This paper presents a thorough examination of rock physics, discipline central to integrating geophysical observation and the underlying physical properties of geological materials. The research addresses systematically how seismic waves interact with rocks, providing valuable information about subsurface lithology, fluid saturation, pore pressure, and stress regime. The approach brings together theoretical models, empirical correlations, and sophisticated computational methods. We use known rock physics models, such as effective medium theories and Gassmann's fluid substitution, together with a detailed consideration of Petrophysical data from well logs and core measurements to comprehend the main controls on seismic properties like porosity, mineralogy, fluid type, and effective stress. Seismic response predictions and estimation of the effect of different parameters are made using forward modeling and sensitivity analyses, with special focus on the diagnostic capability of Poisson's ratio and VP/VS ratio for\ fracture and fluid detection. The paper also discusses micro-scale observations using Digital Rock Physics (DRP), explaining the significant role of pore structure on macroscopic elastic properties. The revolutionary contribution of machine learning and artificial intelligence is also emphasized, showing their effectiveness in predicting petrophysical properties and lithofacies classifying from seismic attributes. While recognizing the progress, the topic covers the existing challenges, such as uncertainty quantification, complex anisotropy, and the requirement for strong time-lapse and geomechanical integration. Finally, this book emphasizes the critical importance of rock physics in minimizing subsurface uncertainty and maximizing decision-making for a wide range of applications in energy, environmental science, and engineering.
Jehanzeb Khan (Mon,) studied this question.