ABSTRACT

One of the major challenges in the interpretation of sonic logs is the presence of bed-boundary (shoulder-bed) effects, which can decrease the accuracy of the estimated elastic properties due to spatial averaging caused by the sonic receiver array across thin beds. A reliable approach to account for shoulder-bed effects in the interpretation of sonic logs is the implementation of forward modeling and inversion techniques. We have developed an efficient inversion-based interpretation method for the estimation of in situ rock formation elastic properties from sonic logs acquired in vertical wells. The method uses semianalytical spatial sensitivity functions for fast forward modeling of sonic-slowness logs and estimates formation elastic properties by iteratively matching the available logs with numerical simulations. Due to the intrinsic vertical resolution limits of sonic logs, the inversion method requires predefined bed boundaries using other high-resolution well logs. We first developed a workflow to estimate shear slowness of thin beds from flexural mode dispersions measured at multiple discrete frequencies. Then, we extended the method to estimate layer-by-layer compressional and shear slownesses by combining the slowness logs of nondispersive P- and S-waves. The method was first successfully verified using data numerically simulated for synthetic rock formations consisting of multiple thin beds and exhibiting large elastic property contrasts. Maximum relative errors and maximum uncertainty in the estimates were less than 2% and 6%, respectively. Field data acquired in wells penetrating multiple horizontal thin beds were also used to appraise the reliability and resolution improvement of the method in the estimation of formation compressional and shear slownesses. Our results indicated that our inversion-based interpretation method improved the vertical resolution of sonic logs by 70%. The new inversion-based interpretation method opens up the possibility of integrating modern borehole acoustic measurements with nuclear and resistivity logs for improved poroelastic and petrophysical interpretations.

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