SciELO - Scientific Electronic Library Online

 
vol.4 número2METHODOLOGY TO DESIGN OF SYNTHETIC SONIC LOG (SSL) USING ARTIFICIAL NEURAL NETWORKS. COLORADO FIELD APPLICATION índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • En proceso de indezaciónCitado por Google
  • No hay articulos similaresSimilares en SciELO
  • En proceso de indezaciónSimilares en Google

Compartir


CT&F - Ciencia, Tecnología y Futuro

versión impresa ISSN 0122-5383versión On-line ISSN 2382-4581

Resumen

ESCANDON, Carlos  y  MONTES, Luis. DETECTING AND CHARACTERIZING FRACTURES IN SEDIMENTARY DEPOSITS WITH STONELEY WAVES. C.T.F Cienc. Tecnol. Futuro [online]. 2010, vol.4, n.2, pp.7-19. ISSN 0122-5383.

The naturally fractured reservoirs are attractive potential zones for a successful hydrocarbon prospecting, and the variable density logs (VDL) with Chevron patterns generated by Stoneley waves is a suited tool to characterize fractures. In this project, a simplified algorithm to evaluate fracture location using reflection coefficients and analysis of attenuation was implemented. It also uses a permeability indicator (Stoneley Slowness added by Permeability) to discriminate permeability in fractures. The algorithm was tested in a foot hill well of the Colombian west range, detecting a previously known fractured sandstone zone and indicating its permeability. Besides, the algorithm detected other existent fractures zones with low permeability for production. Previous well flow evaluation of the localized fractures characterized them as low or no permeability fractures.

Palabras clave : deposits; fractures; waves; permeability; sonic log; Llanos foothills.

        · resumen en Español     · texto en Inglés     · Inglés ( pdf )

 

Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons