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D-Index & Metrics

Engineering and Technology

D-Index
50
Citations
7322
World Ranking
4181
National Ranking
1195

Overview

Pejman Tahmasebi is affiliated with the University of Wyoming in the United States and has made significant contributions to the fields of Engineering and Environmental Science. Their research spans several subfields including Ocean Engineering, Computational Mechanics, Mechanics of Materials, Mechanical Engineering, and Geophysics.

Their scholarly output includes work on various main topics such as Enhanced Oil Recovery Techniques, Hydrocarbon Exploration and Reservoir Analysis, Seismic Imaging and Inversion Techniques, Landslides and Related Hazards, Hydraulic Fracturing and Reservoir Analysis, Granular Flow and Fluidized Beds, and Groundwater Flow and Contamination Studies.

Among the recent publications is "Machine learning in geo- and environmental sciences: From small to large scale" (2020) published in Advances in Water Resources, which has received notable citations. Other significant papers in the broader research landscape associated with related topics include "A comparative machine learning study for time series oil production forecasting: ARIMA, LSTM, and Prophet" (2022) in Computers & Geosciences, "Physics informed machine learning: Seismic wave equation" (2020) in Geoscience Frontiers, "Graph neural network for groundwater level forecasting" (2022) in Journal of Hydrology, and "Reconstruction, optimization, and design of heterogeneous materials and media: Basic principles, computational algorithms, and applications" (2021) in Physics Reports.

Frequent collaborators with whom Pejman Tahmasebi has co-authored multiple works include Serveh Kamrava, Muhammad Sahimi, Tao Bai, Tsimur Davydzenka, and Yuqi Wu.

The primary venues for publication involve journals such as Physical Review E, Advances in Water Resources, Computers & Geosciences, Geoscience Frontiers, and Computers and Geotechnics, reflecting a focus on interdisciplinary approaches at the interface of engineering and environmental science.

Best Publications

  • Multiple-point geostatistical modeling based on the cross-correlation functions

    Pejman Tahmasebi;Ardeshir Hezarkhani;Muhammad Sahimi

  • A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation

    Pejman Tahmasebi;Ardeshir Hezarkhani

  • Segmentation of digital rock images using deep convolutional autoencoder networks

    Sadegh Karimpouli;Pejman Tahmasebi

  • Machine learning in geo- and environmental sciences: From small to large scale

    Pejman Tahmasebi;Serveh Kamrava;Tao Bai;Muhammad Sahimi

  • A comparative machine learning study for time series oil production forecasting: ARIMA, LSTM, and Prophet

    Unknown

  • A comprehensive study on geometric, topological and fractal characterizations of pore systems in low-permeability reservoirs based on SEM, MICP, NMR, and X-ray CT experiments

    Yuqi Wu;Yuqi Wu;Pejman Tahmasebi;Chengyan Lin;Muhammad Aleem Zahid

  • Cross-correlation function for accurate reconstruction of heterogeneous media

    Pejman Tahmasebi;Muhammad Sahimi

  • Reconstruction of three-dimensional porous media using a single thin section.

    Pejman Tahmasebi;Muhammad Sahimi

  • Linking Morphology of Porous Media to Their Macroscopic Permeability by Deep Learning

    Serveh Kamrava;Pejman Tahmasebi;Muhammad Sahimi

  • Physics informed machine learning: Seismic wave equation

    Sadegh Karimpouli;Pejman Tahmasebi

  • MS-CCSIM

    Pejman Tahmasebi;Muhammad Sahimi;Jef Caers

  • Application of Adaptive Neuro-Fuzzy Inference System for Grade Estimation; Case Study, Sarcheshmeh Porphyry Copper Deposit, Kerman, Iran

    Pejman Tahmasebi;Ardeshir Hezarkhani

  • Three-Dimensional Stochastic Characterization of Shale SEM Images

    Pejman Tahmasebi;Pejman Tahmasebi;Farzam Javadpour;Muhammad Sahimi

  • Comparative evaluation of back-propagation neural network learning algorithms and empirical correlations for prediction of oil PVT properties in Iran oilfields

    Jalil Asadisaghandi;Pejman Tahmasebi

  • Simulation of Earth textures by conditional image quilting

    K. Mahmud;K. Mahmud;G. Mariethoz;G. Mariethoz;J. Caers;P. Tahmasebi

  • Coupled hydro-mechanical analysis of seasonal underground hydrogen storage in a saline aquifer

    Unknown

  • Multiscale study for stochastic characterization of shale samples

    Pejman Tahmasebi;Pejman Tahmasebi;Farzam Javadpour;Muhammad Sahimi;Mohammad Piri

  • Comparing Training-Image Based Algorithms Using an Analysis of Distance

    Xiaojin Tan;Pejman Tahmasebi;Jef Caers

  • Data mining and machine learning for identifying sweet spots in shale reservoirs

    Pejman Tahmasebi;Farzam Javadpour;Muhammad Sahimi

  • Image-based velocity estimation of rock using Convolutional Neural Networks.

    Sadegh Karimpouli;Pejman Tahmasebi

  • Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm.

    Serveh Kamrava;Serveh Kamrava;Pejman Tahmasebi;Muhammad Sahimi

  • A fast and independent architecture of artificial neural network for permeability prediction

    Pejman Tahmasebi;Ardeshir Hezarkhani

Frequent Co-Authors

Muhammad Sahimi
Muhammad Sahimi University of Southern California
Jef Caers
Jef Caers Stanford University
Mohammad Piri
Mohammad Piri University of Wyoming
Albert J. Valocchi
Albert J. Valocchi University of Illinois at Urbana-Champaign
Erik H. Saenger
Erik H. Saenger Ruhr University Bochum
Andy Baker
Andy Baker University of New South Wales
Veerle Cnudde
Veerle Cnudde Utrecht University
Peyman Mostaghimi
Peyman Mostaghimi University of New South Wales
Davood Ghanbari
Davood Ghanbari Arak University of Technology
HengAn Wu
HengAn Wu University of Science and Technology of China

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