Development of machine learning methodology for polymer gels screening for injection wells

Results show that logistic classification models and their variants correctly predict the proper gel technology in more than 85% of projects in the training and validation samples with a minimum AUC of 0.9375. We also used a prediction profiler to visually monitor performances of the classifiers and certain tendencies were identified by the investigation of the mispredicted projects. The novelty of the new methodology is its capability to predict the most applicable gel technology for undiagnosed injection wells.