Detection of sub-seismic fault footprint from signal-to-noise ratio based on wavelet modulus maximum in the tight reservoir

Subtle fault (sub-seismic fault) interpretation, which lies below the seismic resolution, is restricting to the tight reservoir exploration. To obtain the sub-seismic faults, significant effort is required to identify their footprint in the seismic data. We introduce a method, which is signal-to-noise ratio based on wavelet modulus maximum (SNRWMM), for detecting sub-seismic fault footprint. SNRWMM is calculated by the wavelet modulus maximum. Furthermore, we discuss the calculation procedure. We applied the proposed method on the 2D synthetic and real data, and found that the sub-seismic fault can be visible. And so the sub-seismic fault footprint, which existed in the imaging logging data, can be identified by the seismic interpreter. Consequently, SNRWMM can be used as a proxy for sub-seismic faults, and this method can be used to extract the implicit information to bridge the information gap between sub-seismic faults and well logging data.