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Kumar Hemant Singh

Observed names: K H Singh, K. H. Singh, K. Hemant Singh, K.H. Singh, KUMAR HEMANT SINGH, Kumar Hemant Singh, Kumar H. Singh, Kumar Singh
Observed institutions: Goddard Space Flight Center, Indian Institute of Technology Bombay, National Geophysical Research Institute, Govind Ballabh Pant University of Agriculture and Technology, ICAR-Directorate of Rapeseed-Mustard Research, Bharatpur, Council of Scientific and Industrial Research, University of Maryland, Baltimore County, Miami University, Banaras Hindu University
ORCID: 0000-0001-7341-1490
Observed ORCID: 0000-0001-7341-1490
OpenAlex ID: A5080367267
Depth to Curie temperature across the central Red Sea from magnetic data using the de-fractal method
2014 · Ahmed Salem, Chris Green, et al. · Tectonophysics · 119
Seismic Inversion Methods: A Practical Approach
2020 · S. P. Maurya, N. P. Singh, et al. · Springer geophysics · 66
Fractal analysis and spatial disposition of porosity in major indian gas shales using low-pressure nitrogen adsorption and advanced image segmentation
2019 · Ashutosh Tripathy, Anil Kumar, et al. · Journal of Natural Gas Science and Engineering · 48
Pore system, microstructure and porosity characterization of Gondwana shale of Eastern India using laboratory experiment and watershed image segmentation algorithm
2018 · Piyush Sarkar, Anil Kumar, et al. · Marine and Petroleum Geology · 45
Qualitative and quantitative comparison of geostatistical techniques of porosity prediction from the seismic and logging data: a case study from the Blackfoot Field, Alberta, Canada
2018 · S. P. Maurya, K. H. Singh, et al. · Marine Geophysical Research · 36
Qualitative and quantitative reservoir characterization using seismic inversion based on particle swarm optimization and genetic algorithm: a comparative case study
2024 · Ravi Kant, S. P. Maurya, et al. · Scientific Reports · 31
Forward modelling of oceanic lithospheric magnetization
2012 · S. M. Masterton, D. Gubbins, et al. · Geophysical Journal International · 29
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Predicting Porosity by Multivariate Regression and Probabilistic Neural Network using Model-based and Coloured Inversion as External Attributes: A Quantitative Comparison
2019 · S. P. Maurya, K. H. Singh · Journal of the Geological Society of India · 27
Core-log integration and application of machine learning technique for better reservoir characterisation of Eocene carbonates, Indian offshore
2021 · Ilius Mondal, Kumar Hemant Singh · Energy Geoscience · 23
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Petrophysical insights into pore structure in complex carbonate reservoirs using NMR data
2024 · Ilius Mondal, Kumar Hemant Singh · Petroleum Research · 21
Comparison of neural networks techniques to predict subsurface parameters based on seismic inversion: a machine learning approach
2024 · Nitin Verma, S. P. Maurya, et al. · Earth Science Informatics · 20
Qualitative and quantitative comparison of the genetic and hybrid genetic algorithm to estimate acoustic impedance from post-stack seismic data of Blackfoot field, Canada
2022 · S P Maurya, R Singh, et al. · Geophysical Journal International · 20
Use of genetic algorithm in reservoir characterisation from seismic data: A case study
2019 · Satya Prakash Maurya, Nagendra Pratap Singh, et al. · Journal of Earth System Science · 20
Enhancement of CO2 monitoring in the sleipner field (north sea) using seismic inversion based on simulated annealing of time-lapse seismic data
2024 · G. Hema, S.P. Maurya, et al. · Marine and Petroleum Geology · 19
Estimation of Elastic Parameters, Mineralogy and Pore Characteristics of Gondwana Shale in Eastern India for Evaluation of Shale Gas Potential
2018 · Piyush Sarkar, Kumar Hemant Singh, et al. · Current Science · 18
LP and ML Sparse Spike Inversion for Reservoir Characterization - A Case Study from Blackfoot Area, Alberta, Canada
2015 · S.P. Maurya, K.H. Singh · Proceedings · 17
Seismic inversion based on principal component analysis and probabilistic neural network for prediction of porosity from post-stack seismic data
2024 · Nitin Verma, Ravi kant, et al. · Earth Science Informatics · 15
Application of maximum likelihood and model-based seismic inversion techniques: a case study from K-G basin, India
2021 · Richa, S. P. Maurya, et al. · Journal of Petroleum Exploration and Production Technology · 15
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Integrated thin layer classification and reservoir characterization using sparse layer reflectivity inversion and radial basis function neural network: a case study
2024 · Raghav Singh, Aditya Srivastava, et al. · Marine Geophysical Research · 14
Prediction of acoustic impedance and density porosity using seismic inversion, and geostatistical methods on Krishna Godavari basin, India: A case study
2023 · S.P. Maurya, Richa, et al. · Journal of Applied Geophysics · 12
Reservoir characterisation using hybrid optimisation of genetic algorithm and pattern search to estimate porosity and impedance volume from post-stack seismic data: A case study
2024 · Nitin Verma, S P Maurya, et al. · Journal of Earth System Science · 11
Fluid substitution in NMR T2 distribution and resistivity independent saturation computation using synthetic capillary pressure data
2022 · Ilius Mondal, Kumar Hemant Singh · Petroleum Research · 11
Post-stack Seismic Inversion
2020 · S. P. Maurya, N. P. Singh, et al. · Springer geophysics · 11
Implementing 4D seismic inversion based on Linear Programming techniques for CO2 monitoring at the Sleipner field CCS site in the North Sea, Norway
2024 · Ajay Pratap Singh, Satya Prakash Maurya, et al. · Acta Geophysica · 10
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Fundamental of Seismic Inversion
2020 · S. P. Maurya, N. P. Singh, et al. · Springer geophysics · 10
Works count: 108
Citation count: 846
H-index: 16
I10-index: 27
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