A new approach for optimizing productivity/injectivity in naturally fractured reservoirs based on fracture network detection using Fourier - wavelet transform analysis

Fracture detection is a key step for characterization and modeling of reservoirs for optimizing production by shooting to the casing right in fracture muster points. Actually, fractures play crucial role in production of oil and gas by introducing super conductive paths to the porous medium and the challenge is finding where they are.Many approaches took advantage of sharp changes of rock physical properties in the presence of fractures for fracture detection. Likewise, wavelet transform analysis (WTA) is sensitive to changes in the inlet signal and can be employed for this purpose. Considering petrophysical data as input, fractures can be highlighted with change in near wellbore resistivity in the fairly fixed lithology. Decomposition of such signals after removing high frequency noises shows very valuable data hidden in the low frequency part of the original signal.In this research, WTA is employed for finding fracture muster points in one of Middle Eastern carbonates. MSFL profile is de-noised and results show good match with interpreted FMI of under studied interval in highlighting open fractures. Application of this approach can help for finding hot spots for perforation or well path design of directional wells and also can eliminate running of image logs.