A study of wavelet transform in the identification of fracture of Formation Micro-Resistivity image logging

Formation Micro-Resistivity (FMI) is an emerging logging technology in recent years. Although fracture can be directly illustrated in FMI, there is a great subjective factor for the identification of fracture. This paper focuses on the difficulties of avoiding the subjective factor in the fracture identification of FMI using wavelet transform. The resistivity curve of FMI is decomposed by wavelet transform, and we make a research in the relationship between decomposed signal and fracture. Using signal decomposition of wavelet transform adjusts the fracture identification of FMI to identify fracture more accurately.