Open Access
Issue |
Sci. Tech. Energ. Transition
Volume 77, 2022
|
|
---|---|---|
Article Number | 21 | |
Number of page(s) | 6 | |
DOI | https://doi.org/10.2516/stet/2022020 | |
Published online | 28 November 2022 |
- Aghli G., Moussavi-Harami R., Mohammadian R. (2020) Reservoir heterogeneity and fracture parameter determination using electrical image logs and petrophysical data (a case study, carbonate Asmari Formation, Zagros Basin, SW Iran), Pet. Sci. 17, 1, 51–69. [CrossRef] [Google Scholar]
- Andreasen A. (2021) Optimisation of carbon capture from flue gas from a Waste-to-Energy plant using surrogate modelling and global optimisation, Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles 76, 55. [CrossRef] [Google Scholar]
- Bihani A., Daigle H., Santos J.E., Landry C., Prodanović M., Milliken K. (2022) MudrockNet: Semantic segmentation of mudrock SEM images through deep learning, Comput. Geosci. 158, 104952. [CrossRef] [Google Scholar]
- El Ouahed A., Tiab D., Mazouzi A. (2005) Application of artificial intelligence to characterize naturally fractured reservoirs, in: Canadian International Petroleum Conference, June 7–9, Calgary. [Google Scholar]
- Fornero S.A., Marins G.M., Lobo J.T., Freire A.F.M., de Lima E.F. (2019) Characterization of subaerial volcanic facies using acoustic image logs: Lithofacies and log-facies of a lava-flow deposit in the Brazilian pre-salt, deepwater of Santos Basin, Mar. Pet. Geol. 99, 156–174. [CrossRef] [Google Scholar]
- Ghiat I., Al-Ansari T. (2021) A review of carbon capture and utilisation as a CO2 abatement opportunity within the EWF nexus, J. CO2 Util. 45, 101432. [Google Scholar]
- Hassall J.K., Ferraris P., Al-Raisi M., Hurley N.F., Boyd A., Allen D.F. (2004) Comparison of permeability predictors from NMR, formation image and other logs in a carbonate reservoir, in: Abdu Dhabi International Conference and Exhibition, October 10–13, Abu Dhabi, United Arab Emirates. [Google Scholar]
- Li T., Wang R., Wang Z., Zhao M., Li L. (2018) Prediction of fracture density using genetic algorithm support vector machine based on acoustic logging data, Geophysics 83, 2, 49–60. [Google Scholar]
- Rezig D. (2019) Fracture aperture estimation using electrical image logs (FMI) and acoustic (SS), in: Fifth EAGE/AAPG Tight Reservoirs Workshop, European Association of Geoscientists & Engineers, pp. 1–6. [Google Scholar]
- Tian X., Daigle H. (2018) Machine-learning-based object detection in images for reservoir characterization: A case study of fracture detection in shales, Lead. Edge 37, 6, 435–442. [CrossRef] [Google Scholar]
- Tursunov O., Kustov L., Kustov A. (2017) A brief review of carbon dioxide hydrogenation to methanol over copper and iron based catalysts, Oil Gas Sci. Technol. – Rev IFP Energies nouvelles 72, 5, 9. [CrossRef] [Google Scholar]
- Valentín M.B., Bom C.R., Coelho J.M., Correia M.D., Márcio P., Marcelo P., Faria E.L. (2019) A deep residual convolutional neural network for automatic lithological facies identification in Brazilian pre-salt oilfield wellbore image logs, J. Petrol. Sci. Eng. 179, 474–503. [CrossRef] [Google Scholar]
- Vidal J., Genter A., Schmittbuhl J. (2016) Pre-and post-stimulation characterization of geothermal well GRT-1, Rittershoffen, France: Insights from acoustic image logs of hard fractured rock, Geophys. J. Int. 206, 2, 845–860. [CrossRef] [Google Scholar]
- Wang M., Fan Z., Zhao L., Xing G., Zhao W., Tan C. (2020) Productivity analysis for a horizontal well with multiple reorientation fractures in an anisotropic reservoir, Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles 75, 80, 17. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.