Deep convolutional generative adversarial networks for modeling complex hydrological structures in Monte-Carlo simulation
Abstract Characterization of complex subsurface structures is challenging due to the
demand to preserve geological realism of the training images in earth and environmental …
demand to preserve geological realism of the training images in earth and environmental …
Characterization of subsurface hydrogeological structures with convolutional conditional neural processes on limited training data
One of the main issues in the application of statistical‐learning‐based methods to the
characterization of hydrological phenomena is the complex parameterization of the high …
characterization of hydrological phenomena is the complex parameterization of the high …
Multiple-point geostatistical simulation based on conditional conduction probability
Multiple-point geostatistical (MPS) simulation can enhance extraction and synthesis of
various information in earth and environmental sciences. In particular, it is able to …
various information in earth and environmental sciences. In particular, it is able to …
[HTML][HTML] Terahertz for the detection of the oil bearing characteristics of shale
H Zhan, Y Yang, Y Zhang, X Miao, K Zhao, W Yue - Energy Reports, 2021 - Elsevier
Studying the trace organic matter (OM) in shale is of great significance to develop
exploration plans for shale oil and gas exploration. Due to the low OM content, currently …
exploration plans for shale oil and gas exploration. Due to the low OM content, currently …
Geological Uncertainty Quantification
Our knowledge from underground reservoirs is not complete and is limited to some sparse
core and log data, seismic data, geological interpretations, etc. This limited knowledge leads …
core and log data, seismic data, geological interpretations, etc. This limited knowledge leads …
MPs realization selection with an innovative LSTM tool
A Azamifard, M Ahmadi, F Rashidi, M Pourfard… - Journal of Applied …, 2020 - Elsevier
Multiple point statistics (MPS) methods are good tools to recreate the spatial heterogeneity
of permeability in porous media. On the other hand, a reliable forecast of reservoir …
of permeability in porous media. On the other hand, a reliable forecast of reservoir …
QuiltEdge: Novel geostatistical workflow for heterogeneous reservoirs with an innovative combination of multi-variable image quilting and edge property concept to …
A Azamifard, M Ahmadi, F Rashidi, M Pourfard… - Journal of Petroleum …, 2020 - Elsevier
Detailed and accurate techniques which plays a vital role in providing more reliable
predictions of reservoir performance are needed for spatial modeling of reservoirs with …
predictions of reservoir performance are needed for spatial modeling of reservoirs with …
Insights of new-generation reservoir property modeling (MPS methods) in assessing the reservoir performance for different recovery methods
A Azamifard, M Ahmadi, F Rashidi, M Pourfard… - Arabian Journal of …, 2020 - Springer
Usage of an advanced geostatistical method for reservoir characterization results in more
reliable insights of reservoir performance. Multiple-point statistic (MPS) methods which …
reliable insights of reservoir performance. Multiple-point statistic (MPS) methods which …