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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:

When Petrophysics Meets Big Data: What can Machine Do?
Chicheng Xu, Siddharth Misra, Poorna Srinivasan, et al.
SPE Middle East Oil and Gas Show and Conference (2019)
Closed Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

Machine Learning in Oil and Gas Exploration: A Review
Ahmad Tijjani Lawal, Yingjie Yang, Hongmei He, et al.
IEEE Access (2024) Vol. 12, pp. 19035-19058
Open Access | Times Cited: 15
Facies Identification Based on Multikernel Relevance Vector Machine
Xingye Liu, Xiaohong Chen, Jingye Li, et al.
IEEE Transactions on Geoscience and Remote Sensing (2020) Vol. 58, Iss. 10, pp. 7269-7282
Closed Access | Times Cited: 76
Neural network application to petrophysical and lithofacies analysis based on multi-scale data: An integrated study using conventional well log, core and borehole image data
Amer A. Shehata, Osama A. Osman, Bassem S. Nabawy
Journal of Natural Gas Science and Engineering (2021) Vol. 93, pp. 104015-104015
Closed Access | Times Cited: 58
Lithology identification from well-log curves via neural networks with additional geologic constraint
Chunbi Jiang, Dongxiao Zhang, Shifeng Chen
Geophysics (2021) Vol. 86, Iss. 5, pp. IM85-IM100
Closed Access | Times Cited: 55
Machine learning for locating organic matter and pores in scanning electron microscopy images of organic-rich shales
Yaokun Wu, Siddharth Misra, Carl Sondergeld, et al.
Fuel (2019) Vol. 253, pp. 662-676
Closed Access | Times Cited: 59
Prediction of Reservoir Quality from Log-Core and Seismic Inversion Analysis with an Artificial Neural Network: A Case Study from the Sawan Gas Field, Pakistan
Qiang Zhang, Qamar Yasin, Naser Golsanami, et al.
Energies (2020) Vol. 13, Iss. 2, pp. 486-486
Open Access | Times Cited: 50
Application of ML & AI to model petrophysical and geomechanical properties of shale reservoirs – A systematic literature review
Fahad I. Syed, Abdulla AlShamsi, Amirmasoud Kalantari Dahaghi, et al.
Petroleum (2020) Vol. 8, Iss. 2, pp. 158-166
Open Access | Times Cited: 44
Machine learning workflow to predict multi-target subsurface signals for the exploration of hydrocarbon and water
Oghenekaro Osogba, Siddharth Misra, Chicheng Xu
Fuel (2020) Vol. 278, pp. 118357-118357
Closed Access | Times Cited: 38
Hybrid deep neural networks for reservoir production prediction
Zhenyu Yuan, Handong Huang, Yuxin Jiang, et al.
Journal of Petroleum Science and Engineering (2020) Vol. 197, pp. 108111-108111
Closed Access | Times Cited: 34
Real-Time Hydraulic Fracturing Pressure Prediction with Machine Learning
Yuxing Ben, Michael Perrotte, Mohammadmehdi Ezzatabadipour, et al.
SPE Hydraulic Fracturing Technology Conference and Exhibition (2020)
Closed Access | Times Cited: 30
Reservoir Prediction Based on Closed-Loop CNN and Virtual Well-Logging Labels
Cao Song, Wenkai Lu, Yuqing Wang, et al.
IEEE Transactions on Geoscience and Remote Sensing (2022) Vol. 60, pp. 1-12
Closed Access | Times Cited: 18
A borehole clustering based method for lithological identification using logging data
Hui Liu, Xialin Zhang, Zhanglin Li, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 4, pp. 2801-2817
Closed Access | Times Cited: 3
Fault and fracture network characterization using seismic data: a study based on neural network models assessment
Qamar Yasin, Mariusz Majdański, Ghulam Mohyuddin Sohail, et al.
Geomechanics and Geophysics for Geo-Energy and Geo-Resources (2022) Vol. 8, Iss. 2
Closed Access | Times Cited: 15
A Novel Method of Deep Learning for Shear Velocity Prediction in a Tight Sandstone Reservoir
Ren Jiang, Zhifeng Ji, Wuling Mo, et al.
Energies (2022) Vol. 15, Iss. 19, pp. 7016-7016
Open Access | Times Cited: 15
Hierarchical automated machine learning (AutoML) for advanced unconventional reservoir characterization
Yousef Ahmad Mubarak, Ardiansyah Koeshidayatullah
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 7
Deep-Learning-Based Vuggy Facies Identification from Borehole Images
Jiajun Jiang, Rui Xu, Scott C. James, et al.
SPE Reservoir Evaluation & Engineering (2020) Vol. 24, Iss. 01, pp. 250-261
Closed Access | Times Cited: 19
Diagenetic Facies Classification in the Arbuckle Formation Using Deep Neural Networks
Tianqi Deng, Chicheng Xu, Xiaozheng Lang, et al.
Mathematical Geosciences (2021) Vol. 53, Iss. 7, pp. 1491-1512
Closed Access | Times Cited: 16
Big Data Characteristics (V’s) in Industry
Nagham Saeed, Laden Husamaldin
Iraqi Journal of Industrial Research (2021) Vol. 8, Iss. 1, pp. 1-9
Open Access | Times Cited: 13
Deriving Permeability and Reservoir Rock Typing Supported with Self-Organized Maps SOM and Artificial Neural Networks ANN - Optimal Workflow for Enabling Core-Log Integration
Luigi Saputelli, Rafael Celma, Douglas A. Boyd, et al.
SPE Reservoir Characterisation and Simulation Conference and Exhibition (2019)
Closed Access | Times Cited: 14
Integration of NMR and Conventional Logs for Vuggy Facies Classification in the Arbuckle Formation: A Machine Learning Approach
Rui Xu, Tianqi Deng, Jiajun Jiang, et al.
SPE Reservoir Evaluation & Engineering (2020) Vol. 23, Iss. 03, pp. 917-929
Closed Access | Times Cited: 14
A Comparative Study on Supervised Machine Learning Algorithms for Copper Recovery Quality Prediction in a Leaching Process
Víctor Flores, Claudio Leiva
Sensors (2021) Vol. 21, Iss. 6, pp. 2119-2119
Open Access | Times Cited: 12
Machine learning assisted model based petrographic classification: a case study from Bokaro coal field
Abir Banerjee, Bappa Mukherjee, Kalachand Sain
Acta Geodaetica et Geophysica (2024)
Closed Access | Times Cited: 1
Transfer learning for well logging formation evaluation using similarity weights
Bin-Sen Xu, Feng Zhou, Jun Zhou, et al.
Artificial Intelligence in Geosciences (2024), pp. 100091-100091
Open Access | Times Cited: 1
A Data-Driven Approach to Forecasting Production with Applications to Multiple Shale Plays
Hao Xiong, Changjae Kim, Jing Fu
SPE Improved Oil Recovery Conference (2020)
Closed Access | Times Cited: 12
Supervised and Unsupervised Machine Learning Approach in Facies Prediction
Daniel Oluwadara Fadokun, Ishioma Bridget Oshilike, Mike Onyekonwu
SPE Nigeria Annual International Conference and Exhibition (2020)
Closed Access | Times Cited: 10
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