Rock typing is a vital step in oil and gas reservoir development to achieve predictions of hydrocarbon reserves, recovery, and underground storage capacity for CO2 or hydrogen. To address inaccurate initial hydrocarbon in-place prediction and improper rock property distribution on a reservoir model, a recent rock typing method, pore geometry and structure (PGS), has revealed a more accurate prediction on connate water saturation and better grouping of capillary pressure. However, the current state still needs physical interpretations of the PGS rock typing method. We have compiled thousands of experimentally measured hydraulic properties, such as permeability k within 12 orders of magnitude, porosity phi up to 0.9, specific surface area S-S within 4 orders of magnitude, and pore size R ranges around 3 orders of magnitude. We conduct the first-ever holistic physical interpretations of the PGS rock typing method using gathered data combined with analytical theory from the Kozeny-Carman equation. Surprisingly, our physics-inspired data-driven study reveals advanced findings on PGS rock typing. These include (i) why the PGS method prevails over the hydraulic flow unit rock typing, (ii) explanations to distinguish between causality and indirect relationships among hydraulic properties, rock type number, and electrical resistivity, (iii) a proposed novel method: permeability prediction from the resistivity and rock type number relationship, and (iv) a suggestion and criticism on how to avoid a recursive prediction on permeability.