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