I study the influence of different elastic parametrizations in amplitude versus angle (AVA)-petrophysical inversion and in litho-fluid facies identification with a focus on a reservoir located in offshore Egypt. Concerning the AVA-petrophysical inversion, I first use linear rock-physics models (RPMs) to rewrite the AVA forward modelling in terms of petrophysical properties instead of elastic properties. After demonstrating the reliability and the prediction capabilities of the derived RPMs, I apply a Bayesian inversion to estimate petrophysical properties from the analytical AVA responses derived from the logged elastic attributes pertaining to a blind well. Then, the standard sensitivity analysis tools are used to theoretically investigate the results provided by the AVA-petrophysical inversion and to examine the differences between the derived petrophysical-AVA forward operators. As regards the litho-fluid facies identification, I verify if different elastic parameterizations yield different classification results. For the considered reservoir, it results that the different elastic parameterizations do not influence the AVA-petrophysical inversion in which the porosity is always the best resolved parameter, whereas shaliness and water saturation are less resolvable. The results also show that different elastic parameterizations provide identical facies classification results.

Analysing the influence of different elastic parameterizations in AVA-petrophysical inversion and in litho-fluid facies classification for a reservoir located in offshore Egypt / Aleardi, Mattia. - In: BOLLETTINO DI GEOFISICA TEORICA E APPLICATA. - ISSN 0006-6729. - 59:1(2018), pp. 47-70.

Analysing the influence of different elastic parameterizations in AVA-petrophysical inversion and in litho-fluid facies classification for a reservoir located in offshore Egypt

Mattia Aleardi
2018

Abstract

I study the influence of different elastic parametrizations in amplitude versus angle (AVA)-petrophysical inversion and in litho-fluid facies identification with a focus on a reservoir located in offshore Egypt. Concerning the AVA-petrophysical inversion, I first use linear rock-physics models (RPMs) to rewrite the AVA forward modelling in terms of petrophysical properties instead of elastic properties. After demonstrating the reliability and the prediction capabilities of the derived RPMs, I apply a Bayesian inversion to estimate petrophysical properties from the analytical AVA responses derived from the logged elastic attributes pertaining to a blind well. Then, the standard sensitivity analysis tools are used to theoretically investigate the results provided by the AVA-petrophysical inversion and to examine the differences between the derived petrophysical-AVA forward operators. As regards the litho-fluid facies identification, I verify if different elastic parameterizations yield different classification results. For the considered reservoir, it results that the different elastic parameterizations do not influence the AVA-petrophysical inversion in which the porosity is always the best resolved parameter, whereas shaliness and water saturation are less resolvable. The results also show that different elastic parameterizations provide identical facies classification results.
Aleardi, Mattia
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/931988
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