Lithofacies successions from diverse depositional environments show distinctive patterns in various rock-physics planes (velocity-porosity, velocity-density and porosityclay). Four clear examples of decameter-scale lithofacies sequences are documented in this study: (1) Micocene fluvial deposits show an inverted-V pattern indicative of dispersed fabric, (2) a fining-upward sequence of mud-rich deep deposits shows a linear trend associated with laminated sand-clay mixtures, (3) sand-rich deposits show a pattern resulting from the scarcity of mixed lithofacies, and (4) a coarsening-upward sequence shows evidence of both dispersed and horizontally laminated mixed lithofacies, with predominating dispersed mixtures generated by bioturbation..It was observed that carbonate-cemented sandstones are extremely heterogeneous in the project deep-water study area. Those from the base of incisions are usually associated with lower shaliness, lower porosity and higher P-impedance, while from the top of flooding surfaces exhibit higher shaliness, higher porosity and lower P-impedance. One rock physics model that captures the observed impedance-porosity trend is the "stiff-sand model." For this model, the high-porosity end-member is unconsolidated sand whose initial porosity is a function of sorting and shaliness, while the low-porosity end-member is solid mineral. These two end points are joined with a Hashin-Shtrikman equation.A systematic variation of quartz:clay ratio from proximal to distal locations was observed in the study area even within a single facies. The quartz:clay ratio changes from [0.5:0.5] to [1:0] along the direction of flow, based on the trends of P-impedance vs. porosity as predicted by the rock model for uncemented sands. The results are in agreement with spill-and-fill sequence stratigraphic model in mini-basin setting. In addition, porosity at the distal location (~25 % to 35%) is higher than the porosity at the proximal location (~20 % to 23%). This trend is explained by a sequence stratigraphic model which predicts progressive increase in sorting by turbidity current along the flow, as well as, quantified by a rock model that heuristically accounts for sorting. The results can be applied to improve quantitative predication of sediment parameters from seismic impedance, away from well locations. Figure 1. Conceptual model illustrating the concomitant changes in porosity and elastic properties of clastic sediments. These textural effects have been documented by previous studies: e.g. , , , , , , , . Figure 2. Rock-physics template to evaluate the patterns of concomitant variations of porosity and elastic properties within clastic sequences. Porosity determined from density and neutron (in sands) logs, clay fraction determined from gamma ray and the difference between neutron and density porosities. Figure 6. Bivariate histograms of well-log P-wave velocity and porosity (PHID) from the four different clastic depositional sequences shown in Figure A-10. Q indicates the sand points (quartzose sand...