Normalization is an important method for data pre-processing, especially for machine learning. Why do we need normalization? Normalization may change the distribution of the feature vector data set and the distances among observation points. Additionally, it may accelerate convergence of deep learning algorithms . As another example, our AxHeat product uses normalization for the RF heating of reservoirs, and improves algorithm stability after we have applied it to the water saturation.