An Analytical Formulation of Seismic-Derived Resistivity
Mendrofa, Denny Merkurius1,
Bambang Widarsono2 (1) Premier Oil Ltd,
Recent developments in seismic petrophysics have shown that efforts to establish methods used for deriving water saturation (Sw) from seismic usually meet an end in empirical approach as a regression function of acoustic wave or in the use of artificial intelligence. This certainly does not provide a solid theoretical basis to the effort. The paper presents an effort to establish a theoretical aspect to the effort in the form of establishment of a relationship between resistivity and acoustic impedance (AI). We hope that through this theory seismic - derived AI would play an important role for estimation of reservoir rock resistivity (Rt), which in turn would be used in the estimation of water saturation.
The main thrust of the works presented in this paper is formulation of combined formulas between acoustic velocity models from Gassmann's Theory and water saturation models (Modified Poupon and Hossin models are used). Combination of Sw formulated in the water saturation models and Sw contained in the acoustic velocity models is the key to develop analytical relationship between Rt and AI. The formulation proved successful and two resistivity functions have been established for cases of laminated and dispersed shale distributions. In essence, through these functions resistivity of porous elastic rock relates directly to acoustic impedance. This offers direct estimation of resistivity without measuring it directly by electrical tools, hence it becomes a starting point of an analytical seismic-petrophysics direct calculation that is developed today. In effect, acoustic impedance values from seismic can entirely be converted to pseudo resistivity and water saturation values. The preference of resistivity to water saturation comes from the knowledge that resistivity usually vary widely for a hydrocarbon-water system reservoir.
AAPG Search and Discover Article #90063©2007 AAPG Annual Convention, Long Beach, California