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- W4317201188 abstract "Summary Utilizing a quantum machine learning method for mapping interwell saturation based on well logs and electromagnetic tomography provides a data-driven approach to deep diagnostics of the reservoir, honoring both geology as well as reservoir dynamics. The 4IR framework has exhibited a strong estimation quality of the water saturation profile for a realistic reservoir box model via training the network with well-log data in the near-wellbore zone. This new approach can be readily supplemented with new data to improve the accuracy of the predicted saturation maps. The 4IR framework is flexible enough to be adapted to different geological structures and petrophysical relationships and the results from this reservoir box model study exhibited great potential in a broader application of the technique for interwell saturation mapping." @default.
- W4317201188 created "2023-01-18" @default.
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- W4317201188 date "2022-01-01" @default.
- W4317201188 modified "2023-09-27" @default.
- W4317201188 title "Enhancing Interwell Saturation Mapping via an Innovative Quantum Machine Learning Framework" @default.
- W4317201188 doi "https://doi.org/10.3997/2214-4609.202270076" @default.
- W4317201188 hasPublicationYear "2022" @default.
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