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- W4387231772 abstract "Abstract We created a seismic feature recognition system based on Artificial Intelligence Machine learning (AIML) and evaluated its effectiveness and precision in comparison to conventional seismic interpretation methods. Findings indicate that performance is influenced by both the generalization of seismic features and the quality of the input data sets. Machines are more effective than conventional methods at identifying seismic characteristics, but they require transfer learning to keep up with new seismic features, necessitating the multi-model strategy covered in this study." @default.
- W4387231772 created "2023-10-02" @default.
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- W4387231772 date "2023-10-02" @default.
- W4387231772 modified "2023-10-16" @default.
- W4387231772 title "AIML Provides the Efficiency and Precision in our Subsurface Geological Understanding" @default.
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- W4387231772 doi "https://doi.org/10.2118/216277-ms" @default.
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