Structural and stratigraphic interpretation
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| 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 |
By using the techniques we learned in interpretation of 3-D seismic data, we now interpret the image volume from 3-D prestack depth migration — structural intepretation based on picking a set of depth horizons and stratigraphic interpretation based on amplitude manipulation. Figure 10.9-28 shows six depth horizons that coincide with the geologic markers in the area. The top three horizons, DH1, DH2, and DH3, were delineated largely by using the seed detection technique that involves connecting neighboring voxels with amplitudes that are within a specified range (interpretation of 3-D seismic data). The bottom three horizons, DH4, DH5, and DH6, were delineated by line-based interpretation that involves creating a set of horizon strands along selected inlines and crosslines.
The effect of extensional tectonism is evident on the top three depth horizons. Note in particular the series of faults across the lowlands indicated in green. Examine the depth horizons in reverse order, starting with DH6 and ending with DH1, to reconstruct the structural evolution of the area. In the beginning, there was an erosional surface cut by a deep channel as seen on horizon DH6. There may have been a period of compressional tectonism that gave rise to the gently folded surfaces in the lowlands portion of horizons DH5 and DH4. Then, a reversal from compressional tectonism to extensional tectonism began to cause subsidence of the basin, which in turn gave rise to the formation of the series of faults parallel to the ancient shoreline. The highlands indicated by the orange on all horizons have remained as hiatus until the geologic times approximately coincident with the age of the overburden above horizon DH1.
Now split the image volume into subvolumes that represent individual depositional units as shown in Figure 10.9-29. The extensional fault patterns are observed on the top surfaces of these subvolumes down to horizon DH4. To investigate the interior of each of these depositional units, cut them into thin slices as shown in Figure 10.9-30a. Then, apply transparency (interpretation of 3-D seismic data) to each of the thin slices to identify depositional features of interest. Note the presence of a stream with its traverse orthogonal to the fault patterns. Also shown in Figure 10.9-30b is the map view of the thin slice that exhibits the stream channel disrupted by the faults.
Figure 10.9-26 Part 1: Selected inlines from the image volume in depth derived from the stack of the image gathers as in Figure 10.9-25 that were created by 3-D prestack depth migration of the data as in Figure 10.9-5b using the final 3-D velocity-depth model as in Figure 10.9-23.
Figure 10.9-26 Part 2: Selected inlines from the image volume in depth derived from the stack of the image gathers as in Figure 10.9-25 that were created by 3-D prestack depth migration of the data as in Figure 10.9-5b using the final 3-D velocity-depth model as in Figure 10.9-23.
Figure 10.9-26 Part 3: Selected inlines from the image volume in depth derived from the stack of the image gathers as in Figure 10.9-25 that were created by 3-D prestack depth migration of the data as in Figure 10.9-5b using the final 3-D velocity-depth model as in Figure 10.9-23.
Figure 10.9-26 Part 4: Selected inlines from the image volume in depth derived from the stack of the image gathers as in Figure 10.9-25 that were created by 3-D prestack depth migration of the data as in Figure 10.9-5b using the final 3-D velocity-depth model as in Figure 10.9-23.
Figure 10.9-26 Part 5: Selected inlines from the image volume in depth derived from the stack of the image gathers as in Figure 10.9-25 that were created by 3-D prestack depth migration of the data as in Figure 10.9-5b using the final 3-D velocity-depth model as in Figure 10.9-23.
Figure 10.9-27 Part 1: Selected crosslines from the image volume in depth derived from the stack of the image gathers as in Figure 10.9-25 that were created by 3-D prestack depth migration of the data as in Figure 10.9-5b using the final 3-D velocity-depth model as in Figure 10.9-23.
Figure 10.9-27 Part 2: Selected crosslines from the image volume in depth derived from the stack of the image gathers as in Figure 10.9-25 that were created by 3-D prestack depth migration of the data as in Figure 10.9-5b using the final 3-D velocity-depth model as in Figure 10.9-23.
Figure 10.9-27 Part 3: Selected crosslines from the image volume in depth derived from the stack of the image gathers as in Figure 10.9-25 that were created by 3-D prestack depth migration of the data as in Figure 10.9-5b using the final 3-D velocity-depth model as in Figure 10.9-23.
Figure 10.9-27 Part 4: Selected crosslines from the image volume in depth derived from the stack of the image gathers as in Figure 10.9-25 that were created by 3-D prestack depth migration of the data as in Figure 10.9-5b using the final 3-D velocity-depth model as in Figure 10.9-23.
