Prediction of Shear Wave Velocity Using Artificial Neural Network Technique, Multiple Regression and Petrophysical Data: A Case Study in Asmari Reservoir (SW Iran)

Journals Menu

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Open Journal of Geology

ISSN Print: 2161-7570
ISSN Online: 2161-7589
www.scirp.org/journal/ojg
E-mail: ojg@scirp.org

Google-based Impact Factor: 0.83
Citations h5-index & Ranking

Journals Menu

"Prediction of Shear Wave Velocity Using Artificial Neural Network Technique, Multiple Regression and Petrophysical Data: A Case Study in Asmari Reservoir (SW Iran)"
written by Habib Akhundi, Mohammad Ghafoori, Gholam-Reza Lashkaripour,
published by Open Journal of Geology, Vol.4 No.7, 2014

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	Prediction of permeability from well logs using a new hybrid machine learning algorithm
	Petroleum, 2022

[2]	Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms
	Journal of Petroleum …, 2022

[3]	S-wave velocity inversion and prediction using a deep hybrid neural network
	Science China Earth Sciences, 2022

[4]	Estimation of shear wave velocity in an Iranian oil reservoir using machine learning methods
	Journal of Petroleum …, 2022

[5]	Artificial intelligence model for predicting geomechanical characteristics using easy-to-acquire offset logs without deploying logging tools
	Petroleum, 2022

[6]	A committee machine with intelligent experts (CMIE) for estimation of fast and slow shear wave velocities utilizing petrophysical logs
	Computers & …, 2022

[7]	Prediction of Shear Wave Velocity in the Williston Basin Using Big Data Analysis and Robust Machine Learning Algorithms
	56th US Rock …, 2022

[8]	Artificial Intelligence Model in Predicting Geomechanical Properties for Shale Formation: A Field Case in Permian Basin
	Energies, 2022

[9]	A novel approach to pore pressure modeling based on conventional well logs using convolutional neural network
	Journal of Petroleum …, 2022

[10]	Estimating shear wave velocity in carbonate reservoirs from petrophysical logs using intelligent algorithms
	Journal of Petroleum …, 2022

[11]	Estimation of Litho-Fluid Facies Distribution from Zero-Offset Acoustic and Shear Impedances
	Applied Sciences, 2022

[12]	Geomechanical analysis of an oil field: Numerical study of wellbore stability and reservoir subsidence
	Petroleum Research, 2022

[13]	Prediction of Shear Wave Velocity Based on a Hybrid Network of Two-Dimensional Convolutional Neural Network and Gated Recurrent Unit
	Geofluids, 2022

[14]	Synthetic shear sonic log generation utilizing hybrid machine learning techniques
	Artificial Intelligence in Geosciences, 2022

[15]	Prediction of Shear Wave Velocity by Extreme Learning Machine Technique from Well Log Data
	نشریه علمی پژوهشی ژئومکانیک …, 2022

[16]	Prediction of Sonic Shear Wave Using Artificial Neural Network
	Majeed… - The Iraqi Geological …, 2022

[17]	Prediction of shear wave velocity and modification of Castagna and Carroll relationships in one of the Iranian oil fields
	Rudarsko-geološko-naftni …, 2022

[18]	Development of 1D-Synthetic Geomechanical Well Logs for Applications Related to Reservoir Geomechanics in Buzurgan Oil Field
	The Iraqi Geological Journal, 2021

[19]	Successful Case Study of Machine Learning Application to Streamline and Improve History Matching Process for Complex Gas-Condensate Reservoirs in Hai Thach …
	SPE Middle East Oil & …, 2021

[20]	Successful Application of Machine Learning to Improve Dynamic Modeling and History Matching for Complex Gas-Condensate Reservoirs in Hai Thach Field, Nam …
	… Intelligence-Towards a …, 2021

[21]	Chemezov II, Lechenko GE, Volkov KR, Prisyazhnaya VS, Dyomyshev IS, Bugorskiy DS
	Организационный комитет, 2021

[22]	Shear wave velocity estimation utilizing statistical and multi-intelligent models from petrophysical data in a mixed carbonate-siliciclastic reservoir, SW Iran
	2021

[23]	МАШИННОЕ ОБУЧЕНИЕ КАК ПОЛЕЗНЫЙ ИНСТРУМЕНТ В ИССЛЕДОВАНИИ ГЕОМЕХАНИКИ МЕСТОРОЖДЕНИЯ ПРИРОДНОГО ГАЗА
	… современной науки и …, 2021

