AAPG GEO 2010 Middle East
Geoscience Conference & Exhibition
Innovative Geoscience Solutions – Meeting Hydrocarbon Demand in Changing Times
March 7-10, 2010 – Manama, Bahrain
Integrating Rock Physics, Seismic
Reservoir Characterization and Static
Modeling
of Carbonates; a Case Study from the UAE
(1) ADCO, Abu Dhabi, United Arab Emirates.
(2) Shell, Abu Daubi, United Arab Emirates.
An integrated workflow to generate seismically constrained reservoir models is described. Several key technologies were used including carbonates rock physics estimation, seismic
forward
modeling
and comparison to surface 3D
seismic
, as well as probabilistic
seismic
inversion.
Using the SUN rock model as a framework, the team derived relationships between the reservoir properties (like modeled facies, porosity and fluid content) and the elastic properties (Vp, Vs and density). The theory of the Sun model was chosen as a key for relating reservoir properties to seismic
: relations were identified between Suns frame flexibility factor (describing the elasticity of the rock frame determined by pore geometry), velocities, densities and porosities. Those relations were compared to the information on sedimentology, diagenesis, structural position and reservoir rock types. Detailed well to
seismic
match enabled estimating a fit-for-purpose average wavelet to be used over the entire field. The fluid substitution of the well logs, log blocking, and the fluid properties made it possible to model the fluid content impact on the
seismic
, and to better understand the impact of peg-leg multiples still present in the
seismic
data.
The generation of 3D synthetic seismic
based on the static model included the use of the relations obtained from the rock physics model, the well log blocking and the derived
seismic
wavelet. The match between real and modeled synthetic
seismic
indicates how well the parameters in the static model describe the reservoir, and the relevance of the variables (rock & fluid properties, layering, and wavelet) included in the forward
modeling
. The
seismic
match was improved by iteratively fine tuning the different variables used to generate the synthetic
seismic
. The optimization process highlighted which variables control the
seismic
response. These were subsequently used to define the stochastic parameters and the uncertainties in the probabilistic
seismic
inversion. The inversion algorithm used utilizes the constrained static model as input and can invert to any of the variables present in it. Therefore it was possible to obtain probability distributions for porosity, fluid saturation and rock rigidity in any location of the reservoir that match the
seismic
.
The workflow was applied to the Bab field in Abu Dhabi, UAE. The resulting static model reflects more accurately the lateral variability of the rock properties while preserving vertical resolution.