Comparison of Probabilistic Techniques in the Study of Fluid Effects on Seismic Properties

The parametric method is known for probabilistic estimation of hydrocarbon reserves (Smith et al. 1993). This analytical approach is not “black boxy” as compared to the Monte Carlo simulation. It uses common statistical information. More so, the relative impact of the input parameters is easily ranked to ascertain each individual’s contribution to the total uncertainty. This paper elaborates the use of the parametric approach to analyze the uncertainty associated with the effect of reservoir fluids on seismic properties. The outcome is compared with Monte Carlo simulation and deterministic techniques. A forward modeling algorithm based on fluid substitution procedure is employed in the study. The model assumes each reservoir fluid such as black oil, volatile oil, gas condensate, dry gas and water is saturated in the rock pores. The effect of these fluids on seismic properties such as compressional velocity, shear velocity, acoustic impedances is simulated with uncertainty. Moreover, saturation changes effect on these seismic properties in a two phase system is also studied. Beyond these, a relative impact analysis is carried out to know the individual input data’s contribution to the total uncertainty. Sandstone reservoir rock and fluid properties from laboratory are used for the analysis. Scale-up techniques are used to ensure consistency between laboratory and seismic scale data. The results from both parametric and Monte Carlo simulation showed a good agreement. The results showed a unique effect exhibited by each reservoir fluid on the seismic properties. This approach can assist in identifying reservoir fluids especially at in-situ conditions from the seismic results. The outcome also showed a similar observed result in the Wyllie plot of velocity versus fluid saturation changes. The prediction of saturation effect on seismic properties would enrich time-lapse reservoir monitoring in identifying unswept zones and aid in optimizing in-fill drilling.