In Andian area of Biyang Depression, the formation of target reservoir is interbeded with thin sand layers less than 10m and the sand layers vary severely in lateral. It is difficult to distinguish the boundaries of sand and shale layers using the acoustic impedance attributes. Here, we proposed a detailed inversion method based on Gaussian association simulation method using Poisson’s ratio parameter as background constraint which were extracted from two-angle elastic impedance inversion. The case study showed that the inverted high resolution Poisson’s ratio volume can reveal the detailed information of the thin layers. And the inverted result matched the geology and well log data, based on which we predicted the distribution of the thin reservoir and favorable target layers which was proved true by drilling.
Biyang Depression is a half graben-like fault depression which developed in the East Qinling fold belt, where oil source and reservoir system developed. The oil reservoir mainly distributed in fan delta depositional system of the southern steep slope and in river delta system of the northern gentle slope of the depression. Andian area is in the southern and eastern margin of Biyang Depression which is depressed area controlled by the upfaulted block of fracture. The reservoirs are mainly lithologic traps, where Eh2 and Eh3 sands are the main oil-bearing layers, and sandstone developed with good reservoir-cap combination. However, the sand body is thin in this area, generally less than 10m, and lateral variation is significant, where conventional inversion methods cannot effectively predict the reservoir. We integrated the required well log data, 3D seismic data and geology information, and found that the thin layers played a critical role in the study area. As we know, the vertical resolution of seismic data is quarter of seismic wavelength (Widess,1973). In this case study, we found that we can’t discriminate the sand layers less than 20m through conventional seismic section. Many authors proposed their methods to solve thin layers and image geologic feature, including statistical inversion (Sams,1999; Shanor, 2001), spectral decomposition analysis (Partyka, 1999, 2005; Castagna, 2003), spectral inversion (Chopra, 2006) and so on. Here, we proposed a detailed inversion which combines the elastic inversion and statistical simulation to estimate high vertical resolution Poisson’s ratio volume. Since the elastic impedance inversion result was used as background constraint, the final simulated result had improved lateral geological feature. Numerous processing techniques had utilized to improve the quality of pre-stack gather and to diminish the damaging ambiguous affect to the inversion result. Interpretation including estimation of lithology, porosity, and saturation were made from geologic and well log data. Those work provided powerful technical support for stable inversion results. And we verified the final inversion results according to the blind well test and obtained satisfactory results at last.
The research area covered 90km3 of 3D seismic data. The seismic bin size was 25m by 25m. There were 29 high quality wells selected for the inversion process.