Constraining Elastic Rock Properties in A CO_2 Enhanced Oil Recovery Reservoir Using Sonic Log Data

摘要

The main objective of this paper is to investigate the geomechanical property changes taking place with CO_2 injection in Delhi Field. Sonic velocity has been cross plotted with clay content and density logs, and the correlation has been used to create synthetic sonic logs based on neural network that provides an alternative way to extrapolate the rock property changes to any well location in the field where sonic log data is not available. Nevertheless, neural network cannot be applied to predict the sonic log after the CO_2 injection as the sonic data is not yet available after CO_2 injection. Hence, the Eberhart-Phillips correlation was utilized to calculate the velocity changes caused by pore pressure changes that the pressure data from several wells in the field is available. While Eberhart-Phillips correlation doesn't take into account the CO_2 saturation effect on the compressional velocity, the Gassmann equation has been applied to calculate the effects of CO_2 saturation, and the result can be utilized to linearly input into the Eberhart-Phillips correlation to couple the effects of CO_2 saturation and effective stress. And then the 3D Young's modulus cube, Poisson's ratio cube, unconfined compressive strength(UCS) in various effective stress scenarios have been evaluated to predict the geomechanical risk with the associated changes.