Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 2 of 2 for “"Lithological clustering"”.
-
Deep Neural Networks for Rate of Penetration Prediction: A Subsurface-Centric Approach Using Well Logs in the Volve Oil Field
… = 4.96, MSE = 81.56) likely due to variations in lithological complexity outside the reservoir. To address this, unsupervised learning was employed to characterize lithological heterogeneity using k-means clustering, validated via silhouette scores, elbow method, t-SNE, and PCA. Additional …
-
Deep Neural Networks for Rate of Penetration Prediction: A Subsurface-Centric Approach Using Well Logs in the Volve Oil Field
… = 4.96, MSE = 81.56) likely due to variations in lithological complexity outside the reservoir. To address this, unsupervised learning was employed to characterize lithological heterogeneity using k-means clustering, validated via silhouette scores, elbow method, t-SNE, and PCA. Additional …