Delineating Hydrocarbon Response using Robust Bulk Modulus Inversion Through Linearised AVO Approximation

Abstract

SUMMARY The key to further demonstrate 4D values in Field A relies on the interpretation of the reservoir changes due to production from year 1995 to 2006. Significant rock properties change due to pressure and fluid movement showed different amplitude variation with offset (AVO) behaviour on seismic data at different vintages. Existing AVO indicators suggest ambiguous results prone to certain factors such as porosity. Fluid properties such as oil and water of density has similar range of values. Hence, differentiating oil versus water in the porous media has become a problem typically in exploration prospecting and production monitoring. This problem can be mitigated if we are able to estimate accurately the bulk modulus parameters since it differs between the properties in the pore-fluid phase and rock-solid phase of homogeneous media. Since the conventional fluid factor (f) provides ambiguous results prone to the instability of pore fluid mixture and porosity in identifying fluid prospect, we re-parameterized new AVO approximation in term of K considering bulk modulus of the rock matrix higher than the bulk modulus of the effective pore fluid (combine with porosities higher than 15%). Then, the inverse problem is solved using conjugate gradient optimization and tested the robustness of the new method on thin channelized synthetic model and real field data. The synthetic result shows the inverted pore fluid bulk modulus is closer to the measured model and the initial model, however larger uncertainties was observed from inverted density compared to the measured model. Starting from the noise free scenario, we gradually added noise from 5% to 30% into the channelized synthetic model to ensure the quality of the inversion method. Field data example revealed that 4D inverted effective pore-fluid bulk modulus are capable to identify lateral waterflood sweeping effect in the reservoir after eleven (11) years of production, expand the ability in differentiating fluid for clastic reservoir hence increase the probability for accurate hydrocarbon prediction.