Articles citing this paper
Application of the radial basis function neural network to the prediction of log properties from seismic attributes
B.H. Russell, L.R. Lines and D.P. Hampson
34(2) pp.15 - 23
26 articles found in Crossref database.
Sand fraction prediction from seismic attributes using optimized support vector regression in an oil reservoir
Amiri Bakhtiar Mohammad Sadegh,
Zargar Ghasem,
Riahi Mohammad Ali, Ansari Hamid Reza
Earth Science Informatics. 2020 13(2). p.405
A Missing Well-Logs Imputation Method Based on Conditional Denoising Diffusion Probabilistic Models
Meng Han,
Lin Botao,
Zhang Ruxin, Jin Yan
SPE Journal. 2024 p.1
Toward improved coal density estimation from geophysical logs
Zhou Binzhong, Esterle Joan
Exploration Geophysics. 2008 39(2). p.124
Use seismic colored inversion and power law committee machine based on imperial competitive algorithm for improving porosity prediction in a heterogeneous reservoir
Ansari Hamid Reza
Journal of Applied Geophysics. 2014 108 p.61
The effective seismic attributes in porosity prediction for different rock types: Some implications from four case studies
Abdulaziz Abdulaziz M.
Egyptian Journal of Petroleum. 2020 29(1). p.95
Data kit inversion and uncertainty analysis
Fernández-Muñiz Zulima,
Khaniani Hassan, Fernández-Martínez Juan Luis
Journal of Applied Geophysics. 2019 161 p.228
Reservoir Characterisation of High-Pressure, High-Temperature Zone of Malay Basin Using Seismic Inversion and Artificial Neural Network Approach
Yazmyradova Gulbahar,
Hassan Nik Nur Anis Amalina Nik Mohd,
Salleh Nur Farhana,
Hermana Maman, Soleimani Hassan
Applied Sciences. 2021 11(21). p.10248
Shear wave velocity prediction using seismic attributes and well log data
Gholami Raoof,
Moradzadeh Ali,
Rasouli Vamegh, Hanachi Javid
Acta Geophysica. 2014 62(4). p.818
Gaussian mixture model deep neural network and its application in porosity prediction of deep carbonate reservoir
Wang Yingying,
Niu Liping,
Zhao Luanxiao,
Wang Benfeng,
He Zhiliang,
Zhang Hong,
Chen Dong, Geng Jianhua
GEOPHYSICS. 2022 87(2). p.M59
Integration of well logs and seismic attributes for prediction of thermal maturity and TOC content in the Kazhdumi Formation (central Persian Gulf basin)
Aliakbardoust Elnaz,
Adabi Mohammad Hossein,
Kadkhodaie Ali,
Harris Nicholas B., Chehrazi Ali
Journal of Applied Geophysics. 2024 222 p.105319
Estimation of reservoir porosity using analysis of seismic attributes in an Iranian oil field
Soleimani Fatemeh,
Hosseini Erfan, Hajivand Farzad
Journal of Petroleum Exploration and Production Technology. 2020 10(4). p.1289
Application of supervised machine learning paradigms in the prediction of petroleum reservoir properties: Comparative analysis of ANN and SVM models
Otchere Daniel Asante,
Arbi Ganat Tarek Omar,
Gholami Raoof, Ridha Syahrir
Journal of Petroleum Science and Engineering. 2021 200 p.108182
Improving coal quality estimation through multiple geophysical log analysis
Zhou Binzhong, O'Brien Graham
International Journal of Coal Geology. 2016 167 p.75
Estimation of porosity from seismic attributes using a committee model with bat-inspired optimization algorithm
Gholami Amin, Ansari Hamid Reza
Journal of Petroleum Science and Engineering. 2017 152 p.238
Artificial Neural Networks in the domain of reservoir characterization: A review from shallow to deep models
Saikia Pallabi,
Baruah Rashmi Dutta,
Singh Sanjay Kumar, Chaudhuri Pradip Kumar
Computers & Geosciences. 2020 135 p.104357
Estimation of subsurface rock properties from seismic inversion and geo-statistical methods over F3-block, Netherland
Kushwaha Prabodh Kumar,
Maurya Satya Prakash,
Rai Piyush, Singh Nagendra Pratap
Exploration Geophysics. 2021 52(3). p.258
Estimation of Reservoir Porosity and Water Saturation Based on Seismic Attributes Using Support Vector Regression Approach
Na’imi S.R.,
Shadizadeh S.R.,
Riahi M.A., Mirzakhanian M.
Journal of Applied Geophysics. 2014 107 p.93
Stacked ensemble model for reservoir characterisation to predict log properties from seismic signals
Saikia Pallabi, Baruah Rashmi Dutta
Computational Geosciences. 2023 27(6). p.1067
Predicting Porosity by Using Seismic Multi-Attributes and Well Data and Combining These Available Data by Geostatistical Methods in a South Iranian Oil Field
Jalalalhosseini S. M.,
Ali H., Mostafazadeh M.
Petroleum Science and Technology. 2014 32(1). p.29
Artificial Intelligence and Data Analytics for Energy Exploration and Production (2022)
Comparison of neural networks techniques to predict subsurface parameters based on seismic inversion: a machine learning approach
Verma Nitin,
Maurya S. P.,
kant Ravi,
Singh K. H.,
Singh Raghav,
Singh A. P.,
Hema G.,
Srivastava M. K.,
Tiwari Alok K.,
Kushwaha P. K., Singh Richa
Earth Science Informatics. 2024 17(2). p.1031
Petroleum reservoir properties estimation using neural networks
2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) (2015)
3D model of water saturation, effective porosity and volume of shale in upper Assam Shelf, India using multi-attribute regression and cascade-probabilistic neural network
Rai Neha,
Singha Dip Kumar, Chatterjee Rima
Journal of Applied Geophysics. 2023 218 p.105202
Petrophysical data prediction from seismic attributes using committee fuzzy inference system
Kadkhodaie-Ilkhchi Ali,
Rezaee M. Reza,
Rahimpour-Bonab Hossain, Chehrazi Ali
Computers & Geosciences. 2009 35(12). p.2314
Comparison of model-based generalized regression neural network and prestack inversion in predicting Poisson's ratio in Heidrun Field, North Sea
Keynejad Saba,
Sbar Marc L., Johnson Roy A.
The Leading Edge. 2017 36(11). p.938
Hydrocarbon-bearing dolomite reservoir characterization: A case study from eastern Canada
SEG Technical Program Expanded Abstracts 2014 (2014)