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Quantitative Interpretation of Oil-Base Mud Microresistivity Imager Via Artificial Neural Networks
First Section
1. OBM Imager and Quantitative Interpretation (11:50)
2. NN As Forward Model Proxy in Inversion (9:34)
3. Metrics for Depth Matching QC (7:34)
4. Conclusions and Other Applications (8:39)
2. NN As Forward Model Proxy in Inversion
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