A stochastic permeability model for the shale-gas systems

ME Naraghi, F Javadpour - International Journal of Coal Geology, 2015 - Elsevier
The pore network in shale reservoirs consists of pores associated with both organic matter
and inorganic matrix. The range of pore sizes within the organic matter is usually an order of …

Classification and identification of hydrocarbon reservoir lithofacies and their heterogeneity using seismic attributes, logs data and artificial neural networks

M Raeesi, A Moradzadeh, FD Ardejani… - Journal of Petroleum …, 2012 - Elsevier
3D seismic data interpretation plays a key role in identifying Lithofacies and their lateral
changes for hydrocarbon reservoirs exploration. Among mathematical analysis techniques …

Seismic facies analysis based on deep learning

Y Zhang, Y Liu, H Zhang, H Xue - IEEE Geoscience and …, 2019 - ieeexplore.ieee.org
Seismic facies analysis is to study the sedimentary environment of stratigraphic sequence
and provides an important basis for reservoir prediction. Most of the existing analysis …

Seismic facies analysis using machine learning techniques: a review and case study

BA Owusu, CD Boateng, VDS Asare, SK Danuor… - Earth Science …, 2024 - Springer
Seismic facies analysis which is aimed at identifying subsurface geological features from
seismic data, has evolved due to the time-consuming and labor-intensive nature of its …

Clinoform quantification for assessing the effects of external forcing on continental margin development

V Kertznus, B Kneller - Basin Research, 2009 - Wiley Online Library
The Ebro continental margin is characterized by a complex pattern of well‐developed, highly
progradational and aggradational, margin‐scale clinoforms. Analysis of conventional 3D …

Seismic facies analysis based on self-organizing map and empirical mode decomposition

H Du, J Cao, Y Xue, X Wang - Journal of Applied Geophysics, 2015 - Elsevier
Seismic facies analysis plays an important role in seismic interpretation and reservoir model
building by offering an effective way to identify the changes in geofacies inter wells. The …

A computationally efficient projection-based approach for spatial generalized linear mixed models

Y Guan, M Haran - Journal of Computational and Graphical …, 2018 - Taylor & Francis
Inference for spatial generalized linear mixed models (SGLMMs) for high-dimensional non-
Gaussian spatial data is computationally intensive. The computational challenge is due to …

Sedimentary architecture analysis of deltaic sand bodies using sequence stratigraphy and seismic sedimentology: a case study of Jurassic deposits in Zhetybay …

J Ni, D Zhao, X Liao, X Li, L Fu, R Chen, Z Xia, Y Liu - Energies, 2022 - mdpi.com
Three-dimensional (3D) seismic data and well log data were used to investigate the
sandstone architecture of the Middle Jurassic deltaic reservoirs of the Zhetybay Oilfield …

Robotized petrophysics: Machine learning and thermal profiling for automated mapping of lithotypes in unconventionals

Y Meshalkin, D Koroteev, E Popov, E Chekhonin… - Journal of Petroleum …, 2018 - Elsevier
We present a method for predicting rock types. The method is based on continuous high-
resolution thermal logging along full-size core samples and being applied for rocks from a …

[HTML][HTML] Reservoir heterogeneity analysis using multi-directional textural attributes from deep learning-based enhanced acoustic impedance inversion: A study from …

A Dixit, A Mandal, SS Ganguli - Energy Geoscience, 2024 - Elsevier
Reservoir heterogeneities play a crucial role in governing reservoir performance and
management. Traditionally, detailed and inter-well heterogeneity analyses are commonly …