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In recent times, characterization of reservoir using elastic properties of the well logs is limited to discrimination of reservoir fluids and lithologies which do not precisely reflect reservoir characteristics. In this study, we propose a robust approach that uses the well log derived attributes to predict the effects of the production related changes and performance levels of the reservoirs. First, the elastic attributes were generated from the well logs using the transform menu of the E-log program. The appropriate pairs of the attributes were cross-plotted and color overlay of the most robust attributes established. The cross-plot of Lambda-Rho versus Mu-Rho revealed the gas charged sand, brine charged sand and streak of shale in HD5000 reservoir. The color overlay of the lambda-Rho showed very high degree of brine saturation and very low gas saturation. The cross plot of velocity ratio versus P-impedance in HD8000 reservoir revealed hydrocarbon charged sand which was associated with very low velocity ratio, acoustic impedance values and brine saturation. The color overlay of acoustic impedance showed very high hydrocarbon saturation and low brine saturation. The cross plot of Mu-rho versus density at HD9000 reservoir also revealed the hydrocarbon charged sand (very low-density values) and brine charged sand. The color overlay of density revealed relatively high hydrocarbon and low brine saturation. The high brine saturation in the reservoirs probably resulted from increase in formation water due to production and steam injection program which is an indication of reservoir depletion. However, the results indicate that HD8000 and HD9000 reservoirs are still active for more hydrocarbon production while HD5000 reservoir is not.

Predicting Reservoir Performance Using the Elastic Properties of Well Logs in Fabi Field, Niger Delta Basin in Nigeria