Synthetic well logs generation via Recurrent Neural Networks

D Zhang, C Yuntian, M ** - Petroleum Exploration and Development, 2018 - Elsevier
To supplement missing logging information without increasing economic cost, a machine
learning method to generate synthetic well logs from the existing log data was presented …

[HTML][HTML] Shear wave velocity prediction: A review of recent progress and future opportunities

JO Olutoki, J Zhao, NA Siddiqui, M Elsaadany… - Energy …, 2024 - Elsevier
Shear logs, also known as shear velocity logs, are used for various types of seismic
analysis, such as determining the relationship between amplitude variation with offset (AVO) …

Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms

M Rajabi, O Hazbeh, S Davoodi, DA Wood… - Journal of Petroleum …, 2023 - Springer
Shear wave velocity (VS) data from sedimentary rock sequences is a prerequisite for
implementing most mathematical models of petroleum engineering geomechanics …

Physics-constrained deep learning of geomechanical logs

Y Chen, D Zhang - IEEE Transactions on geoscience and …, 2020 - ieeexplore.ieee.org
Geomechanical logs are of ultimate importance for subsurface description and evaluation,
as well as for the exploration of underground resources, such as oil and gas, groundwater …

Multi‐Scale Geomechanical Modelling of Unconventional Shale Gas: The Implication on Assisting Geophysics–Geology–Engineering Integration

Y **ao, C Liang, D Zhu, C Zou, J Yan… - International Journal of …, 2024 - Wiley Online Library
In the development of unconventional shale play, simulation of the performance for wells
needs to incorporate sufficient complexity in geology to take fully into account the …

Remaining life estimation of used components in consumer products: Life cycle data analysis by Weibull and artificial neural networks

MI Mazhar, S Kara, H Kaebernick - Journal of operations management, 2007 - Elsevier
Environmental awareness and legislative pressures have made manufacturers responsible
for the take-back and end-of-life treatment of their products. To competitively exploit these …

Prediction of shear wave velocity from petrophysical data utilizing intelligent systems: An example from a sandstone reservoir of Carnarvon Basin, Australia

MR Rezaee, AK Ilkhchi, A Barabadi - Journal of Petroleum Science and …, 2007 - Elsevier
Shear wave velocity (Vs) associated with compressional wave velocity (Vp) can provide
accurate data for geophysical study of a reservoir. These so called petroacoustic studies …

Development of a fuzzy model to predict flyrock in surface mining

M Rezaei, M Monjezi, AY Varjani - Safety science, 2011 - Elsevier
Flyrock is one of the most hazardous side effects of blasting operation in surface mining.
This phenomenon can be considered as the main cause of casualties and damages …

S-wave velocity inversion and prediction using a deep hybrid neural network

J Wang, J Cao, S Zhao, Q Qi - Science China Earth Sciences, 2022 - Springer
The S-wave velocity is a critical petrophysical parameter in reservoir description, prestack
seismic inversion, and geomechanical analysis. However, obtaining the S-wave velocity …

Intelligent approaches for prediction of compressional, shear and Stoneley wave velocities from conventional well log data: A case study from the Sarvak carbonate …

M Rajabi, B Bohloli, EG Ahangar - Computers & Geosciences, 2010 - Elsevier
Compressional, shear and Stoneley wave velocities (Vp, Vs and Vst, respectively) are
important reservoir characteristics that have many applications in petrophysical, geophysical …