Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 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

Showing 12 citing articles:

Evaluation and Development of a Predictive Model for Geophysical Well Log Data Analysis and Reservoir Characterization: Machine Learning Applications to Lithology Prediction
Aditya Mishra, Anjali Sharma, Atul Kumar Patidar
Natural Resources Research (2022) Vol. 31, Iss. 6, pp. 3195-3222
Closed Access | Times Cited: 51
Ensemble-based big data analytics of lithofacies for automatic development of petroleum reservoirs
Saurabh Tewari, U. D. Dwivedi
Computers & Industrial Engineering (2018) Vol. 128, pp. 937-947
Closed Access | Times Cited: 65
Driver Fatigue Detection Through Chaotic Entropy Analysis of Cortical Sources Obtained From Scalp EEG Signals
Aritra Chaudhuri, Aurobinda Routray
IEEE Transactions on Intelligent Transportation Systems (2019) Vol. 21, Iss. 1, pp. 185-198
Closed Access | Times Cited: 59
A comparative study of heterogeneous ensemble methods for the identification of geological lithofacies
Saurabh Tewari, U. D. Dwivedi
Journal of Petroleum Exploration and Production Technology (2020) Vol. 10, Iss. 5, pp. 1849-1868
Open Access | Times Cited: 54
A Novel Application of Ensemble Methods with Data Resampling Techniques for Drill Bit Selection in the Oil and Gas Industry
Saurabh Tewari, U. D. Dwivedi, Susham Biswas
Energies (2021) Vol. 14, Iss. 2, pp. 432-432
Open Access | Times Cited: 16
Identification of lithofacies from well log data in the upper Assam basin using machine learning techniques
Shikha Das, Dip Kumar Singha, Partha Pratim Mandal, et al.
Acta Geophysica (2024) Vol. 72, Iss. 5, pp. 3191-3210
Closed Access | Times Cited: 1
A Novel Automatic Detection and Diagnosis Module for Quantitative Lithofacies Modeling
Saurabh Tewari, U. D. Dwivedi
(2018)
Closed Access | Times Cited: 10
Application of Artificial Neural Networks for Identification of Lithofacies by Processing of Core Drilling Data
Mingsheng Yang, Yuanbiao Hu, Baolin Liu, et al.
Applied Sciences (2023) Vol. 13, Iss. 21, pp. 11934-11934
Open Access | Times Cited: 2
Automated Lithofacies Classification: A Comprehensive Machine Learning Approach in Shushan Basin Reservoirs, Western Desert, Egypt.
Amr M. Abuzeid, Ashraf R. Baghdady, Ahmed A. Kassem
Journal of African Earth Sciences (2024), pp. 105487-105487
Closed Access
Sweet Spot Identification in Unconventional Shale Reservoirs
Rabah Mesdour, Mustafa Basri, Cenk Temizel, et al.
(2023), pp. 333-349
Open 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
Classification for the Determination of Estimation Domains in a Cu-Zn Skarn Deposit in Central Peru, New Approach using Gaussian Kernel Support Vector Machine
Harold Velasquez Sanchez, Marjory Aguilar
(2020)
Open Access
Page 1

Scroll to top