Lowering the Risk in Reservoir Fluid Prediction Through Multiscale Integration presented by Marwah Al Ismail

Abstract

One of the major challenges facing the oil industry today is understanding the differences in data scales and how those variations affect the acoustic signatures of the reservoir parameters at different scales. Acoustic measurements of carbonate rock from core samples are usually different from those acquired at the wellbore for the same rock. The dissimilarity may be due to variations in laboratory and borehole conditions, heterogeneity at different scales as well as differences in tool physics. For example, acoustic slowness measurement in the laboratory would require a different frequency than would be required in a wellbore. This research was conducted to understand the differences in fluid acoustic signature at different scales as it is a critical part of the effort to minimize uncertainties and lower risks in hydrocarbon exploration and production. A carbonate oil reservoir in Saudi Arabia was selected for this study. Acoustic measurements from core plugs and wireline logs of three wells were used to study the changes of fluid acoustic signature over different scales. The workflow consists of three parts. Firstly, at log scale, the in-situ pore fluids were replaced with a hundred percent saturation of oil and then brine using a modified Gassmann’s equation. Then the acoustic responses associated with both scenarios were noted. Secondly, a similar procedure was performed on laboratory measurements acquired under reservoir conditions. Finally, the differences between these measurements were quantified and empirical models to correct for such variations were derived. The results of this study show that variations in the measurements make it difficult to recognize the acoustic signature caused by different fluids. Therefore, certain corrections should be applied using the derived models for any fluid saturation predictions in this field. The outcome of this research also improved our understanding of uncertainties associated with different scales and will enhance our predictions of reservoir fluids in the future.

AAPG Datapages/Search and Discovery Article #90332 © 2018 AAPG International Conference and Exhibition, Cape Town, South Africa, November 4-11, 2018