need for large‐scale experimental systems (311 mm diameter) to improve measurement accuracy and visualization of cuttings transport. Additionally, artificial neural networks offer a promising approach to enhance prediction accuracy by addressing the complex relationships between engineering factors and borehole cleaning efficiency. These insights provide a foundation for optimizing drilling operations and improving wellbore stability in extended‐reach wells.
Source: Energy Science & Engineering
DOI: 10.1002/ese3.70133
Authors: Song Xuncheng, Shi Jiaming, Shi Yucai, Wang Wei
Institution: China University of Petroleum, East China
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,780
OpenAlex ID: W4410416619