Abstract

Between all available methods for fractures evaluation, core and image logs are prime methods. However, both of these data are very expensive and practically available in less than 10% of drilled wells. Therefore, a less expensive and quick method would be very helpful for fracture analysis. The main aim of this study is to identify the fracture parameters in the carbonate reservoirs, i.e. fracture density and fracture aperture, using a combination of sonic, resistivity and other conventional logs which commonly available in all wells. For this aim, fractures and their parameters were precisely determined on the image logs in 6 wells from carbonate Asmari Formation as a typical fractured reservoir in the world. Then, the effect of fracture parameters on the sonic and resistivity logs were used to identify fracture parameters in the wells with no core and image logs. Results indicate that the zones with high fracture density and aperture are easily detectable by conventional logs. On the other hand, the behavior of these logs is a function of fracture parameters in the fractured intervals, especially in the zones with high fracture aperture. Separation between shallow (RLA2) and deep (RLA5) resistivity logs along with their cross plot are very reliable indicators for fractured intervals. Sonic transit time rapidly increases where fractures density or aperture increased as well. In this study, a combination of sonic and neutron porosity logs have also been used to determine the effect of fracture aperture, as the main effective factor on the reservoir properties. Furthermore, full waveforms in some studied wells combined with sonic transit time to improve the results of fractures evaluation. Using sonic and resistivity along with neutron porosity and gamma ray logs provides a reliable method for describing the fracture parameters which shows high correlation with image logs results. Due to the high impact of fracture aperture on both reservoir quality and conventional log responses, determination of this parameter is more crucial than other fracture parameters. This method is also applicable for OBM (Oil Base Mud) image tools which conventionally cannot detect fracture aperture.

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