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Lithology identification using well logs: A method by integrating artificial neural networks and sedimentary patterns
Effective identification of lithology using well logs is one of the most important steps for
reservoir characterization. A lot of methods have been developed to identify lithology …
reservoir characterization. A lot of methods have been developed to identify lithology …
Evaluation and development of a predictive model for geophysical well log data analysis and reservoir characterization: Machine learning applications to lithology …
This work critically evaluated the applicability of machine learning methodology applied to
automated well log creation towards reliable lithology prediction and subsequent reservoir …
automated well log creation towards reliable lithology prediction and subsequent reservoir …
Production prediction at ultra-high water cut stage via Recurrent Neural Network
W Hongliang, MU Longxin, SHI Fugeng… - Petroleum Exploration …, 2020 - Elsevier
A deep learning method for predicting oil field production at ultra-high water cut stage from
the existing oil field production data was presented, and the experimental verification and …
the existing oil field production data was presented, and the experimental verification and …
A comparison of deep machine learning and Monte Carlo methods for facies classification from seismic data
Among the large variety of mathematical and computational methods for estimating reservoir
properties such as facies and petrophysical variables from geophysical data, deep machine …
properties such as facies and petrophysical variables from geophysical data, deep machine …
When petrophysics meets big data: What can machine do?
Petrophysics is a pivotal discipline that bridges engineering and geosciences for reservoir
characterization and development. New sensor technologies have enabled real-time …
characterization and development. New sensor technologies have enabled real-time …
Insights into the application of machine learning in reservoir engineering: current developments and future trends
H Wang, S Chen - Energies, 2023 - mdpi.com
In the past few decades, the machine learning (or data-driven) approach has been broadly
adopted as an alternative to scientific discovery, resulting in many opportunities and …
adopted as an alternative to scientific discovery, resulting in many opportunities and …
Automated well-log processing and lithology classification by identifying optimal features through unsupervised and supervised machine-learning algorithms
The application of specialized machine learning (ML) in petroleum engineering and
geoscience is increasingly gaining attention in the development of rapid and efficient …
geoscience is increasingly gaining attention in the development of rapid and efficient …
Well-logging prediction based on hybrid neural network model
L Wu, Z Dong, W Li, C **g, B Qu - Energies, 2021 - mdpi.com
Well-logging is an important formation characterization and resource evaluation method in
oil and gas exploration and development. However, there has been a shortage of well …
oil and gas exploration and development. However, there has been a shortage of well …
Deep-learning-based automated stratigraphic correlation
Stratigraphic correlation is essential in field evaluation as it provides the necessary tops to
compartmentalize the reservoir. It further contributes to other parts of the field development …
compartmentalize the reservoir. It further contributes to other parts of the field development …
Prediction of gas hydrate saturation using machine learning and optimal set of well-logs
Resistivity and acoustic logs are widely used to estimate gas hydrate saturation in various
sedimentary systems using one of the two popular methods ((1) acoustic velocity and (2) …
sedimentary systems using one of the two popular methods ((1) acoustic velocity and (2) …