Revista Fuentes El Reventón Energético (Dec 2008)

PROPIEDADES PETROFISICAS EN EL ESTUDIO DE UN PROCESO DE INYECCION DE AGUA MEDIANTE MODELOS FISICOS ESCALADOS

  • Carlos Augusto Jerez Quiroga,
  • Erika Margarita TRIGOS BECERRA,
  • Fernando Wilson Londoño Galvis,
  • Samuel Fernando Muñoz Navarro

Journal volume & issue
Vol. 6, no. 2
pp. 49 – 55

Abstract

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In the study of waterflood process using scaled physical models, there are some factors like petrophysics, geometry, pressure and others properties of the porous media that are impossible to reproduce exactly, because the conditions present a big difference. Now, if it is impossible to reproduce the porous media in laboratory, petrophysics properties are going to be different too, like these properties determine flow fluids the production results between field and laboratory are different. However, scaled models are very expensive but if you are going to study a new process where the physics is not unknow, they are a big help, then ¿What can you do with the difference in petrophysical properties? Well, you can ignore this difference or pay a lot of money additionally for ¿try¿ of build a better porous media. But, there is a third option that you can include for the calculation of the difference in petrophysical properties; the question is ¿How? In this work it was proposed a new method based in the difference of mobile porous volume, because this property have relation with residual saturations, porosity and scale factor. Use of this method is limited for some characteristics like geometry, we used a configuration of two wells in a eighth of five spot; the reservoir must be homogeneous without shale intercalations, and finally fluids used in field and laboratory must present equal mobility relation. When you are going to use this graphic method, it is necessary to know mobile porous volume in field, the scale factor used and mobile porous volume in model. With these properties, you can read a difference factor for the recovery factor in the graphic and with this value you can matching your recovery factor and other production data, to get a best result with your physical models.

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