To characterize the Buena Vista Hills field, the authors have implemented methods of modeling, processing and interpretation. The modeling methods are based on deterministic and stochastic solutions. Deterministic solutions were developed in Phase 1 and applied in Phase 2 to simulate acoustic responses of laminated reservoirs. Specifically, the simulations were aimed at implementing processing techniques to correct P-wave and S-wave velocity logs for scattering effects caused by thin layering. The authors are also including a summary of the theory and the processing steps of this new method for predicting intrinsic dispersion and attenuation in Section 2. Since the objective for ...
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To characterize the Buena Vista Hills field, the authors have implemented methods of modeling, processing and interpretation. The modeling methods are based on deterministic and stochastic solutions. Deterministic solutions were developed in Phase 1 and applied in Phase 2 to simulate acoustic responses of laminated reservoirs. Specifically, the simulations were aimed at implementing processing techniques to correct P-wave and S-wave velocity logs for scattering effects caused by thin layering. The authors are also including a summary of the theory and the processing steps of this new method for predicting intrinsic dispersion and attenuation in Section 2. Since the objective for correcting velocity scattering effects is to predict intrinsic dispersion from velocity data, they are presenting an application to illustrate how to relate permeability anisotropy with intrinsic dispersion. Also, the theoretical solution for calculating full waveform dipole sonic that was developed in Phase 1 was applied to simulate dipole responses at different azimuthal source orientations. The results will be used to interpret the effects of anisotropy associated with the presence of vertical fractures at Buena Vista Hills. The results of the integration of core, well logs, and geology of Buena Vista Hills is also given in Section 2. The results of this integration will be considered as the input model for the inversion technique for processing production data. Section 3 summarizes accomplishments. In Section 4 the authors present a summary of the technology transfer and promotion efforts associated with this project. In the last section, they address the work to be done in the next six months and future work by applying the processing, modeling and inversion techniques developed in Phases 1 and 2 of this project.
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Parra, J.O.; Hackett, C.L.; Brown, R.L.; Collier, H.A. & Datta-Gupta, A.Characterization of fracture reservoirs using static and dynamic data: From sonic and 3D seismic to permeability distribution,
report,
October 1, 1998;
United States.
(digital.library.unt.edu/ark:/67531/metadc678655/:
accessed February 23, 2019),
University of North Texas Libraries, Digital Library, digital.library.unt.edu;
crediting UNT Libraries Government Documents Department.