Revised models for evaluating hydrocarbon saturation of tight sandstone formations based on dielectric dispersion logs

Author:

Wang Xiaoyu12,Liao Guangzhi12,Zhao Peiqiang12,Mao Zhiqiang12

Affiliation:

1. State Key Laboratory of Petroleum Resources and Prospecting China University of Petroleum Beijing China

2. Beijing Key Laboratory of Earth Prospecting and Information Technology China University of Petroleum Beijing China

Abstract

AbstractAccurate estimation of hydrocarbon saturation is significant for log interpreters to evaluate tight sandstone formations. It is difficult to use conventional wireline logs to calculate hydrocarbon saturation in complex reservoirs. Dielectric dispersion logs are processed using dielectric models to obtain accurate saturation assessment, especially in high salinity shaly sand formations. However, the dielectric models consist of complex refractive index method model and shaly sand model ignore the impact of clay effects on complex refractive index method model, and the dielectric dispersion logs generated by them appear several unphysical phenomena in the clay‐bearing formations, such as the permittivity data at the highest frequency are greater than those at the second highest frequency and the conductivity data at the highest frequency are lower than those at the second highest frequency. This paper modifies the dielectric models by introducing a combined conductive phase in complex refractive index method model to correct the unphysical behaviours. Revised models are combined with four permittivity and four conductivity logs acquired by dielectric scanner at 24, 102, 360 and 960 MHz to inverse the water saturation, water salinity, textural index for water‐bearing pore and fraction of clay‐related phase. The complex refractive index method model interprets the logs measured at 960 MHz and shaly‐sand model interprets other dielectric dispersion logs. The particle swarm optimization algorithm is used to search inversion parameters. The results of forward simulation show that the revised models can correct unphysical behaviours of dielectric dispersion logs generated by the original models. Moreover, we apply original models and revised models to laboratory core data. The results of experiments show that the mean relative error values of the original models are 19.38% and 23.60% and of the revised models are 5.54% and 6.28% in two cases. It shows that the revised models are more accurate than the original models to interpret dielectric dispersion logs of tight sandstone reservoirs.

Publisher

Wiley

Subject

Geochemistry and Petrology,Geophysics

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