Seismic facies model

Once a three-dimensional seismic facies model has been generated and calibrated with well data, the next step consists in translating the facies model more efficiently to the simulation domain. The challenge faced is to minimize the manual work and to preserve as much as possible the detailed representation carried by the three-dimensional seismic facies model in order to improve the seismic to simulation workflow. 

Fig. 16. [Reproduced in colour in Plate 26 on page 440.] Stratal slice of the seismic facies model 8 ms above the base of the Grane reservoir. The dark blue and light blue facies represent flat continuous seismic facies and are caiibrated as sands. The yellow and red facies represent discontinuous and dipping seismic facies and are calibrated as shale prone deformation featmes as indicated by the Gamma Ray log along a horizontal well.

A three-dimensional seismic facies model could be built from supervised classification of seismic textures that captures the detailed structural framework of the reservoir and its complex architecture. 

Summary. A new seismic to simulation workflow is proposed, where the aim is the reduction of the overall turn-around time, from seismic data acquisition to reservoir model building and simulation. To this end, new automated procedures axe established firstly, for discriminating seismic data into three-dimensional seismic facies, and secondly, for building a voxel-based reservoir model. 

In the second part, automated voxel grid extraction for reservoirs is explained. The required input is the voxel size together with the top and bottom horizons delimiting the reservoir extents. The calibrated three-dimensional seismic facies are then used to associate each voxel with porosity and permeability values. This last automated step results in a voxel-based reservoir model. 

These seismic facies geobodies, whether they are sedimentary, structural, diagenetic, or fluid related constitute an attempt to identify, isolate and extract geological/rock physical objects or properties in one single coherent modelling entity. The system level allows interactive visualization and analysis of these geobodies and their more efficient transfer to the reservoir model. 

Fig. 6. [Reproduced in colonr in Plate 19 on page 434.] Classification of seismic facies based on texture attributes defines a geological/structural model. Using iterative and hierarchical classification capability, seismic facies can be calibrated and assigned to Uthology and fluids using well data or another set of attributes such as amplitude-based, or AVO data.

It is shown in the following subsections that combining the voxel model approach, introduced hereafter, together with three-dimensional seismic facies results fulfil all of the above specifications. 

Automated Grid and Fault Extraction, Seismic Facies Classification. The first requirement for building a reservoir model is to determine its extents and characteristics. 

Fig. 12. [Reproduced in colour in Plate 22 on page 436.] (A) The facies model captures implicitly discontinuities related to faults as shown with the distribution of texture-based seismic facies in three dimensions within the hanging wall and foot wall of a fault. The voxel grid geometry defined for the reservoir model is superimposed on the facies model to show how the facies will be associated to the voxels. The facies being located in the centre of the voxel is used to define the property of the cell. (B) Distribution of the facies within the voxel grid geometry.

Finally, the voxel model is flexible and can be tuned to provide the best representation of the heterogeneity of the reservoir. As mentioned in the automated geometry extraction step, this is achieved by comparing the size of the voxel with the size of 3D seismic facies. Yet when more than one type of... 

Facies Model and Calibration with Well Data. While the comparison of PP versus PS seismic image seems to indicate a potential fluid contact in the western part of the sand lobe fitting the observed OWC at well location, additional information, such as VP/VS ratio (the ratio of velocities of P-wave to S-wave, and gives equivalent information as measurements of Poisson s ratio), density logs, and porosity logs have confirmed the complexity of the... 

Due to the observations and because of the small voxel size chosen, the inclusion of faults in the reservoir model does not appear as a priority for this case study. As mentioned earher and as seen in Figure 12, the detailed heterogeneities of the reservoir captured with the tree-dimensional seismic facies are brought forward to the reservoir voxel model thereby implicitly modelling the discontinuities. 

The effect of three-dimensional seismic facies on the voxel model were evaluated by using two case studies. On the one hand, a voxel model based on acoustic impedance only, and on the other hand a voxel model based on both acoustic impedance and three-dimensional seismic facies were built. 

Fig. 18. [Reproduced in colour in Plate 27 on page 441.] Comparison of porosity at the top of the reservoir for the two voxel models, (a) Voxel model based on acoustic impedance only, (b) Voxel model based on acoustic impedance and three-dimensional seismic facies results.

The computer used for simulation is a Sunblade 1000 with two CPUs at 750 MHz and 4 gigabytes memory. About 30 CPU hours were needed to run a three phases streamline simulation for 4800 production days. Figure 20 (a) shows a three-dimensional view of the porosity distribution obtained for the voxel model based on acoustic impedance and three-dimensional seismic facies results. Figure 20 (b) shows the initial oil saturation together with the location of the seven wells used for the simulation. 

A new methodology for building reservoir models from seismic data based on three-dimensional seismic facies has been demonstrated on the Grane field. This new approach enables a workflow from seismic domain to simulation domain, by bridging the two close together through the voxelization process. 

A property voxelization step allowed to populate the model with rock properties based on (1) empirical models linking porosity and permeability to acoustic impedance, or (2) empirical models and additional constraints given by the calibration of the seismic facies with well data. 

This method from seismic to simulation exploiting three-dimensional seismic facies and voxelization process opens new perspectives on reservoir model building, multiple scenarios realizations and faster or right time model up>-dating. 

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