|Publisher||Society of Petroleum Engineers||Language||English|
|Content Type||Conference Paper|
|Title||Construction of a Stochastic Geological Model Constrained by High-Resolution 3D Seismic Data - Application to the Girassol Field, Offshore Angola|
O. Lerat, P. Nivlet, B. Doligez, N. Lucet, and F. Roggero, IFP; P. Berthet,
Total; F. Lefeuvre, Total E&P Borneo; and
SPE Annual Technical Conference and Exhibition, 11-14 November 2007, Anaheim, California, U.S.A.
2007. Society of Petroleum Engineers
|6 Reservoir Description and Dynamics
6.1 Reservoir Geology and Geophysics
The first and critical step of this approach was the definition of a 3D grid of facies proportions from 3D HR seismic data to constrain the geological modeling process. A novel approach has been developed to account for scale differences between seismic and well data to obtain a detailed geological facies description.
In the second step, geological facies proportions derived from the seismic
facies characterization have been optimized to minimize the differences between
the seismic impedances of the average stochastic model and the real impedances.
In the last step, the truncated Gaussian algorithm has been
This approach was applied successfully to the Girassol field, a complex and faulted turbidite field located offshore Angola. The objective was to build an initial geological model for an innovative history matching workflow integrating 4D seismic data (Roggero et al., ).
Thanks to the exceptionally high resolution of the seismic data, a 3D matrix
of lithofacies proportions has been constructed with a resolution close to that
of standard well logs (metric). Together with variograms, these geostatistical
parameters have been used to generate equiprobable images of the geological
model. Both well data and the seismic constraint are honored. Average sand
proportions and volumes computed from ten realizations are in good agreement
with the average values computed using the seismic constraint. Variability in
the distribution of geological facies has been quantified and can be related to
the uncertainty of the seismic constraint. This uncertainty has been reduced in
the history matching process by introducing more deterministic
The understanding of deep offshore reservoir architecture relies to a large extent on seismic interpretation combined with knowledge from outcrop analogs (Beydoun et al., ; Sikkema and Wojcik, ; Eschard et al., ; Joseph et al., ). Seismic information can be used to constrain initial facies models in various ways (Dubrule, ). The integration of seismic data in geostatistical facies models can be direct. In this case, the seismic information is integrated during the estimation/simulation phase, using external drift, coestimation, cokriging, and their variations. Another approach consists of an indirect integration starting with a preliminary estimation of seismic and geological attributes, which is followed by the simulation phase. In this case, 2D maps of seismic facies or quantitative attributes are often used (Doligez et al., [10, 11]; Fournier et al., ).
A specific workflow has been developed for the geological modeling of the Girassol field, to integrate quantitatively a 3D constraint of facies proportions based on the interpretation of the high-resolution 3D seismic data. The objective is to prepare the integration of 4D seismic data to update the geological model. This final phase is based on an innovative history matching methodology, as presented by Roggero et al. .
|File Size||1,491 KB||16|