[24]	Prediction of shear wave velocity using machine learning technique, multiple regression and well logs
	ARMA/DGS/SEG 2nd International Geomechanics …, 2021

[25]	Improved prediction of shear wave velocity for clastic sedimentary rocks using hybrid model with core data
	Journal of Rock Mechanics and Geotechnical …, 2021

[26]	Application of conditional generative model for sonic log estimation considering measurement uncertainty
	2021

[27]	Shear wave velocity prediction based on LSTM and its application for morphology identification and saturation inversion of gas hydrate
	2021

[28]	Shear Wave Velocity Prediction of Carbonate Reservoirs Based on CatBoost
	2021

[29]	Data-driven S-wave velocity prediction method via a deep-learning-based deep convolutional gated recurrent unit fusion network
	Geophysics, 2021

[30]	A new rock physics model to estimate shear velocity log
	2021

[31]	Rock physics model-based prediction of shear wave velocity utilizing machine learning technique for a carbonate reservoir, southwest Iran
	2020

[32]	Predictive Models and Feature Ranking in Reservoir Geomechanics: A Critical Review and Research Guidelines
	2020

[33]	Shear wave velocity prediction based on adaptive particle swarm optimization optimized recurrent neural network
	2020

[34]	ANALISIS PREDIKSI SHEAR-WAVE VELOCITY MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK
	2020

[35]	Computation Methods in Petrophysics for Addressing Redundancy and Reservoir Property Prediction
	2020

[36]	Machine Learning: A Useful Tool in Geomechanical Studies, a Case Study from an Offshore Gas Field
	2020

[37]	Improvement of petrophysical workflow for shear wave velocity prediction based on machine learning methods for complex carbonate reservoirs
	2020

[38]	Predicting of shear wave velocity using Artificial Neural Networks
	2020

[39]	A Machine Learning Approach to Shear Sonic Log Prediction
	2019

[40]	CMUT-based biosensor with convolutional neural network signal processing
	2019

[41]	Machine learning technique for the prediction of shear wave velocity using petrophysical logs
	2019

[42]	Combining classification and regression for improving shear wave velocity estimation from well logs data
	2019

[43]	A new integrated workflow for improving permeability estimation in a highly heterogeneous reservoir of Sawan Gas Field from well logs data
	Geomechanics and Geophysics for Geo-Energy and Geo-Resources, 2018

[44]	استفاده از مدل هیبریدی ACOR-BP جهت تخمین سرعت موج برشی از نگارهای تخلخل‎
	2018

[45]	Data driven model for sonic well log prediction
	Journal of Petroleum Science and Engineering, 2018

[46]	Прогноз изменения скорости поперечной волны в породах на месторождении СП" Вьесовпетро" на шельфе Вьетнама
	2018

[47]	Development of Hybrid ACOR-BP Algorithm for Estimation of Shear Wave Velocity from Porosity Logs
	Journal of Petroleum Research, 2018

[48]	Predicting Shear Wave Velocity of Soil Using Multiple Linear Regression Analysis and Artificial Neural Networks
	2017

[49]	بهینه سازی اجتماع ذرات به منظور تخمین سرعت موج برشی از داده های چاه پیمایی‎
	2017

[50]	Estimating shear wave velocities in oil fields: a neural network approach
	Geosciences Journal, 2015

[51]	Metamorfik Kayaçlarda Vp ve Vs Dalga Hızları Arasındaki İlişkiler


[52]	CONSTRUCTION OF A VELOCITY MODEL OF SHEAR WAVE FOR COMPLEXLY STRUCTURED GEOLOGICAL MEDIUM USING NEURAL NETWORK (BY …


[53]	Shear Wave Velocity Prediction Based on Cross Convolution Network

[1]	Rock-physics-guided machine learning for shear sonic log prediction GEOPHYSICS, 2024 DOI:10.1190/geo2023-0152.1

[2]	Exploring Shear Wave Velocity—NSPT Correlations for Geotechnical Site Characterization: A Review CivilEng, 2024 DOI:10.3390/civileng5010006

[3]	Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms Journal of Petroleum Exploration and Production Technology, 2023 DOI:10.1007/s13202-022-01531-z

[4]	Prediction of permeability from well logs using a new hybrid machine learning algorithm Petroleum, 2023 DOI:10.1016/j.petlm.2022.03.003

