Well-Logging-Based Lithology Classification Using Machine Learning Methods for High-Quality Reservoir Identification: A Case Study of Baikouquan Formation in Mahu Area of Junggar Basin, NW China
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Yunxin Xie & Chenyang Zhu & Yue Lu & Zhengwei Zhu, 2019. "Towards Optimization of Boosting Models for Formation Lithology Identification," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-13, August.
- Timur Merembayev & Darkhan Kurmangaliyev & Bakhbergen Bekbauov & Yerlan Amanbek, 2021. "A Comparison of Machine Learning Algorithms in Predicting Lithofacies: Case Studies from Norway and Kazakhstan," Energies, MDPI, vol. 14(7), pages 1-16, March.
- Antonio Mucherino & Petraq J. Papajorgji & Panos M. Pardalos, 2009. "Data Mining in Agriculture," Springer Optimization and Its Applications, Springer, number 978-0-387-88615-2, June.
- Matthias Schonlau & Rosie Yuyan Zou, 2020. "The random forest algorithm for statistical learning," Stata Journal, StataCorp LP, vol. 20(1), pages 3-29, March.
- Zhixue Sun & Baosheng Jiang & Xiangling Li & Jikang Li & Kang Xiao, 2020. "A Data-Driven Approach for Lithology Identification Based on Parameter-Optimized Ensemble Learning," Energies, MDPI, vol. 13(15), pages 1-15, July.
- Laura Auria & Rouslan A. Moro, 2008. "Support Vector Machines (SVM) as a Technique for Solvency Analysis," Discussion Papers of DIW Berlin 811, DIW Berlin, German Institute for Economic Research.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Sascha O. Becker, Sascha O & Voth, Hans-Joachim, 2023. "From the Death of God to the Rise of Hitler," The Warwick Economics Research Paper Series (TWERPS) 1478, University of Warwick, Department of Economics.
- Chetan Badgujar & Sanjoy Das & Dania Martinez Figueroa & Daniel Flippo, 2023. "Application of Computational Intelligence Methods in Agricultural Soil–Machine Interaction: A Review," Agriculture, MDPI, vol. 13(2), pages 1-39, January.
- Hui Zou & Zhihong Zou & Xiaojing Wang, 2015. "An Enhanced K-Means Algorithm for Water Quality Analysis of The Haihe River in China," IJERPH, MDPI, vol. 12(11), pages 1-14, November.
- Aurelia Rybak & Aleksandra Rybak & Spas D. Kolev, 2023. "Modeling the Photovoltaic Power Generation in Poland in the Light of PEP2040: An Application of Multiple Regression," Energies, MDPI, vol. 16(22), pages 1-17, November.
- Kyuhan Lee & Jinsoo Park & Iljoo Kim & Youngseok Choi, 2018. "Predicting movie success with machine learning techniques: ways to improve accuracy," Information Systems Frontiers, Springer, vol. 20(3), pages 577-588, June.
- Wang, Feipeng & Wong, Wing-Keung & Wang, Zheng & Albasher, Gadah & Alsultan, Nouf & Fatemah, Ambreen, 2023. "Emerging pathways to sustainable economic development: An interdisciplinary exploration of resource efficiency, technological innovation, and ecosystem resilience in resource-rich regions," Resources Policy, Elsevier, vol. 85(PA).
- Odile Carisse & Mamadou Lamine Fall, 2021. "Decision Trees to Forecast Risks of Strawberry Powdery Mildew Caused by Podosphaera aphanis," Agriculture, MDPI, vol. 11(1), pages 1-16, January.
- Orkida Ilollari & Petraq Papajorgji & Adrian Civici & Howard Moskowitz, 2022. "Measuring Client’s Feelings on Mobile Banking," Review of Applied Socio-Economic Research, Pro Global Science Association, vol. 23(1), pages 28-39, June.
- Xiaxuan He & Qifeng Yuan & Yinghong Qin & Junwen Lu & Gang Li, 2024. "Analysis of Surface Urban Heat Island in the Guangzhou-Foshan Metropolitan Area Based on Local Climate Zones," Land, MDPI, vol. 13(10), pages 1-34, October.
- Sagnik Anupam & Arpan Kumar Kar, 2021. "Phishing website detection using support vector machines and nature-inspired optimization algorithms," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 76(1), pages 17-32, January.
- Sascha O. Becker & Hans-Joachim Voth, 2023.
