*4.3. Evaluation of the Developed Machine Learning Models*

After training, the developed machine learning models were then tested using the remaining data collected from the same training sandstone formation in Well-A and then validated using 38 data points (unseen data) collected from a sandstone formation in Well-B.

Uncertainty quantification is at the heart of decision making, especially in subsurface applications. Uncertainty about the geological structures, rocks, and fluids is because of the lack of access to the subsurface geological medium [57,58]. The uncertainty in the prediction results of all machine learning models developed in this study was directly controlled by the uncertainty on the well log data used

to develop these models which were highly controlled by the depth of investigation and vertical resolution of every logging tool.

### **5. Results and Discussion**
