## 4 Field Data Examples  
When seismic waves propagate through hydrocarbon reservoirs, waves induced by fluid flow can lead to abnormal attenuation of energy and frequency (e.g., [31; 32]). The phenomenon of abnormal attenuation mainly shows the loss of high-frequency energy and the conservation of strong low-frequency energy (e.g., [33; 34; 35; 36; 37]). Spectral decomposition technology can be utilized to identify hydrocarbon reservoirs by analyzing the different frequency response characteristics among different scale geological bodies (e.g., [38]). Here, we apply the SSGST method to seismic field data from the ZhongJiang Gas Field located in the western Sichuan Basin, China, in order to identify hydrocarbon reservoirs by analyzing the abnormal instantaneous frequency and energy. The seismic section consists of 304 traces with 1126 sampling points and a sampling interval of 2 ms, which is shown in Figure 7. The green curve in the horizontal direction at around 1.35 ms is a seismic horizon and the green vertical line represents a gas well. The area within the blue ellipse is a gas-bearing reservoir, which is our study area. Figure 8 is a histogram based on comprehensive analysis of log data. There are two sets of hydrocarbon reservoirs in the study area: the first set of reservoirs (JS33-1) is located in near a depth of 2560 m and thickness of about 22 m, and the second set of reservoirs (JS33-2) is located in near a depth of 2600 m and thickness of about 18 m.  
We used the CWT, GST, SSCWT, and SSGST methods respectively to processes the seismic data and extract the constant frequency sections at 40 Hz and 50 Hz, as shown in Figures 9-12. The results are enlarged, and only the areas with time ranging from 1.2 s to 1.9 s are displayed in these constant frequency sections. In the constant frequency sections at 40 Hz (Figures 9a, 10a, 11a and 12a), we can see a strong energy in the study area. However, obvious energy attenuation can be seen in each of the 50 Hz sections (Figures 9b, 10b, 11b and 12b). This phenomenon is consistent with objective reality. Therefore, the four methods are all effective for hydrocarbon detection. Although the analysis results of the CWT and GST can observe the abnormal attenuation in the hydrocarbon reservoir, they offer rough reservoir information due to the poor time-frequency resolution of CWT and GST (Figures 9 and 10). Compared with the CWT and GST methods, the SSCWT method can improve the time-frequency resolution and obtain the accurate reservoir information but cannot identify the boundaries of the two sets of hydrocarbon reservoirs, as shown in Figure 11.  
Figure 7: The seismic section from the ZhongJiang Gas Field. Figure 8: Histogram from the comprehensive analysis of well data (The red curve on the left is acoustic log (AC), and the unit of AC is us/ft. The black curve is natural gamma ray log (GR), and the unit of GR is API. The blue curve is true formation resistivity log (RT), and the unit of RT is OMM. The red curve on the right is shallow investigate double lateral resistivity log (RS), and the unit of RS is OMM.). Figure 9: Constant frequency sections based on CWT (**a**) at 40 Hz and (**b**) at 50 Hz. The constant frequency sections at 40 Hz and 50 Hz obtained by SSGST are shown in Figure 12. By comparing these two constant frequency sections, we can conclude that the hydrocarbon reservoir is in the elliptical area. To highlight more details about the elliptical area in Figure 12, we have locally enlarged the 40 Hz constant frequency section and combined it with the red acoustic velocity logging curve to analysis. The strong energy group in the two black-dashed, rectangular areas in Figure 13  
Figure 11: Constant frequency sections based on SSCWT (**a**) at 40 Hz and (**b**) at 50 Hz. Figure 12: Constant frequency sections based on SSGST (**a**) at 40 Hz and (**b**) at 50 Hz. Figure 10: Constant frequency sections based on GST (**a**) at 40 Hz and (**b**) at 50 Hz. represent the two hydrocarbon reservoirs, namely JS33-1 and JS33-2, respectively.