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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:

Well tops guided prediction of reservoir properties using modular neural network concept: A case study from western onshore, India
Soumi Chaki, Akhilesh Verma, Aurobinda Routray, et al.
Journal of Petroleum Science and Engineering (2014) Vol. 123, pp. 155-163
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Application of supervised machine learning paradigms in the prediction of petroleum reservoir properties: Comparative analysis of ANN and SVM models
Daniel Asante Otchere, Tarek Ganat, Raoof Gholami, et al.
Journal of Petroleum Science and Engineering (2020) Vol. 200, pp. 108182-108182
Closed Access | Times Cited: 355
Machine learning and multi-agent systems in oil and gas industry applications: A survey
Khadijah Muzzammil Hanga, Yevgeniya Kovalchuk
Computer Science Review (2019) Vol. 34, pp. 100191-100191
Open Access | Times Cited: 133
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
RETRACTED ARTICLE: A comprehensive study on artificial intelligence in oil and gas sector
Devansh Gupta, Manan Shah
Environmental Science and Pollution Research (2021) Vol. 29, Iss. 34, pp. 50984-50997
Closed Access | Times Cited: 27
Machine learning methods for estimating permeability of a reservoir
Hera Khan, Ayush Srivastav, Amit Kumar Mishra, et al.
International Journal of Systems Assurance Engineering and Management (2022) Vol. 13, Iss. 5, pp. 2118-2131
Closed Access | Times Cited: 19
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
Gaussian mixture model deep neural network and its application in porosity prediction of deep carbonate reservoir
Yingying Wang, Liping Niu, Luanxiao Zhao, et al.
Geophysics (2021) Vol. 87, Iss. 2, pp. M59-M72
Closed Access | Times Cited: 21
Neural network applications to reservoirs: Physics-based models and data models
Tahar Aı̈fa
Journal of Petroleum Science and Engineering (2014) Vol. 123, pp. 1-6
Open Access | Times Cited: 24
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
Artificial Neural Network Modeling and Forecasting of Oil Reservoir Performance
Ehsan Amirian, Eugene Fedutenko, Chaodong Yang, et al.
Lecture notes in social networks (2018), pp. 43-67
Closed Access | Times Cited: 18
Reservoir quality estimation using a new ternary diagram approach applied to carbonate formations in north-western Iraq
Omar K. Mohammed-Sajed, Paul Glover, Richard Collier
Journal of Petroleum Science and Engineering (2020) Vol. 196, pp. 108024-108024
Open Access | Times Cited: 14
Quantification of sand fraction from seismic attributes using Neuro-Fuzzy approach
Akhilesh Verma, Soumi Chaki, Aurobinda Routray, et al.
Journal of Applied Geophysics (2014) Vol. 111, pp. 141-155
Open Access | Times Cited: 13
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
A Novel Automatic Detection and Diagnosis Module for Quantitative Lithofacies Modeling
Saurabh Tewari, U. D. Dwivedi
(2018)
Closed Access | Times Cited: 10
Automatic characterization and quantitative analysis of seismic facies in naturally fractured reservoir: Case study of Amguid Messaoud field, Algeria
Hamlaoui Mahmoud
Mining of Mineral Deposits (2023) Vol. 17, Iss. 3, pp. 42-48
Open Access | Times Cited: 3
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
Geostatistical Three-Dimensional Modeling of a Tight Gas Reservoir: A Case Study of Block S6 of the Sulige Gas Field, Ordos Basin, China
Jinliang Zhang, Longlong Liu, Ruoshan Wang
Energies (2017) Vol. 10, Iss. 9, pp. 1439-1439
Open Access | Times Cited: 6
Reservoir Characterization: A Machine Learning Approach
Soumi Chaki
arXiv (Cornell University) (2015)
Open Access | Times Cited: 5
Development of a hybrid learning system based on SVM, ANFIS and domain knowledge: DKFIS
Soumi Chaki, Aurobinda Routray, William K. Mohanty, et al.
(2015) Vol. 3, pp. 1-6
Open Access | Times Cited: 3
Seismic inversion based on principal component analysis and probabilistic neural network for prediction of porosity from post-stack seismic data
Nitin Verma, Ravi Kant, S. P. Maurya, et al.
Earth Science Informatics (2024) Vol. 18, Iss. 1
Closed Access
Machine learning
Mohammad Ali Ahmadi
Elsevier eBooks (2024), pp. 31-60
Closed Access
A Variational Mode Decomposition Based Novel Preprocessing Method for Reservoir Characterization Using Support Vector Regression
Soumi Chaki, Aurobinda Routray, William K. Mohanty
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (2018), pp. 6171-6174
Closed Access | Times Cited: 3
Stochastic modeling of earth’s hydrocarbon resources using artificial neural network
A. Sircar, Biswajit Thander, Kriti Yadav
Modeling Earth Systems and Environment (2020) Vol. 7, Iss. 3, pp. 1579-1594
Closed Access | Times Cited: 3
Machine Learning Involvement in Reservoir Simulation by Optimizing Algorithms in SAGD and SA-SAGD Processes
Yu Zhang
(2017)
Closed Access | Times Cited: 1
Application of Machine Learning Algorithms for Petroleum Reservoir Characterization
Soumi Chaki, Aurobinda Routray, William K. Mohanty
(2022), pp. 6-20
Closed Access | Times Cited: 1
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