Gas Reservoir Detection Using Mixed Components Short Time Fourier Transform (MC-STFT) as a new attribute

Abstract

Abstract Identification of gas reservoirs as a main natural resource due to its economic importance has always been one of the most important issues in research studies in the oil and gas field. Accurate localization of a gas reservoir through seismic data has been broadly studied. The final destination of all seismic attributes is to distinguish a specific feature and make it detectable. Accordingly, many seismic attributes have been developed among which short time Fourier transform (STFT)-based methods play an important role. However, simplicity and efficiency can make a method superior. So we propose an attribute which utilizes mixed components of STFT (MC-STFT). The novelty about this method is that without altering STFT method or adding any complexity, MC-STFT is able to detect gas reservoirs at high resolution. In fact, this method takes advantage of extracting three frequency components obtained by STFT. We apply this method on three data sets, first, Marmousi model and then two other real seismic zero-offset sections. Numerical results confirm its good performance in high resolution gas reservoir detection.