RESERVOIR PARAMETERS ESTIMATION USING ROCK PHYSICS MODELLING AND AVO ANALYSIS FOR CHARACTERIZATION OF LOWER GORU FORMATION

Abstract

Although Seismic interpretation is important in terms of reservoir detections, the characterization of reservoirs is based upon well analysis. The problem with this analysis is one dimensionality. In order to deal with this problem, use of other methods are essential. Apart from post stack data analysis, pre stacked data analysis is a key tool to study the varying behavior of reservoirs with variation in their characteristics. Models for pre stacked analysis have been generated throughout the years which can be utilized to either distinguish reservoir sands into different classes and can play an essential part for inverting for a particular parameter if the model results for varying of a specific variable is geostatistically correlated with the pre stack data of the area. Focus of this study is to quantitatively characterize reservoir within study area and to check for variation within the reservoir using Rock Physics Models and Amplitude Versus Offset (AVO) analysis. The procedure starts with demarcation of horizons on the basis of seismic to well tie. Structural interpretation is important to study any existing petroleum play. The structural interpretation was therefore carried out including horizon marking of Lower Goru formation and C-interval. Fault polygon were demarcated to analyze two dimensional trend of the faults within the area. Petro-physical analysis concluded presence of reservoirs within the shaly sand lithology of Lower Goru formation. Zones were marked within the sand patches which showed favorable results. In order to study the pre stacking trend for the reservoir marked using the above mentioned techniques, T- matrix and Non Interactive Approximation RPMs were utilized to obtain the dry rock properties. The porosity within the models was varied to check the effect on the elastic parameters. Wood’s equation was used for determination of effective properties of fluid which was then inculcated into the dry rock model with the help of Gassmann’s equation. The saturation level within the Wood’s equation was varied to check the response of the models under differing saturations. Reflectivity series for varying offset (angle) were determined using Rugger’s approximation. The trend showed presence of Class I sands in the reservoir. Results from the models under influence of varying input variables were compared and the trends were discussed. AVO synthetics were generated for each scenario using both the RPMs. The results upon comparison showed a comparatively sharper traces in case of elastic parameters obtained from T – matrix compared to NIA.