Volume-based interpretation

**Seismic Data Analysis**
Series	Investigations in Geophysics
Author	Öz Yilmaz
DOI	http://dx.doi.org/10.1190/1.9781560801580
ISBN	ISBN 978-1-56080-094-1
Store	SEG Online Store

Interpretation of 3-D seismic data is based on one of the following two strategies:

Image in time, interpret in time to create a set of time structure maps, and then perform time-to-depth conversion to create the corresponding set of depth structure maps, or
Image in depth and interpret directly in depth to create a set of depth structure maps.

Whatever the strategy, the resulting depth structure maps are calibrated to well data.

We demonstrated the first strategy for interpretation in interpretation of 3-D seismic data. We now demonstrate the second strategy for interpretation. Figure 10.8-21 shows selected 3-D views of the image volume from 3-D prestack depth migration of the data as in Figure 10.8-19 in the inline direction, and Figure 10.8-22 shows selected 3-D views of the image volume in the crossline direction as in Figure 10.8-20. Begin the structural interpretation session by 3-D visualization of the image volume in depth to understand and characterize the subsurface structural model. Combine the visualization of the image volume in the inline and crossline directions with the the scanning of the depth slices (Figure 10.8-23). Note that the structural model is based on wrench tectonism that has caused the intensive faulting and folding.

Figure 10.8-19 Part 1: Selected inline sections from the image volume derived from 3-D prestack depth migration using the updated velocity-depth model based on the layer velocities and reflector geometries shown in Figure 10.8-12.
Figure 10.8-19 Part 2: Selected inline sections from the image volume derived from 3-D prestack depth migration using the updated velocity-depth model based on the layer velocities and reflector geometries shown in Figure 10.8-12.
Figure 10.8-19 Part 3: Selected inline sections from the image volume derived from 3-D prestack depth migration using the updated velocity-depth model based on the layer velocities and reflector geometries shown in Figure 10.8-12.
Figure 10.8-20 Part 1: Selected crossline sections from the image volume derived from 3-D prestack depth migration using the updated velocity-depth model based on the layer velocities and reflector geometries shown in Figure 10.8-12.
Figure 10.8-20 Part 2: Selected crossline sections from the image volume derived from 3-D prestack depth migration using the updated velocity-depth model based on the layer velocities and reflector geometries shown in Figure 10.8-12.

By using the seed detection technique (interpretation of 3-D seismic data), we capture a set of surface patches for each of the depth horizons to be interpreted. Where seed detection fails, as in the complex fault zones, the surface paths are complemented with the horizon strands along the selected inlines and crosslines derived from line-based interpretation. The combination of seed detection and line-based interpretation produce a set of control points for each depth horizon as shown in Figures 10.8-24a through 10.8-29a. The control points are then used to create a complete surface for each horizon by grid-fitting (Section J.5) as shown in Figures 10.8-24b through 10.8-29b. The sixth horizon, which is the deepest, shown in Figure 10.8-29b is deeper in some areas than the maximum depth (4 km) associated with the image volume from 3-D prestack depth migration (Figures 10.8-21 and 10.8-22). All six depth horizons are shown in the 3-D view of Figure 10.8-30.

