Using conventional logs for fracture detection and characterization in one of Iranian field

Abstract

Fracture analysis is generally accepted as one of the main steps through better understanding and optimization of assessment to production in most of the carbonate reservoirs. Effects of fracturing on reservoir performance provides engineers and geoscientists with the information needed to make business decisions with a higher degree of certainty. There are a few methods, which give us tracks of the fractures and the main problem is that even these are obtained using considerable time and money. What is clear is the importance of these data. In the last decade the main obsession of reservoir professionals was to develop some methods to detect more exactly the fracture attributes as well as extending the domain of the obtained data by different ordinary practices among them borehole image logs, surface geological analysis, well tests, etc. In the current paper we will apply a method, by which we could estimate the position of the fractures and this method could be used for confirming the results of the borehole image logs or even used alone and we will show that the fracture positions would be determined as precise as any other available method(s). Five wells were selected in one of the Iranian gas reservoir for which we have already the result of seismic interpretation. Other information as some petrophysical logs (Sonic, Neutron Density, MSFL, RHOB, etc), mud loss and drilling data are available for all wells. One of these wells also has borehole image log. Applying these data we could determine the position of the fracture and roughly the fracture orientation. By determining the Wavelet detail coefficient of petrophysical logs, and velocity index, with considering to other data including Mud loss and Variable Density Log (VDL), we could establish the fracture positions along the wells. For fracture density determination in inter well space, first curvature analysis was done and, then fracture density along the wells correlated with structural curvature at well location. We use this correlation and Geo-statistical method for obtain fracture density map in the reservoir.