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The problem of theoretical prediction of the elastic stiffness parameter [Formula: see text] is important, as well as proper establishment of its theoretical bounds, which is extremely useful in the reliable [Formula: see text] estimation. We revise a formula for the lower bound [Formula: see text], empirically derived by F. Yan with coauthors, based on their empirical inequality between two Poisson’s ratios in a transversely isotropic elastic medium; i.e., [Formula: see text]. In doing this, we consider a theoretical counterexample derived on theoretical grounds by J. Sarout leading to the opposite inequality [Formula: see text]. Our analysis on shale anisotropy (using published data on various shale samples) proves both inequalities to be true. Therefore, we can divide shale data into two groups: 1 and 2; i.e., group 1 we define by the inequality [Formula: see text], and group 2 by [Formula: see text]. In the framework of the linear slip (LS) model, we found another restriction on two Poisson’s ratios [Formula: see text], which must be satisfied in the LS model. In addition, we found that the theoretical formula for the [Formula: see text] in the LS model and the bound [Formula: see text] should be equal: [Formula: see text]. Also, we found that [Formula: see text] depends on the normal fracture compliance [Formula: see text]. We postulate that there is a critical compliance [Formula: see text] predicted by the LS model that marks the transition between two inequalities of Poisson’s ratios: [Formula: see text], and [Formula: see text]. These inequalities become a part of a broader interpretation, in which the compliance [Formula: see text] acts as a transitional intermediate response (i.e., [Formula: see text]) between the two shale groups 1 and 2. Each shale group (i.e., [Formula: see text], and [Formula: see text]) is assigned to different [Formula: see text] (i.e., [Formula: see text] and [Formula: see text]), which imply differentiation of rock properties in two groups, such as different fluid saturation, as an example.
The problem of theoretical prediction of the elastic stiffness parameter [Formula: see text] is important, as well as proper establishment of its theoretical bounds, which is extremely useful in the reliable [Formula: see text] estimation. We revise a formula for the lower bound [Formula: see text], empirically derived by F. Yan with coauthors, based on their empirical inequality between two Poisson’s ratios in a transversely isotropic elastic medium; i.e., [Formula: see text]. In doing this, we consider a theoretical counterexample derived on theoretical grounds by J. Sarout leading to the opposite inequality [Formula: see text]. Our analysis on shale anisotropy (using published data on various shale samples) proves both inequalities to be true. Therefore, we can divide shale data into two groups: 1 and 2; i.e., group 1 we define by the inequality [Formula: see text], and group 2 by [Formula: see text]. In the framework of the linear slip (LS) model, we found another restriction on two Poisson’s ratios [Formula: see text], which must be satisfied in the LS model. In addition, we found that the theoretical formula for the [Formula: see text] in the LS model and the bound [Formula: see text] should be equal: [Formula: see text]. Also, we found that [Formula: see text] depends on the normal fracture compliance [Formula: see text]. We postulate that there is a critical compliance [Formula: see text] predicted by the LS model that marks the transition between two inequalities of Poisson’s ratios: [Formula: see text], and [Formula: see text]. These inequalities become a part of a broader interpretation, in which the compliance [Formula: see text] acts as a transitional intermediate response (i.e., [Formula: see text]) between the two shale groups 1 and 2. Each shale group (i.e., [Formula: see text], and [Formula: see text]) is assigned to different [Formula: see text] (i.e., [Formula: see text] and [Formula: see text]), which imply differentiation of rock properties in two groups, such as different fluid saturation, as an example.
Detecting vertical transversely isotropic (VTI) formations and quantifying the magnitude of anisotropy are fundamental for describing organic mudrocks. Methods used to estimate stiffness coefficients of VTI formations often provide discontinuous or spatially averaged results over depth intervals where formation layers are thinner than the receiver aperture of acoustic tools. We have developed an inversion-based method to estimate stiffness coefficients of VTI formations that are continuous over the examined depth interval and that are mitigated for spatial averaging effects. To estimate the coefficients, we use logs of frequency-dependent compressional, Stoneley, and quadrupole/flexural modes measured with wireline or logging-while-drilling (LWD) instruments in vertical wells penetrating horizontal layers. First, we calculate the axial sensitivity functions of borehole sonic modes to stiffness coefficients; next, we use the sensitivity functions to estimate the stiffness coefficients of VTI layers sequentially from frequency-dependent borehole sonic logs. Because sonic logs exhibit spatial averaging effects, we deaverage the logs by calculating layer-by-layer slownesses of formations prior to estimating stiffness coefficients. The method is verified with synthetic models of homogeneous and thinly bedded formations constructed from field examples of organic mudrocks. Results consist of layer-by-layer estimates of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]. We observe three sources of error in the estimated coefficients: (1) bias error originating from deaveraging the sonic logs prior to the sequential inversion, (2) error propagated during the sequential inversion, and (3) error associated with noisy slowness logs. We found that the relative bias and uncertainty of the estimated coefficients are largest for [Formula: see text] and [Formula: see text] because borehole modes exhibit low sensitivity to these two coefficients. The main advantage of our method is that it mitigates spatial averaging effects of sonic logs, while at the same time it detects the presence of anisotropic layers and yields continuous estimations of stiffness coefficients along the depth interval of interest.
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