How can NMR measurements improve rock physics predictions?

This study shows that Nuclear Magnetic Resonance (NMR) measurements can successfully be used to predict the accurate input parameters (porosity, macro-porosity, micro-porosity, permeability, capillary pressure, aspect ratio, crack porosity, critical frequency, etc.) in rock physics modeling.  Rock physics models help us understand and quantify the different lithologies, changing pore fluids, heterogeneous of pore types and their distribution, and elastic properties in general.  Additionally, rock physics models provide a solid basis for quantitative seismic interpretation by minimizing interpretation risk. During the last decade applications and challenges for rock physics modeling have changed dramatically: whereas the underlying objective is to select and optimize input parameters for a sensible rock physics model, the important breakthroughs in rock physics did not come from integrating physics or mathematical axioms but by calibrating elastic models to physical rock properties. However, the importance of selecting the proper input parameters to steer rock physics models has been emphasized less. Obviously, if input parameters to a rock physics model are wrong then resultant predictions will be erroneous regardless of using a “better, more sophisticated” model. Few inputs in rock physics modeling are treated as free parameters (e.g. aspect ratio, crack porosity, micro porosity, critical frequency, etc.). If a model includes free (i.e., unconstrained) parameters, it will always be possible to model elastic properties to just fit the model parameters.  NMR is a useful tool to measure in-situ reservoir properties. We advocate that NMR data should be integrated with rock physics models to describe the fluid-related dispersion, water weakening effect, and fluid viscosity effects in reservoir rocks. Furthermore, NMR measurements can be used to generate reliable reservoir depth trends to address porosity reduction and mechanical strength of reservoir rocks.