[5]	Robust estimation of shear wave velocity in a carbonate oil reservoir from conventional well logging data using machine learning algorithms Journal of Applied Geophysics, 2023 DOI:10.1016/j.jappgeo.2023.104971

[6]	Reconstruction of missing shear wave slowness in shale gas reservoir based on deep learning algorithm Geoenergy Science and Engineering, 2023 DOI:10.1016/j.geoen.2023.211865

[7]	Machine Learning Techniques for Soil Characterization Using Cone Penetration Test Data Applied Sciences, 2023 DOI:10.3390/app13148286

[8]	Predicting Shear Wave Velocity Using a Convolutional Neural Network and Dual-Constraint Calculation for Anisotropic Parameters Incorporating Compressional and Shear Wave Velocities Processes, 2023 DOI:10.3390/pr11082356

[9]	Geomechanical analysis of an oil field: Numerical study of wellbore stability and reservoir subsidence Petroleum Research, 2023 DOI:10.1016/j.ptlrs.2022.08.002

[10]	Statistical and machine learning hybridization for predicting shear wave velocity in tight sand reservoirs: A case study Geoenergy Science and Engineering, 2023 DOI:10.1016/j.geoen.2023.212420

[11]	Synthetic shear sonic log generation utilizing hybrid machine learning techniques Artificial Intelligence in Geosciences, 2022 DOI:10.1016/j.aiig.2022.09.001

[12]	Synthetic shear sonic log generation utilizing hybrid machine learning techniques Artificial Intelligence in Geosciences, 2022 DOI:10.1016/j.aiig.2022.09.001

[13]	Estimation of shear wave velocity in an Iranian oil reservoir using machine learning methods Journal of Petroleum Science and Engineering, 2022 DOI:10.1016/j.petrol.2021.109841

[14]	Metamorfik Kayaçlarda Vp ve Vs Dalga Hızları Arasındaki İlişkiler European Journal of Science and Technology, 2022 DOI:10.31590/ejosat.1040028

[15]	Prediction of permeability from well logs using a new hybrid machine learning algorithm Petroleum, 2022 DOI:10.1016/j.petlm.2022.03.003

[16]	基于深度混合神经网络的横波速度反演预测方法 SCIENTIA SINICA Terrae, 2022 DOI:10.1360/SSTe-2021-0128

[17]	A committee machine with intelligent experts (CMIE) for estimation of fast and slow shear wave velocities utilizing petrophysical logs Computers & Geosciences, 2022 DOI:10.1016/j.cageo.2022.105149

[18]	Prediction of Shear Wave Velocity Based on a Hybrid Network of Two-Dimensional Convolutional Neural Network and Gated Recurrent Unit Geofluids, 2022 DOI:10.1155/2022/9974157

[19]	Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms Journal of Petroleum Exploration and Production Technology, 2022 DOI:10.1007/s13202-022-01531-z

[20]	Artificial intelligence model for predicting geomechanical characteristics using easy-to-acquire offset logs without deploying logging tools Petroleum, 2022 DOI:10.1016/j.petlm.2021.10.002

[21]	Estimation of Litho-Fluid Facies Distribution from Zero-Offset Acoustic and Shear Impedances Applied Sciences, 2022 DOI:10.3390/app12157754

[22]	Geomechanical analysis of an oil field: Numerical study of wellbore stability and reservoir subsidence Petroleum Research, 2022 DOI:10.1016/j.ptlrs.2022.08.002

[23]	Synthetic shear sonic log generation utilizing hybrid machine learning techniques Artificial Intelligence in Geosciences, 2022 DOI:10.1016/j.aiig.2022.09.001

[24]	S-wave velocity inversion and prediction using a deep hybrid neural network Science China Earth Sciences, 2022 DOI:10.1007/s11430-021-9870-8

[25]	Artificial Intelligence Model in Predicting Geomechanical Properties for Shale Formation: A Field Case in Permian Basin Energies, 2022 DOI:10.3390/en15228752

[26]	Artificial intelligence model for predicting geomechanical characteristics using easy-to-acquire offset logs without deploying logging tools Petroleum, 2022 DOI:10.1016/j.petlm.2021.10.002

[27]	A committee machine with intelligent experts (CMIE) for estimation of fast and slow shear wave velocities utilizing petrophysical logs Computers & Geosciences, 2022 DOI:10.1016/j.cageo.2022.105149

