... public borehole diameter diameter y-axis prediction saudi aramco machine learning regressor correlation coefficient porosity aape brownlee xgboost regressor International Geomechanics Symposium IGS-2022-77 Prediction of Borehole Caliper Log Using Machine Learning for Multi-Stage Frac...

... upstream oil & gas artificial intelligence directional drilling drilling operation well logging public aape log analysis machine learning dtsm real-time prediction predicted sonic log surface drilling parameter rmse saudi aramco reservoir characterization slowness algorithm...

... represents the optimum parameters for the RF developed model that were obtained during the RP parameters testing phase for developing the model. The analysis showed that the RF model with the optimized parameters predicted the Vs with an accuracy R higher than 0.91 with an AAPE of 1.1 % during the model...

..., the average absolute percentage error (AAPE) ranged from 0.97% to 3.07% for training and testing respectively. The developed models were validated using another dataset. The models predicted the pore pressure gradient for the validation dataset with high accuracy (R of 0.99, RMSE around 0.01 and AAPE around...