Uncertainty Quantification of Young's Modulus on Core Scale: A Bayesian Analysis on a Comprehensive Geomechanical Model

ABSTRACT The ability to accurately measure the static Young's modulus is crucial for understanding subsurface storage reservoirs. However, obtaining this data can be difficult and costly. Much previous research focused on the impact of one or two factors on geomechanical properties at a single scale, but a more comprehensive understanding is needed. This study examines the impact of six rock properties - porosity, clay content, permeability, sample size, and the framework grain content to cement content (FGC/CC) ratio on Young's modulus in samples from five rock facies. The goal is to systematically quantify the effects of these secondary rock properties on a primary geomechanical property in a range of sandstones at the core scale. This study suggests that the pore abundance and the relative amount of framework grains and cements play competing roles in rock's elastic behavior. In addition, the surrogate model yields the minimum uncertainty and reflects nonlinear trends between Young's modulus and secondary rock properties. Overall, we represented a data-driven approach to quantify the uncertainty of Young's modulus of rocks using cost-effective experimental measurements. INTRODUCTION Understanding and minimizing uncertainties in geomechanical properties can lead to successful geological investigations and complex engineering projects and prevent accidents such as reservoir leakage and wellbore collapse. Elastic modulus is a primary property (among mechanical properties), but data are often unavailable and can be costly to measure. Alternative to direct measurements, estimating elastic modulus is more effective if the roles of secondary properties, such as geological, hydrological, and petrophysical properties, can be quantified. Previous studies often evaluate the correlation between primary and secondary properties to predict primary geomechanical properties (Han et al., 1986; Chang et al., 2006). However, the correlations between primary and secondary properties are not comprehensive, and the uncertainty associated with predictive primary geomechanical properties is generally unknown. Therefore, a framework for the Bayesian assessment of a comprehensive geomechanical model with constrained uncertainty has been developed to address this challenge. The comprehensive geomechanical model is capable of predicting elastic modulus based on main secondary properties.