Prediction of Permeability Using Group Method of Data Handling (GMDH) Neural Network from Well Log Data

Group Method of Data Handling (GMDH) Lithology Identification Based on Wavelet Analysis and Dimensionality Reduction as Well Log Data Pre-Processing Techniques

(2019) Chuanbo Shen et al.   Energies

A novel analysis-prediction approach for geometrically nonlinear problems using group method of data handling

(2019) Tan N. Nguyen et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Sediment transport modeling in rigid boundary open channels using generalize structure of group method of data handling

(2019) Mir Jafar Sadegh Safari et al.   JOURNAL OF HYDROLOGY

Development of New Permeability Formulation From Well Log Data Using Artificial Intelligence Approaches

(2018) Tamer Moussa et al.   JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME

Artificial Neural Network-Based Prediction of Performances-Exhaust Emissions of Diesohol Piloted Dual Fuel Diesel Engine Under Varying Compressed Natural Gas Flowrates

(2018) Abhishek Paul et al.   JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME

A New Input Selection Algorithm Using the Group Method of Data Handling and Bootstrap Method for Support Vector Regression Based Hourly Load Forecasting

(2018) Jungwon Yu et al.   Energies

Investigating the Predictive Performance of Gaussian Process Regression in Evaluating Reservoir Porosity and Permeability

(2018) Solomon Asante-Okyere et al.   Energies

Modeling heat capacity of ionic liquids using group method of data handling: A hybrid and structure-based approach

(2018) Alireza Rostami et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

New insights into the prediction of heterogeneous carbonate reservoir permeability from well logs using artificial intelligence network

(2017) Salaheldin Elkatatny et al.   NEURAL COMPUTING & APPLICATIONS

Use of group method of data handling for transport energy demand modeling

(2017) Geer Teng et al.   Energy Science & Engineering

Global sensitivity analysis using sparse high dimensional model representations generated by the group method of data handling

(2016) Romain S.C. Lambert et al.   MATHEMATICS AND COMPUTERS IN SIMULATION

Modeling and prediction of geothermal reservoir temperature behavior using evolutionary design of neural networks

(2015) S. Porkhial et al.   GEOTHERMICS

Evaluation of GMDH networks for prediction of local scour depth at bridge abutments in coarse sediments with thinly armored beds

(2015) Mohammad Najafzadeh et al.   OCEAN ENGINEERING

A general approach for porosity estimation using artificial neural network method: a case study from Kansas gas field

(2015) Sagar Singh et al.   STUDIA GEOPHYSICA ET GEODAETICA

Artificial Neural Networks applied to estimate permeability, porosity and intrinsic attenuation using seismic attributes and well-log data

(2014) Ursula Iturrarán-Viveros et al.   JOURNAL OF APPLIED GEOPHYSICS

Applications of artificial intelligence methods in prediction of permeability in hydrocarbon reservoirs

(2014) Raoof Gholami et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Prediction of permeability in a tight gas reservoir by using three soft computing approaches: A comparative study

(2014) Sadegh Baziar et al.   Journal of Natural Gas Science and Engineering

Reservoir permeability prediction by neural networks combined with hybrid genetic algorithm and particle swarm optimization

(2012) Mohammad Ali Ahmadi et al.   GEOPHYSICAL PROSPECTING

A systematic method for permeability prediction, a Petro-Facies approach

(2011) A. Chehrazi et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

A new approach to improve neural networks' algorithm in permeability prediction of petroleum reservoirs using supervised committee machine neural network (SCMNN)

(2010) Sadegh Karimpouli et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Estimation of the Reservoir Permeability by Petrophysical Information Using Intelligent Systems

(2008) M. Ahmadi et al.   PETROLEUM SCIENCE AND TECHNOLOGY