Figure 10.8-21 Subvolumes of the image volume from 3-D prestack depth migration viewed along the inline direction.
Figure 10.8-22 Subvolumes of the image volume from 3-D prestack depth migration viewed along the crossline direction.
Figure 10.8-23 Selected depth slices of the image volume from 3-D prestack depth migration as in Figures 10.8-22 and 10.8-23.
Figure 10.8-24 Interpretation of depth horizon DH1 from the image volume as in Figures 10.8-22 and 10.8-23: (a) map view of picks created from a combination of seed detection and line-based interpretation, (b) the surface in depth created by gridfitting the control points in (a). The displays in (a) and (b) are color-coded independently.
Figure 10.8-25 Interpretation of depth horizon DH2 from the image volume as in Figures 10.8-22 and 10.8-23: (a) map view of picks created from a combination of seed detection and line-based interpretation, (b) the surface in depth created by gridfitting the control points in (a). The displays in (a) and (b) are color-coded independently.
Figure 10.8-26 Interpretation of depth horizon DH3 from the image volume as in Figures 10.8-22 and 10.8-23: (a) map view of picks created from a combination of seed detection and line-based interpretation, (b) the surface in depth created by gridfitting the control points in (a). The displays in (a) and (b) are color-coded independently.
Figure 10.8-27 Interpretation of depth horizon DH4 from the image volume as in Figures 10.8-22 and 10.8-23: (a) map view of picks created from a combination of seed detection and line-based interpretation, (b) the surface in depth created by gridfitting the control points in (a). The displays in (a) and (b) are color-coded independently.
Figure 10.8-28 Interpretation of depth horizon DH5 from the image volume as in Figures 10.8-22 and 10.8-23: (a) map view of picks created from a combination of seed detection and line-based interpretation, (b) the surface in depth created by gridfitting the control points in (a). The displays in (a) and (b) are color-coded independently.
Figure 10.8-29 Interpretation of depth horizon DH6 from the image volume as in Figures 10.8-22 and 10.8-23: (a) map view of picks created from a combination of seed detection and line-based interpretation, (b) the surface in depth created by gridfitting the control points in (a). The displays in (a) and (b) are color-coded independently.
Figure 10.8-30 All six surfaces in depth as in Figures 10.8-24 through 10.8-29. Each surface is color-coded independently.

Stratigraphic interpretation uses an amplitude manipulation technique based on removal of opacity (interpretation of 3-D seismic data). Application of this technique to the depositional unit bounded by surface DH3 at the top and DH4 at its base (Figure 10.8-31a) leads to the discovery of an ancient channel (Figure 10.8-31b). This buried channel within the depositional unit of Figure 10.8-31a resembles the recent channel system at the water bottom which is dramatically manifested by the depth slices shown in Figure 10.8-32.

A close-up view reveals the disruption of the buried channel by the faulting associated with the wrench tectonism in the area (Figure 10.8-33a). By using the subvolume detection (interpretation of 3-D seismic data), the channel can be isolated as shown in Figure 10.8-33b. The color-coded view of the channel shows that elevation changes exist along the channel caused by the faulting that has occurred after the formation of the channel itself (Figure 10.8-34a). After its subvolume detection, the channel can be extracted from the volume associated with the depositional unit (Figure 10.8-31a) and viewed in combination with the surface that corresponds to the base of the unit (Figure 10.8-34b). The objective is to gain a complete understanding of the stratigraphic prospect represented by the channel in relation to the subsurface structural model.

Finally, the results of the structural interpretation (Figures 10.8-24b through 10.8-29b) are combined to build a solid earth model. Figure 10.8-35b shows the layer boundaries represented by the depth horizons that were derived from the structural interpretation. Each layer is then represented by a solid volume bounded by these surfaces as shown in Figure 10.8-35. Explosion of the entire solid model facilitates viewing of the individual depositional units represented by the solid segments (Figure 10.8-36). The solid segment associated with the zone of interest can be subsequently populated by the seismically derived petrophysical properties, which are constrained by the well data, to derive a reservoir model.

Figure 10.8-31 (a) The depositional unit bounded by surface DH3 (as in Figure 10.8-26) at the top and bounded by surface DH4 (as in Figure 10.8-27) at the bottom; the subvolume has been extracted from the image volume as in Figures 10.8-22 and 10.8-23, (b) the same subvolume as in (a) with the opacity removed.
Figure 10.8-32 Selected shallow depth slices of the image volume from 3-D prestack depth migration as in Figures 10.8-22 and 10.8-23.
Figure 10.8-33 (a) Close-up view of the subvolume as in Figure 10.8-31b, (b) seed detection applied to the lower portion of the channel.
Figure 10.8-34 (a) The same subvolume as in Figure 10.8-33b with the channel color-coded in depth, (b) the same channel as in (a) displayed with the base surface DH4 of the depositional unit as in Figure 10.8-31a.
Figure 10.8-35 (a) All six surfaces in depth as in Figures 10.8-24 through 10.8-29; (b) solid model created from the depth horizons in (a).
Figure 10.8-36 Explosion of the solid model shown in Figure 10.8-35b.