"From the Death of God to the Rise of Hitler,"
CESifo Working Paper Series
10730, CESifo.
- Becker, Sascha O. & Voth, Hans-Joachim, 2023. "From the Death of God to the Rise of Hitler," CAGE Online Working Paper Series 688, Competitive Advantage in the Global Economy (CAGE).
- Becker, Sascha O. & Voth, Hans-Joachim, 2023. "From the Death of God to the Rise of Hitler," CEPR Discussion Papers 18543, C.E.P.R. Discussion Papers.
- Sascha O. Becker & Hans-Joachim Voth, 2023. "From the Death of God to the Rise of Hitler," CEH Discussion Papers 03, Centre for Economic History, Research School of Economics, Australian National University.
- Becker, Sascha O. & Voth, Hans-Joachim, 2023. "From the Death of God to the Rise of Hitler," IZA Discussion Papers 16538, Institute of Labor Economics (IZA).
- Mostafaei, Kamran & maleki, Shaho & Zamani Ahmad Mahmoudi, Mohammad & Knez, Dariusz, 2022. "Risk management prediction of mining and industrial projects by support vector machine," Resources Policy, Elsevier, vol. 78(C).
- Ahmet Faruk Aysan & Bekir Sait Ciftler & Ibrahim Musa Unal, 2024. "Predictive Power of Random Forests in Analyzing Risk Management in Islamic Banking," JRFM, MDPI, vol. 17(3), pages 1-19, March.
- Sakiru Adebola Solarin & Muhammed Sehid Gorus & Onder Ozgur, 2024. "Modelling the economic effect of inbound birth tourism: a random forest algorithm approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(5), pages 4223-4240, October.
- Zhu, Xinyi & Shen, Xiaoyan & Chen, Kailiang & Zhang, Zeqing, 2024. "Research on the prediction and influencing factors of heavy duty truck fuel consumption based on LightGBM," Energy, Elsevier, vol. 296(C).
- Maria A. F. Silva Dias & Yania Molina Souto & Bruno Biazeto & Enzo Todesco & Jose A. Zuñiga Mora & Dylana Vargas Navarro & Melvin Pérez Chinchilla & Carlos Madrigal Araya & Dayanna Arce Fernández & Be, 2024. "Reduction of Wind Speed Forecast Error in Costa Rica Tejona Wind Farm with Artificial Intelligence," Energies, MDPI, vol. 17(22), pages 1-12, November.
- Özer Depren & Mustafa Tevfik Kartal & Serpil Kılıç Depren, 2021. "Recent innovation in benchmark rates (BMR): evidence from influential factors on Turkish Lira Overnight Reference Interest Rate with machine learning algorithms," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-20, December.
- Tomasz Rymarczyk & Konrad Niderla & Edward Kozłowski & Krzysztof Król & Joanna Maria Wyrwisz & Sylwia Skrzypek-Ahmed & Piotr Gołąbek, 2021. "Logistic Regression with Wave Preprocessing to Solve Inverse Problem in Industrial Tomography for Technological Process Control," Energies, MDPI, vol. 14(23), pages 1-21, December.
- Mingqiu Hou & Yuxiang Xiao & Zhengdong Lei & Zhi Yang & Yihuai Lou & Yuming Liu, 2023. "Machine Learning Algorithms for Lithofacies Classification of the Gulong Shale from the Songliao Basin, China," Energies, MDPI, vol. 16(6), pages 1-19, March.
- Johannes Berens & Kerstin Schneider & Simon Görtz & Simon Oster & Julian Burghoff, 2018.
"Early Detection of Students at Risk – Predicting Student Dropouts Using Administrative Student Data and Machine Learning Methods,"
CESifo Working Paper Series
7259, CESifo.
- Schneider, Kerstin & Berens, Johannes & Oster, Simon & Burghoff, Julian, 2018. "Early Detection of Students at Risk - Predicting Student Dropouts Using Administrative Student Data and Machine Learning Methods," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181544, Verein für Socialpolitik / German Economic Association.
- Johannes Berens & Simon Oster & Kerstin Schneider & Julian Burghoff, 2018. "Early Detection of Students at Risk - Predicting Student Dropouts Using Administrative Student Data and Machine Learning Methods," Schumpeter Discussion Papers sdp18006, Universitätsbibliothek Wuppertal, University Library.
More about this item
Keywords
machine learning; supervised classification; lithology identification; well-logging; ensemble methods; gradient-boosted decision trees;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3675-:d:817721. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.