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Vertical transverse isotropy (VTI) will affect seismic inversion, but it is not possible to solve for the full set of anisotropic elastic parameters from amplitude variation with offset inversion because there exists an isotropic solution to every VTI problem. We can easily approximate the pseudoisotropic properties that result from the isotropic solution to the anisotropic problem for well-log data. We can then use these well-log properties to provide a low-frequency model for inversion and/or a framework for interpreting either absolute or relative inversion results. This, however, requires prior knowledge of the anisotropic properties, which are often unavailable or poorly constrained. If we ignore anisotropy and assume that the amplitude variations caused by VTI are going to be accounted for by effective wavelets, the inversion results would be in error: The impact of anisotropy is not merely a case of linear scaling of seismic amplitudes for any particular angle range. Ignoring VTI does not affect the prediction of acoustic impedance, but it does affect predictions of [Formula: see text] and density. For realistic values of anisotropy, these errors can be significant, such as predicting oil instead of brine. If the anisotropy of the rocks is known, then we can invert for the true vertical elastic properties using the known anisotropy coefficients through a facies-based inversion. This can produce a more accurate result than solving for pseudoelastic properties, and it can take advantage of the sometimes increased separation of isotropic and anisotropic rocks in the pseudoisotropic elastic domain. Because the effect of anisotropy will vary depending on the strength of the anisotropy and the distribution of the rocks, we strongly recommend forward modeling for each case prior to inversion to understand the potential impact on the study objectives.
Vertical transverse isotropy (VTI) will affect seismic inversion, but it is not possible to solve for the full set of anisotropic elastic parameters from amplitude variation with offset inversion because there exists an isotropic solution to every VTI problem. We can easily approximate the pseudoisotropic properties that result from the isotropic solution to the anisotropic problem for well-log data. We can then use these well-log properties to provide a low-frequency model for inversion and/or a framework for interpreting either absolute or relative inversion results. This, however, requires prior knowledge of the anisotropic properties, which are often unavailable or poorly constrained. If we ignore anisotropy and assume that the amplitude variations caused by VTI are going to be accounted for by effective wavelets, the inversion results would be in error: The impact of anisotropy is not merely a case of linear scaling of seismic amplitudes for any particular angle range. Ignoring VTI does not affect the prediction of acoustic impedance, but it does affect predictions of [Formula: see text] and density. For realistic values of anisotropy, these errors can be significant, such as predicting oil instead of brine. If the anisotropy of the rocks is known, then we can invert for the true vertical elastic properties using the known anisotropy coefficients through a facies-based inversion. This can produce a more accurate result than solving for pseudoelastic properties, and it can take advantage of the sometimes increased separation of isotropic and anisotropic rocks in the pseudoisotropic elastic domain. Because the effect of anisotropy will vary depending on the strength of the anisotropy and the distribution of the rocks, we strongly recommend forward modeling for each case prior to inversion to understand the potential impact on the study objectives.
We performed an integrated multidisciplinary study for reservoir characterization of a Utica Shale field in eastern Ohio covered by a multiclient 3D seismic data set acquired in 2015. Elastic seismic inversion was performed in-house for effective reservoir characterization of the Utica Shale, which covers the interval from the top of Upper Utica (UUTIC) to the top of Trenton Limestone. Accurate, high-fidelity inversion results were obtained, including acoustic impedance, shear impedance, density, and VP/VS. These consistent inversion results allow for the reliable calculation of geomechanical and petrophysical properties of the reservoir. The inverted density clearly divides the Point Pleasant (PPLS) interval as low density from the overlying UUTIC Shale interval. Both Poisson's ratio (PR) and brittleness unmistakably separate the underlying PPLS from the overlying Utica interval. The PPLS Formation is easier to hydraulically fracture due to its much lower PR. Sequence S4 is the best due to its higher Young's modulus to sustain the open fractures. The calculated petrophysical volumes indisputably delineate the traditional Utica Shale into two distinctive sections. The upper section, the UUTIC, can be described as having 1%–2% total organic carbon (TOC), 3.5%–4.8% porosity, 10%–24% water saturation, and 40%–58% clay content. The lower section, PPLS, can be described as having 3%–4.5% TOC, 5%–9% porosity, 2%–10% water saturation, and about 15%–35% clay content. Both sections exhibit spatial variation of the properties. Nevertheless, the underlying PPLS is obviously a significantly better reservoir and operationally easier to produce.
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