Enhanced group method of data handling (GMDH) for permeability prediction based on the modified Levenberg Marquardt technique from well log data
AK Mulashani, C Shen, BM Nkurlu, CN Mkono… - Energy, 2022 - Elsevier
Permeability is the key variable for reservoir characterization used for estimating the flow
patterns and volume of hydrocarbons. Modern computer advancement has highlighted the …
patterns and volume of hydrocarbons. Modern computer advancement has highlighted the …
Convergent newton method and neural network for the electric energy usage prediction
In the neural network adaptation, the Newton method could find a minimum with its second-
order partial derivatives, and convergent gradient steepest descent could assure its error …
order partial derivatives, and convergent gradient steepest descent could assure its error …
Logging-data-driven permeability prediction in low-permeable sandstones based on machine learning with pattern visualization: A case study in Wenchang A Sag …
X Zhao, X Chen, Q Huang, Z Lan, X Wang… - Journal of Petroleum …, 2022 - Elsevier
Permeability is a crucial analytical variable in petrophysical parameters of reservoir rocks,
which is highly related to geo-energy exploration and evaluation. Conventional physics …
which is highly related to geo-energy exploration and evaluation. Conventional physics …
[HTML][HTML] Investigations on the relationship among the porosity, permeability and pore throat size of transition zone samples in carbonate reservoirs using multiple …
Finding an accurate method for estimating permeability aside from well logs has been a
difficult task for many years. The most commonly used methods targeted towards regression …
difficult task for many years. The most commonly used methods targeted towards regression …
[HTML][HTML] Utilizing machine learning for flow zone indicators prediction and hydraulic flow unit classification
Reservoir characterization, essential for understanding subsurface heterogeneity, often
faces challenges due to scale-dependent variations. This study addresses this issue by …
faces challenges due to scale-dependent variations. This study addresses this issue by …
NMR-data-driven prediction of matrix permeability in sandstone aquifers
Predicting the matrix permeability of subsurface sandstone aquifers is a formidable
challenge. One test showing great promise is nuclear magnetic resonance (NMR), as it is …
challenge. One test showing great promise is nuclear magnetic resonance (NMR), as it is …
Image segmentation and flow prediction of digital rock with U-net network
F Wang, Y Zai - Advances in Water Resources, 2023 - Elsevier
Computed tomography (CT) images of sandstone contain rich reservoir information.
Analyzing digital rock images is important for geological research and the flow in the …
Analyzing digital rock images is important for geological research and the flow in the …
Permeability estimating beyond boreholes from electrical conductivity data determined from magnetotelluric sounding: Soultz-sous-Forêts site (France) case study
V Spichak, O Zakharova - Geothermics, 2022 - Elsevier
Permeability of intact and fractured core samples collected in EPS1 borehole at the Soultz-
sous-Forêts geothermal site (France) is used for neural network permeability prediction …
sous-Forêts geothermal site (France) is used for neural network permeability prediction …
Machine learning approaches for formation matrix volume prediction from well logs: insights and lessons learned
PVD Kannaiah, NK Maurya - Geoenergy Science and Engineering, 2023 - Elsevier
Determining the formation rock type and their petrophysical properties using well-log data is
necessary for resource assessment. Formation porosity, shale content, and saturations must …
necessary for resource assessment. Formation porosity, shale content, and saturations must …
Identification of the relatively low permeability area in coal and gas outburst seams by seismic wave tomography technique: Field application and validation
Identifying relatively low permeability areas (RLPA) is significant for site selection and
parameter design for implementing enhanced gas mining measures (eg hydraulic fracturing …
parameter design for implementing enhanced gas mining measures (eg hydraulic fracturing …