Fluid discrimination based on inclusion-based method for tight sandstone reservoirs
P Wang, Y Cui, J Liu - Surveys in Geophysics, 2022 - Springer
Fluid discrimination is challenging for reservoir prediction, especially for tight sandstones
with special petrophysical properties. In this paper, we first review the effective medium …
with special petrophysical properties. In this paper, we first review the effective medium …
Lithological unit classification based on geological knowledge-guided deep learning framework for optical stereo mapping satellite imagery
Lithological unit classification (LUC) refers to the classification of different types of rocks
within an area, and it has been widely used in many fields, such as resource surveys and …
within an area, and it has been widely used in many fields, such as resource surveys and …
Deep carbonate reservoir characterisation using multi-seismic attributes via machine learning with physical constraints
Seismic characterisation of deep carbonate reservoirs is of considerable interest for
reservoir distribution prediction, reservoir quality evaluation and reservoir structure …
reservoir distribution prediction, reservoir quality evaluation and reservoir structure …
Improving uncertainty analysis in well log classification by machine learning with a scaling algorithm
R Feng - Journal of Petroleum Science and Engineering, 2021 - Elsevier
Uncertainty is an important indicator that can provide the confidence in the predictions.
However, most machine learning methods in classification problems are incapable of …
However, most machine learning methods in classification problems are incapable of …
Lithofacies classification of a geothermal reservoir in Denmark and its facies-dependent porosity estimation from seismic inversion
Abstract Characterization of geothermal reservoirs is an important step for exploration and
development of geothermal energy, which is reliable and sustainable for the future. Based …
development of geothermal energy, which is reliable and sustainable for the future. Based …
Variational inference in Bayesian neural network for well-log prediction
We have introduced a Bayesian neural network in quantitative log prediction studies with the
goal of improving the petrophysical characterization and quantifying the uncertainty of model …
goal of improving the petrophysical characterization and quantifying the uncertainty of model …
Joint use of multiseismic information for lithofacies prediction via supervised convolutional neural networks
Lithology prediction from seismic data is of great significance for sweet-spot detection,
reservoir structure delineation, and geologic model building, hence it is important in …
reservoir structure delineation, and geologic model building, hence it is important in …
An improved method for lithology identification based on a hidden Markov model and random forests
Subsurface petrophysical properties usually differ between different reservoirs, which affects
lithology identification, especially for unconventional reservoirs. Thus, the lithology …
lithology identification, especially for unconventional reservoirs. Thus, the lithology …
Estimation of reservoir porosity based on seismic inversion results using deep learning methods
R Feng - Journal of Natural Gas Science and Engineering, 2020 - Elsevier
Location limitation of logged wells restricts the porosity estimation across the whole reservoir
target, whereas seismic data are always collected to cover larger areas. In this paper …
target, whereas seismic data are always collected to cover larger areas. In this paper …
Seismic inversion with deep learning: A proposal for litho-type classification
SL Pintea, S Sharma, FC Vossepoel… - Computational …, 2021 - Springer
This article investigates bypassing the inversion steps involved in a standard litho-type
classification pipeline and performing the litho-type classification directly from imaged …
classification pipeline and performing the litho-type classification directly from imaged …