[28]	Estimation of shear wave velocity in an Iranian oil reservoir using machine learning methods Journal of Petroleum Science and Engineering, 2022 DOI:10.1016/j.petrol.2021.109841

[29]	Shear wave velocity prediction based on LSTM and its application for morphology identification and saturation inversion of gas hydrate Journal of Petroleum Science and Engineering, 2021 DOI:10.1016/j.petrol.2021.109027

[30]	Application of conditional generative model for sonic log estimation considering measurement uncertainty Journal of Petroleum Science and Engineering, 2021 DOI:10.1016/j.petrol.2020.108028

[31]	Shear Wave Velocity Prediction of Carbonate Reservoirs Based on CatBoost 2021 4th International Conference on Artificial Intelligence and Big Data (ICAIBD), 2021 DOI:10.1109/ICAIBD51990.2021.9459061

[32]	Data-driven S-wave velocity prediction method via a deep-learning-based deep convolutional gated recurrent unit fusion network GEOPHYSICS, 2021 DOI:10.1190/geo2020-0886.1

[33]	Successful Application of Machine Learning to Improve Dynamic Modeling and History Matching for Complex Gas-Condensate Reservoirs in Hai Thach Field, Nam Con Son Basin, Offshore Vietnam Day 2 Tue, October 19, 2021, 2021 DOI:10.2118/208657-MS

[34]	Shear wave velocity prediction based on LSTM and its application for morphology identification and saturation inversion of gas hydrate Journal of Petroleum Science and Engineering, 2021 DOI:10.1016/j.petrol.2021.109027

[35]	Successful Case Study of Machine Learning Application to Streamline and Improve History Matching Process for Complex Gas-Condensate Reservoirs in Hai Thach Field, Offshore Vietnam Day 2 Mon, November 29, 2021, 2021 DOI:10.2118/204835-MS

[36]	Improved prediction of shear wave velocity for clastic sedimentary rocks using hybrid model with core data Journal of Rock Mechanics and Geotechnical Engineering, 2021 DOI:10.1016/j.jrmge.2021.06.014

[37]	Improvement of petrophysical workflow for shear wave velocity prediction based on machine learning methods for complex carbonate reservoirs Journal of Petroleum Science and Engineering, 2020 DOI:10.1016/j.petrol.2020.107234

[38]	Shear wave velocity prediction based on adaptive particle swarm optimization optimized recurrent neural network Journal of Petroleum Science and Engineering, 2020 DOI:10.1016/j.petrol.2020.107466

[39]	GEODYNAMICS GEODYNAMICS, 2020 DOI:10.23939/jgd2020.01.071

[40]	Machine Learning: A Useful Tool in Geomechanical Studies, a Case Study from an Offshore Gas Field Energies, 2020 DOI:10.3390/en13143528

[41]	Rock physics model-based prediction of shear wave velocity utilizing machine learning technique for a carbonate reservoir, southwest Iran Journal of Petroleum Science and Engineering, 2020 DOI:10.1016/j.petrol.2020.107864

[42]	Petro-physics and Rock Physics of Carbonate Reservoirs 2020 DOI:10.1007/978-981-13-1211-3_12

[43]	A Machine Learning Approach to Shear Sonic Log Prediction SPE Nigeria Annual International Conference and Exhibition, 2019 DOI:10.2118/198764-MS

[44]	Combining classification and regression for improving shear wave velocity estimation from well logs data Journal of Petroleum Science and Engineering, 2019 DOI:10.1016/j.petrol.2019.106260

[45]	CMUT-based biosensor with convolutional neural network signal processing Ultrasonics, 2019 DOI:10.1016/j.ultras.2019.105956

[46]	Machine learning technique for the prediction of shear wave velocity using petrophysical logs Journal of Petroleum Science and Engineering, 2019 DOI:10.1016/j.petrol.2018.11.032

[47]	A new integrated workflow for improving permeability estimation in a highly heterogeneous reservoir of Sawan Gas Field from well logs data Geomechanics and Geophysics for Geo-Energy and Geo-Resources, 2018 DOI:10.1007/s40948-018-0101-y

[48]	Data driven model for sonic well log prediction Journal of Petroleum Science and Engineering, 2018 DOI:10.1016/j.petrol.2018.06.072

[49]	Estimating shear wave velocities in oil fields: a neural network approach Geosciences Journal, 2016 DOI:10.1007/s12303-015-0036-z

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Open Journal of Geology

Open Journal of Geology

Journals Menu

Home

About SCIRP

Service

Policies