Artículo

Evaluation of in situ elastic and mechanical anisotropic properties based on rock physics, well logs and drill cuttings: A case study from Palermo Aike shale in Austral Basin, Argentina

Ravazzoli, Claudia Leonor Icon; Panizza, Guido Icon; Camilion, Emilio Icon

Otros responsables

Fecha

10/2024

Editorial

Elsevier

Revista

Geoenergy Science and Engineering

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Institución organizadora

ISSN

2949-8910

eISSN

ISBN

Idioma

Inglés

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Resumen

During last years, the Palermo Aike (or Inoceramus) shale formation, in the Austral Basin of Argentina, has received increasing attention from both the oil industry and academia. Due to the intrinsic elastic anisotropy observed in this kind of rocks, vertical well logs are not enough to characterize properly the formation. For this reason, we propose to combine standard well logs and laboratory data measured on drill cuttings to estimate the whole stiffness tensor and the characteristic anisotropy coefficients at borehole scale. With these motivations and, given that there are still few rock physics studies about this particular shale, in this case study we implement a practical calibration procedure to predict densities, sonic velocities and related quantities at well scales. Our formulation combines well known poroelastic rock-physics theories with numerical inversion techniques to estimate fitting and physical parameters, taking into account in the computations the confining stress and pore pressure for each depth. This allows us to calibrate the model under non-hydrostatic differential stress conditions. Another point to highlight is the fact that our procedure does not need to introduce any assumptions about the shape of pores and grains, nor using empirical approximations. The calibrated model permits us to control and replace spurious data and also to derive shear wave velocities, anisotropy parameters, Young’s modulus and Poisson’s ratio logs along the wells under study. The results found allow us to concludethat the proposed workflow is a useful and novel tool that can be applied with real data from any other organic shale reservoir.

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