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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Prediction of the rate of penetration in offshore large-scale cluster extended reach wells drilling based on machine learning and big-data techniques
Xuyue Chen, Chengkai Weng, Xu Du, et al.
Ocean Engineering (2023) Vol. 285, pp. 115404-115404
Closed Access | Times Cited: 17

Showing 17 citing articles:

Prediction of drilling plug operation parameters based on incremental learning and CNN-LSTM
Shaohu Liu, Wu Yuandeng, Rui Huang
Geoenergy Science and Engineering (2024) Vol. 234, pp. 212631-212631
Closed Access | Times Cited: 11
Research on a drilling rate of penetration prediction model based on the improved chaos whale optimization and back propagation algorithm
Kanhua Su, Wenhao Da, Meng Li, et al.
Geoenergy Science and Engineering (2024) Vol. 240, pp. 213017-213017
Closed Access | Times Cited: 7
A comparative analysis of hybrid RF models for efficient lithology prediction in hard rock tunneling using TBM working parameters
Jian Zhou, Peixi Yang, Weixun Yong, et al.
Acta Geophysica (2024) Vol. 72, Iss. 3, pp. 1847-1866
Closed Access | Times Cited: 6
The stress field simulation of a novel M-type convex stepped bottomhole and the rate of penetration enhancement mechanism of a new type of central-grooved PDC bit for offshore deep & ultradeep well drilling
Xuyue Chen, Qiqi Yang, Jin Yang, et al.
Ocean Engineering (2024) Vol. 293, pp. 116706-116706
Closed Access | Times Cited: 5
Enhancing rate of penetration prediction in drilling operations: A data stream framework approach
João Roberto Bertini, Bahram Lavi
Engineering Applications of Artificial Intelligence (2025) Vol. 143, pp. 110034-110034
Closed Access
Optimization of Drilling Rate Based on Genetic Algorithms and Machine Learning Models
Fang Shi, Hualin Liao, Shuaishuai Wang, et al.
Geoenergy Science and Engineering (2025), pp. 213747-213747
Closed Access
A real-time prediction method for rate of penetration sequence in offshore deep wells drilling based on attention mechanism-enhanced BiLSTM model
Qi Yuan, Miao He, Zhichao Chen, et al.
Ocean Engineering (2025) Vol. 325, pp. 120820-120820
Closed Access
A new intelligent optimization method for drilling parameters of extended reach wells based on mechanical specific energy and machine learning
Xuyue Chen, Rong Wang, Jin Yang, et al.
Petroleum Research (2025)
Open Access
Research on rock breaking mechanism of rotary-percussion drilling in marine hard rock strata and the influence of engineering and tool parameters on ROP
Yan Xi, Junhao Xing, Jiwei Li, et al.
Geoenergy Science and Engineering (2025), pp. 213781-213781
Closed Access
An Intelligent Method for Real-Time Surface Monitoring of Rock Drillability at the Well Bottom Based on Logging and Drilling Data Fusion
Dexin Ma, Hongbo Yang, Zhilin Yang, et al.
Processes (2025) Vol. 13, Iss. 3, pp. 668-668
Open Access
O&G, Geothermal Systems, and Natural Hydrogen Well Drilling: Market Analysis and Review
Andreas Nascimento, Diunay Zuliani Mantegazini, Mauro Hugo Mathias, et al.
Energies (2025) Vol. 18, Iss. 7, pp. 1608-1608
Open Access
A real-time drilling parameters optimization method for offshore large-scale cluster extended reach drilling based on intelligent optimization algorithm and machine learning
Xuyue Chen, Xu Du, Chengkai Weng, et al.
Ocean Engineering (2023) Vol. 291, pp. 116375-116375
Open Access | Times Cited: 8
The bottomhole stress field analysis and the rate of penetration enhancement mechanism of a new type of central-grooved single-cone/multi-blade hybrid bit for deep well drilling
Xuyue Chen, Qiqi Yang, Naitong Yang, et al.
Geoenergy Science and Engineering (2023) Vol. 233, pp. 212485-212485
Closed Access | Times Cited: 5
A highly accurate and robust prediction framework for drilling rate of penetration based on machine learning ensemble algorithm
Yuxiang Yang, Xiao Cen, Haocheng Ni, et al.
Geoenergy Science and Engineering (2024), pp. 213423-213423
Closed Access | Times Cited: 1
Enhancing Rate of Penetration Prediction in Drilling Operations: A Data Stream Framework Approach
João Roberto Bertini, Bahram Lavi
(2024)
Closed Access
Prediction of the ROP based on GA-LightGBM and drilling data
Shuai Shuai Wang, Jun Yan, Hao Geng
Geosystem Engineering (2024), pp. 1-19
Closed Access
A Physically-Constrained Ensemble Learning Rate of Penetration Prediction Model based on Multi-Source Data Fusion
Yongdong Fan, Jin Yan, Huiwen Pang, et al.
Applied Intelligence (2024) Vol. 55, Iss. 3
Closed Access
The Stress Field Analysis of a Novel M-Type Convex Stepped Bottomhole and a New Type of Central-Grooved Pdc Bit for Offshore Deep & Ultradeep Well Drilling
Xuyue Chen
(2023)
Closed Access
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