Drained pore modulus determination using digital rock technology

Abstract

Geomechanics helps us understand the life-cycle of a hydrocarbon reservoir and, in turn, impacts geophysical monitoring programs. A common geomechanical problem is to predict reservoir compaction or zones of abnormal pore pressure. These predictions mostly use simple empirical relations, but recently, the use of rock deformation models based on static poroelasticity are becoming the norm. These models require accurate values for the poroelastic parameters. We present a digital rock workflow to determine these poroelastic parameters which are difficult to extract from well-log or laboratory measurements. The drained pore modulus is determinant in the compaction problem. This modulus represents the ratio of pore volume change to confining pressure when the fluid pressure is constant. In laboratory experiments, bulk volume changes are accurately measured by sensors attached to the outer surface of the rock sample. In contrast, pore volume changes are notoriously difficult to measure because these changes need to quantify the pore boundary deformation. Hence, accurate measures of the drained pore modulus are challenging. We simulate static deformation experiments at the pore-scale utilizing digital rock images. We model an Ottawa F-42 sand pack obtained from X-ray micro-tomographic images. We stack two-dimensional micro-CT images to generate a three-dimensional F-42 sand pack sample. We extract a sub-volume from this sample for numerical simulation. We first segment the cropped sample consists of grains and pore spaces and then use the segmentation to generate a volumetric mesh. We compute the elastic, linear momentum balance in the structural domain (grains) and solve the system using the commercial software package ABAQUS. The network of grains (solid phase) is assumed elastic, isotropic, and homogeneous. We calculate the change in pore volume using a new post-processing algorithm, which allows us to compute the local changes in pore volume due to the applied load. This process yields an accurate drained pore modulus. We then use an alternative estimate of the drained pore modulus. We exploit its relation to the drained bulk modulus and the solid phase bulk modulus (i.e., Biot’s coefficient) using the digital rock workflow. Finally, we compare the drained pore modulus values obtained from these two independent analyses and find reasonable agreement.