Seismic wave propagating in a fluid saturated medium generally produces attenuation and dispersion, which consequently change the frequency and phase of reflected wavelets. The frequency characteristics are usually used in reservoir prediction, while the phase characteristics are rarely used. There are two possible reasons for this, one of which is the unclear understanding of the phase behaviors of different kinds of reservoir, and the other of which is the lack of method to extract phase change information from seismic data. In this study, firstly, the causes of phase change due to attenuation are studied through numerical modeling. Then the complex spectral decomposition technique is developed to extract wavelet phase from seismic data. After that, the phase behaviors are further analyzed from seismic experiments on a physical model, in which the reservoir is filled with gas, oil or water. Finally, a real data example demonstrates the high time resolution of the proposed method in reservoir prediction and the successful application of the phase change in distinguishing gas saturated layers and water saturated layers.
Many rock physics studies and field observations have proved that fluid saturated layers will attenuate seismic signals. Higher frequency components are more easily attenuated than lower frequency components. Therefore, the abnormal low-frequency components are usually used for indicating hydrocarbon reservoir. However, in real exploration, this method sometimes fails because water saturated layers also attenuate seismic waves and generate similar frequency spectrum with hydrocarbon filled reservoir. In this situation, we should use other attributes to reduce the uncertainty.
Actually, the attenuation and dispersion change not only the wavelet frequency but also change the wavelet phase. The frequency characteristics are usually used in reservoir prediction, while the phase characteristics are rarely used. That may due to unclear understanding of the phase behaviors of reservoir, and the lack of method to extract phase change information from seismic data.
Huang, Fei (Uppsala University) | Juhlin, Christopher (Uppsala University) | Han, Li (CNOOC Research Institute) | Kempka, Thomas (GFZ German Research Centre for Geosciences) | Norden, Ben (GFZ German Research Centre for Geosciences) | Lüth, Stefan (GFZ German Research Centre for Geosciences) | Zhang, Fengjiao (Uppsala University)
The seismic complex decomposition technique is a spectral decomposition method using inversion strategies to decompose a seismic trace into its constituent frequencies and corresponding complex coefficients. This method has high time-frequency resolution and it is not necessary to select a signal window in comparison to conventional spectral decomposition methods. The thickness of the reservoir at the Ketzin pilot site is relatively thin, making it difficult to resolve seismically due to the band-limited seismic spectrum. This study presents an application of seismic complex decomposition to the time-lapse 3D seismic datasets at the Ketzin pilot site for estimating the temporal thickness of the injected CO2 within the thin reservoir via frequency tuning. Quantitative analysis for CO2 thickness and mass is investigated. Comparison between the real recorded data and the estimates shows that our results are reliable in assessing the amount of the CO2 in the plume at the Ketzin pilot site.
The Ketzin pilot site is located west of Berlin, Germany, as an in situ laboratory for monitoring the storage of carbon dioxide (CO2) in a saline aquifer. The project was initiated in 2004 with the aim to verify effective monitoring methods for mapping the injected CO2 plume and to provide operational field experience of CO2 geological storage (Martens et al., 2013; Martens et al., 2014). One injection/observation well (Ktzi 201) and two observation wells (Ktzi 200 and Ktzi 202) were drilled in 2007 prior to CO2 injection. Over a 5-year period, up to 67 kt of CO2 were injected into the target reservoir, the fluviatile and heterogeneous Upper Stuttgart Formation. It is characterized by alternating siltstones and mudstones with poor reservoir properties and sandstone channels with good reservoir properties. The main-reservoir sandstone unit is 9- 20 m thick in the three wells (Norden et al., 2010).
The time-lapse 3D seismic method has proven to be a successful technique to monitor the growth of the CO2 plume at the Ketzin site. A 3D baseline seismic survey was acquired in autumn 2005 prior to CO2 injection (Juhlin et al., 2007). Two 3D repeat seismic surveys were acquired in autumn 2009 and autumn 2012, after about 22 kt and 61 kt of CO2 had been injected, respectively. Results from the time-lapse analysis (Figure 1) show conspicuous amplitude anomalies due to changes in the reservoir properties after CO2 injection and a preferred westward trend of CO2 migration, reflecting the internal heterogeneity of the reservoir.
Frequency-dependent AVO contains additional attributes of the reservoir, which can enhance the accuracy of the seismic interpretation. Conventional geological models usually used to AVO analysis are thick layers. However, thin layers (thickness below tuning thickness) might be significant reservoirs or important flow units within reservoirs. One difficulty with extracting the additional attributes from thin layers is that the tuning effects affect seismic amplitudes, which can mask or at least alter the features that are associated with permeability and fluid content. Therefore, to best analyze these AVO attributes in different frequencies, it is necessary first to correct the spectral data for the effects of the thin beds. This paper presents one approach to remove the effects of thin-beds on frequency-dependent AVO analysis via spectral inversion.