[HTML][HTML] Key aspects of underground hydrogen storage in depleted hydrocarbon reservoirs and saline aquifers: A fundamental review and understanding
RA Sadkhan, WJ Al-Mudhafar - Energy Geoscience, 2024 - Elsevier
Underground hydrogen storage is critical for renewable energy integration and
sustainability. Saline aquifers and depleted oil and gas reservoirs represent viable large …
sustainability. Saline aquifers and depleted oil and gas reservoirs represent viable large …
Prediction of shale-gas production at Duvernay formation using deep-learning algorithm
Decline–curve analysis (DCA) is an easy and fast empirical regression method for predicting
future well production. However, applying DCA to shale–gas wells is limited by long …
future well production. However, applying DCA to shale–gas wells is limited by long …
Efficient assessment of reservoir uncertainty using distance-based clustering: a review
This paper presents a review of 71 research papers related to a distance-based clustering
(DBC) technique for efficiently assessing reservoir uncertainty. The key to DBC is to select a …
(DBC) technique for efficiently assessing reservoir uncertainty. The key to DBC is to select a …
Production forecasting in shale reservoirs through conventional DCA and machine/deep learning methods
Predicting EUR in unconventional tight-shale reservoirs with prolonged transient behavior is
a challenging task. Most methods used in predicting such long-term behavior have shown …
a challenging task. Most methods used in predicting such long-term behavior have shown …
Techniques for fast screening of 3D heterogeneous shale barrier configurations and their impacts on SAGD chamber development
C Gao, JY Leung - SPE Journal, 2021 - onepetro.org
The steam-assisted gravity drainage (SAGD) recovery process is strongly impacted by the
spatial distributions of heterogeneous shale barriers. Though detailed compositional flow …
spatial distributions of heterogeneous shale barriers. Though detailed compositional flow …
Geological model sampling using PCA-assisted support vector machine for reliable channel reservoir characterization
History matching is a crucial procedure for predicting reservoir performances and making
decisions. However, it is difficult due to uncertainties of initial reservoir models. Therefore, it …
decisions. However, it is difficult due to uncertainties of initial reservoir models. Therefore, it …
Uncertainty quantification of channel reservoirs assisted by cluster analysis and deep convolutional generative adversarial networks
B Kang, J Choe - Journal of Petroleum Science and Engineering, 2020 - Elsevier
Reservoir characterization is to find reservoir properties of interest by combining available
geological information. In channel reservoirs, flow responses are very sensitive depending …
geological information. In channel reservoirs, flow responses are very sensitive depending …
Feature extraction using a deep learning algorithm for uncertainty quantification of channelized reservoirs
Reservoir models are generated by geostatistics using available static data. However, there
is inherent uncertainty in the reservoir models due to limited information. A number of …
is inherent uncertainty in the reservoir models due to limited information. A number of …
Recursive update of channel information for reliable history matching of channel reservoirs using EnKF with DCT
Abstract Ensemble Kalman filter (EnKF) is one of the promising reservoir characterization
schemes for history matching. It has been widely researched due to its excellence in …
schemes for history matching. It has been widely researched due to its excellence in …
Construction of prior models for ES-MDA by a deep neural network with a stacked autoencoder for predicting reservoir production
The design of prior models has continued to receive research attention because of their
importance for ensemble-based methods. There are two approaches to ensemble design …
importance for ensemble-based methods. There are two approaches to ensemble design …