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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:

A Novel Preprocessing Scheme to Improve the Prediction of Sand Fraction From Seismic Attributes Using Neural Networks
Soumi Chaki, Aurobinda Routray, William K. Mohanty
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2015) Vol. 8, Iss. 4, pp. 1808-1820
Open Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Application of machine learning and artificial intelligence in oil and gas industry
A. Sircar, Kriti Yadav, Kamakshi Rayavarapu, et al.
Petroleum Research (2021) Vol. 6, Iss. 4, pp. 379-391
Open Access | Times Cited: 346
Semi-supervised learning for acoustic impedance inversion
Motaz Alfarraj, Ghassan AlRegib
(2019)
Open Access | Times Cited: 84
Application of Correlation-based Recurrent Neural Network in Porosity Prediction for Petroleum Exploration
Mustafa Ibrahim Mansoor, Hadeel Mohammed Tuama, Amjad J. Humaidi
Engineering Research Express (2025) Vol. 7, Iss. 1, pp. 015241-015241
Closed Access | Times Cited: 1
Petrophysical-property estimation from seismic data using recurrent neural networks
Motaz Alfarraj, Ghassan AlRegib
(2018), pp. 2141-2146
Open Access | Times Cited: 70
Estimation of acoustic impedance from seismic data using temporal convolutional network
Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
(2019)
Open Access | Times Cited: 63
Well-Log and Seismic Data Integration for Reservoir Characterization: A Signal Processing and Machine-Learning Perspective
Soumi Chaki, Aurobinda Routray, William K. Mohanty
IEEE Signal Processing Magazine (2018) Vol. 35, Iss. 2, pp. 72-81
Closed Access | Times Cited: 59
Identifying channel sand-body from multiple seismic attributes with an improved random forest algorithm
Yile Ao, Hongqi Li, Liping Zhu, et al.
Journal of Petroleum Science and Engineering (2018) Vol. 173, pp. 781-792
Closed Access | Times Cited: 55
Analysis of differencing and decomposition preprocessing methods for wind speed prediction
Neeraj Dhanraj Bokde, Andrés Feijóo, Kishore Kulat
Applied Soft Computing (2018) Vol. 71, pp. 926-938
Closed Access | Times Cited: 52
A probabilistic neural network (PNN) based framework for lithology classification using seismic attributes
Soumi Chaki, Aurobinda Routray, William K. Mohanty
Journal of Applied Geophysics (2022) Vol. 199, pp. 104578-104578
Closed Access | Times Cited: 24
Extreme learning machine for multivariate reservoir characterization
Xingye Liu, Qiang Ge, Xiaohong Chen, et al.
Journal of Petroleum Science and Engineering (2021) Vol. 205, pp. 108869-108869
Closed Access | Times Cited: 30
Investigating the Accuracy of Artificial Neural Network Models in Predicting Surface Roughness in Drilling Processes
Modestus O. Okwu, Omonigho B. Otanocha, B. A. Edward, et al.
Procedia Computer Science (2024) Vol. 232, pp. 1982-1990
Open Access | Times Cited: 3
Prediction of porosity and water saturation using pre-stack seismic attributes: a comparison of Bayesian inversion and computational intelligence methods
Hadi Fattahi, Sadegh Karimpouli
Computational Geosciences (2016) Vol. 20, Iss. 5, pp. 1075-1094
Closed Access | Times Cited: 29
Semisupervised sequence modeling for elastic impedance inversion
Motaz Alfarraj, Ghassan AlRegib
Interpretation (2019) Vol. 7, Iss. 3, pp. SE237-SE249
Open Access | Times Cited: 27
Is Apache Spark scalable to seismic data analytics and computations?
Yuzhong Yan, Lei Huang, Liqi Yi
2021 IEEE International Conference on Big Data (Big Data) (2015), pp. 2036-2045
Closed Access | Times Cited: 22
Building large-scale density model via a deep-learning-based data-driven method
Zhaoqi Gao, Chuang Li, Bing Zhang, et al.
Geophysics (2020) Vol. 86, Iss. 1, pp. M1-M15
Closed Access | Times Cited: 16
A Diffusion Filter Based Scheme to Denoise Seismic Attributes and Improve Predicted Porosity Volume
Soumi Chaki, Aurobinda Routray, William K. Mohanty
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2017) Vol. 10, Iss. 12, pp. 5265-5274
Closed Access | Times Cited: 18
Seismic facies analysis using machine learning techniques: a review and case study
Bernard Asare Owusu, Cyril D. Boateng, Van-Dycke Sarpong Asare, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 5, pp. 3899-3924
Closed Access | Times Cited: 1
A novel multiclass SVM based framework to classify lithology from well logs: A real-world application
Soumi Chaki, Aurobinda Routray, William K. Mohanty, et al.
(2015), pp. 1-5
Open Access | Times Cited: 12
Bakken stratigraphic and type well log learning network exploited to predict and data mine shear wave acoustic velocity
David A. Wood
Journal of Applied Geophysics (2019) Vol. 173, pp. 103936-103936
Closed Access | Times Cited: 11
Toward Real-Time Seismic Feature Analysis for Bright Spot Detection: A Distributed Approach
Yara Rizk, Hmayag Partamian, Mariette Awad
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2017) Vol. 11, Iss. 1, pp. 322-331
Closed Access | Times Cited: 10
A Novel Automatic Detection and Diagnosis Module for Quantitative Lithofacies Modeling
Saurabh Tewari, U. D. Dwivedi
(2018)
Closed Access | Times Cited: 10
A Novel Preprocessing Method Based on Variational Mode Decomposition for Reservoir Characterization Using Support Vector Regression
Soumi Chaki, Aurobinda Routray, William K. Mohanty
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2019) Vol. 12, Iss. 10, pp. 3759-3768
Closed Access | Times Cited: 9
Machine-Learning-Based Petrophysical Property Modeling
Sridharan Vallabhaneni, Rahul Saraf, Satyam Priyadarshy
SPE Europec featured at 81st EAGE Conference and Exhibition (2019)
Closed Access | Times Cited: 7
Application of Geologically Constrained Machine Learning Method in Characterizing Paleokarst Reservoirs of Tarim Basin, China
Wei Xin, Fei Tian, Xiaocai Shan, et al.
Water (2020) Vol. 12, Iss. 6, pp. 1765-1765
Open Access | Times Cited: 6
Reservoir Characterization: A Machine Learning Approach
Soumi Chaki
arXiv (Cornell University) (2015)
Open Access | Times Cited: 5
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