Application of Machine Learning for Lithofacies Prediction and Cluster Analysis Approach to Identify Rock Type
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Application of Machine Learning for Lithofacies Prediction and Cluster Analysis Approach to Identify Rock Type
Authors
Keywords
-
Journal
Energies
Volume 15, Issue 12, Pages 4501
Publisher
MDPI AG
Online
2022-06-21
DOI
10.3390/en15124501
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Sedimentary Facies Controls for Reservoir Quality Prediction of Lower Shihezi Member-1 of the Hangjinqi Area, Ordos Basin
- (2022) Aqsa Anees et al. Minerals
- Identification of Favorable Zones of Gas Accumulation via Fault Distribution and Sedimentary Facies: Insights From Hangjinqi Area, Northern Ordos Basin
- (2022) Aqsa Anees et al. Frontiers in Earth Science
- Robust machine learning models of carbon dioxide trapping indexes at geological storage sites
- (2022) Hung Vo-Thanh et al. FUEL
- Reconstructing Daily Discharge in a Megadelta Using Machine Learning Techniques
- (2022) Hung Vo Thanh et al. WATER RESOURCES RESEARCH
- The ungrind and grinded effects on the pore geometry and adsorption mechanism of the coal particles
- (2022) Hassan Nasir Mangi et al. Journal of Natural Gas Science and Engineering
- Application of robust intelligent schemes for accurate modelling interfacial tension of CO2 brine systems: Implications for structural CO2 trapping
- (2022) Majid Safaei-Farouji et al. FUEL
- Machine Learning - A novel Approach of Well Logs Similarity based on Synchronization Measures to Predict Shear Sonic Logs
- (2021) Muhammad Ali et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- A Core Logging, Machine Learning and Geostatistical Modeling Interactive Approach for Subsurface Imaging of Lenticular Geobodies in a Clastic Depositional System, SE Pakistan
- (2021) Umar Ashraf et al. Natural Resources Research
- 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
- (2021) Amer A. Shehata et al. Journal of Natural Gas Science and Engineering
- Application of machine learning to predict CO2 trapping performance in deep saline aquifers
- (2021) Hung Vo Thanh et al. ENERGY
- Evaluation of the geothermal parameters to decipher the thermal structure of the upper crust of the Longmenshan fault zone derived from borehole data
- (2021) Jar Ullah et al. GEOTHERMICS
- Sweet spots prediction through fracture genesis using multi-scale geological and geophysical data in the karst reservoirs of Cambrian Longwangmiao Carbonate Formation, Moxi-Gaoshiti area in Sichuan Basin, South China
- (2021) Ren Jiang et al. Journal of Petroleum Exploration and Production Technology
- The impact of diagenesis on the reservoir quality of the early Cretaceous Lower Goru sandstones in the Lower Indus Basin, Pakistan
- (2021) Qamar UZ Zaman Dar et al. Journal of Petroleum Exploration and Production Technology
- Pore structure characteristics and fractal dimension analysis of low rank coal in the Lower Indus Basin, SE Pakistan
- (2020) Hassan Nasir Mangi et al. Journal of Natural Gas Science and Engineering
- Application of Unconventional Seismic Attributes and Unsupervised Machine Learning for the Identification of Fault and Fracture Network
- (2020) Umar Ashraf et al. Applied Sciences-Basel
- Evaluation of machine learning methods for lithology classification using geophysical data
- (2020) Thiago Santi Bressan et al. COMPUTERS & GEOSCIENCES
- Controls on Reservoir Heterogeneity of a Shallow-Marine Reservoir in Sawan Gas Field, SE Pakistan: Implications for Reservoir Quality Prediction Using Acoustic Impedance Inversion
- (2020) Umar Ashraf et al. Water
- Lessons for machine learning from the analysis of porosity-permeability transforms for carbonate reservoirs
- (2019) Frank Male et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- Lithological facies classification using deep convolutional neural network
- (2018) Yadigar Imamverdiyev et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- Classification of reservoir facies using well log and 3D seismic attributes for prospect evaluation and field development: A case study of Sawan gas field, Pakistan
- (2018) Umer Ashraf et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- Principal component analysis vs. self-organizing maps combined with hierarchical clustering for pattern recognition in volcano seismic spectra
- (2016) K. Unglert et al. JOURNAL OF VOLCANOLOGY AND GEOTHERMAL RESEARCH
- Efficient k NN classification algorithm for big data
- (2016) Zhenyun Deng et al. NEUROCOMPUTING
- Clustering spatio–seasonal hydrogeochemical data using self-organizing maps for groundwater quality assessment in the Red River Delta, Vietnam
- (2015) Thuy Thanh Nguyen et al. JOURNAL OF HYDROLOGY
- Applying the cluster analysis technique in logfacies determination for Mishrif Formation, Amara oil field, South Eastern Iraq
- (2014) Buraq Adnan Al-Baldawi Arabian Journal of Geosciences
- A hybrid approach for litho-facies characterization in the framework of sequence stratigraphy: A case study from the South Pars gas field, the Persian Gulf basin
- (2014) Ebrahim Sfidari et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- Identifying organic-rich Marcellus Shale lithofacies by support vector machine classifier in the Appalachian basin
- (2013) Guochang Wang et al. COMPUTERS & GEOSCIENCES
- Self-Organizing Maps applied to ecological sciences
- (2010) Tae-Soo Chon Ecological Informatics
- A support vector machine algorithm to classify lithofacies and model permeability in heterogeneous reservoirs
- (2010) A. Al-Anazi et al. ENGINEERING GEOLOGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search