Submicron size-scale mapping of carbonate effective elastic properties from FIB-SEM images and finite element method

Cheng, Hui; Zhu, Bo; Yuen, David A.; Shi, Yuanhao

doi:10.1007/s11430-015-0132-9

Cited by 1 publication

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“…Moreover, the same rock sample can be examined under varying testing conditions or mineral composition, which can be virtually varied [ 48 ]. Present numerical models employ calculation techniques to determine static [ 49 , 50 , 51 ] and dynamic moduli [ 52 ] mainly for reservoir rocks such as sandstones [ 53 , 54 ] and carbonates [ 55 , 56 ], but also for shales [ 57 ]. However, there is still a discrepancy between the achieved numerical estimates of mechanical properties derived from micro-CT images and laboratory data, where, regardless of the numerical approach, the simulated moduli are systematically higher [ 58 , 59 ].…”

Section: Introductionmentioning

confidence: 99%

Quantifying Rock Weakening Due to Decreasing Calcite Mineral Content by Numerical Simulations

2018

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The quantification of changes in geomechanical properties due to chemical reactions is of paramount importance for geological subsurface utilisation, since mineral dissolution generally reduces rock stiffness. In the present study, the effective elastic moduli of two digital rock samples, the Fontainebleau and Bentheim sandstones, are numerically determined based on micro-CT images. Reduction in rock stiffness due to the dissolution of 10% calcite cement by volume out of the pore network is quantified for three synthetic spatial calcite distributions (coating, partial filling and random) using representative sub-cubes derived from the digital rock samples. Due to the reduced calcite content, bulk and shear moduli decrease by 34% and 38% in maximum, respectively. Total porosity is clearly the dominant parameter, while spatial calcite distribution has a minor impact, except for a randomly chosen cement distribution within the pore network. Moreover, applying an initial stiffness reduced by 47% for the calcite cement results only in a slightly weaker mechanical behaviour. Using the quantitative approach introduced here substantially improves the accuracy of predictions in elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in porosity and mineral distribution.

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