Well logs data are the most widely used data to evaluate subsurface rocks, their petrophysical properties include porosity, permeability and fluid saturation. They are essential for the hydrocarbon reserves estimations and perforation zones determination for production purposes and fields development. Well logging operations of the targeted reservoirs could not be done in NO-10 Well, Noor Oilfield, Southern Iraq due to some problems related to the well condition. The gamma-ray and sonic logs were the only recorded logs, while neutron, density and deep resistivity logs are missed. The missing neutron, density and deep resistivity logs of the Early Cretaceous Nahr Umr Sandstone and the Late Cretaceous Mishrif formations of the well NO-10 were produced and compared together using the Artificial Neural Network ANN in Petrel software. The results show that the total correlation of the ANN Nahr Umr model for the neutron, density and deep resistivity logs are 0.81, 0.49 and 0.51 respectively. Interestingly, the ANN Mishrif Formation model recorded 0.88, 0.92 and 0.81 for neutron, density and resistivity logs respectively. The results show excellent relationships between the original and the predicted logs in the Mishrif model, unlike the Nahr Umr model expect in ANN of the neutron log. It was expected that the total relationships are low in Nahr Umr due to the lithology variation that includes interbedded consolidated and unconsolidated sandstone interbedded with the shale. It is also observed that the gamma log shows low values and the caliper logs is smoothed in the Mishrif. In contrast, the Nahr Umr sandstone logs show that many washouts have occurred. Therefore, logs' responses highly possible to be affected in the Nahr Umr Formation which leads to a decreasing in the coefficient of determinations.