Figure 10.9-28 Part 1: Depth horizon DH1 interpreted from the image volume derived from 3-D prestack depth migration. Selected inlines and crosslines from the image volume are shown in Figures 10.9-26 and 10.9-27, respectively.
Figure 10.9-28 Part 2: Depth horizon DH2 interpreted from the image volume derived from 3-D prestack depth migration. Selected inlines and crosslines from the image volume are shown in Figures 10.9-26 and 10.9-27, respectively.
Figure 10.9-28 Part 3: Depth horizon DH3 interpreted from the image volume derived from 3-D prestack depth migration. Selected inlines and crosslines from the image volume are shown in Figures 10.9-26 and 10.9-27, respectively.
Figure 10.9-28 Part 4: Depth horizon DH4 interpreted from the image volume derived from 3-D prestack depth migration. Selected inlines and crosslines from the image volume are shown in Figures 10.9-26 and 10.9-27, respectively.
Figure 10.9-28 Part 5: Depth horizon DH5 interpreted from the image volume derived from 3-D prestack depth migration. Selected inlines and crosslines from the image volume are shown in Figures 10.9-26 and 10.9-27, respectively.
Figure 10.9-28 Part 6: Depth horizon DH6 interpreted from the image volume derived from 3-D prestack depth migration. Selected inlines and crosslines from the image volume are shown in Figures 10.9-26 and 10.9-27, respectively.
Figure 10.9-29 The subvolume associated with the layer bounded by depth horizons (a) DH1 on top and DH2 at the bottom; (b) DH2 on top and DH3 at the bottom; and (c) DH3 on top and DH4 at the bottom. The depth horizons are shown in Figure 10.9-28 and selected inlines and crosslines from the image volume are shown in Figures 10.9-26 and 10.9-27, respectively.
Figure 10.9-30 (a) A subvolume associated with a 50-m thick slice bounded by depth horizon DH1 on top. The depth horizon is shown in Figure 10.9-28 and selected inlines and crosslines from the image volume are shown in Figures 10.9-26 and 10.9-27, respectively, (b) Map view of the subvolume shown in (a) with opacity removed to enhance the structural and depositional features.
Figure 10.9-31 (a) An inline section from the image volume derived from 3-D prestack depth migration with the interpretation of the top and base of the deltaic depositional sequence. Other selected inlines and crosslines from the image volume are shown in Figures 10.9-26 and 10.9-27, respectively. (b) A close-up view of a crossline section with the horizon strands representing the sublayers associated with the deltaic sequence.
Figure 10.9-32 Top and base of the deltaic sequence interpreted from the image volume derived from 3-D prestack depth migration.
Figure 10.9-33 Selected inline cross-sections of the deltaic sequence with its top and base shown in Figure 10.9-32.
Figure 10.9-34 (a) The subvolume associated with the deltaic sequence extracted from the image volume derived from 3-D prestack depth migration using the top and base surfaces shown in Figure 10.9-32, (b) an inline cross-section of the subvolume in (a).
Figure 10.9-3 A time-with-depth workflow used in the case study presented in 3-D structural inversion applied to seismic data from the Northeast China.
As indicated in Figure 10.9-3, the seismic pathway we followed from phases 1 through 5 in this case study should lead us to constructing a model for the reservoir. Begin with a detailed delineation of the top and base of the deltaic sequence that represents the reservoir unit shown in Figure 10.9-31a. Structural interpretation of the image volume derived from 3-D prestack depth migration (Figures 10.9-26 and 10.9-27) yields the top and base surfaces shown in Figure 10.9-32. Then, define the interior geometry of the reservoir by splitting the deltaic sequence bounded by the two surfaces shown in Figure 10.9-32 into a set of thin layers as shown in Figure 10.9-31b. Cross-sections of the reservoir unit along selected inline traverses after sublayering are shown in Figure 10.9-33.
Next, extract the subvolume associated with the reservoir unit from within the image volume derived from 3-D prestack depth migration (Figure 10.9-34). You may want to use the subvolume to estimate a set of seismic attributes. The sublayers (Figure 10.9-33) then are populated, based on any available well data, and results of the analysis of seismic attributes, such as amplitude variation with offset (analysis of amplitude variation with offset) and acoustic impedance (acoustic impedance estimation), by the petrophysical properties of the reservoir unit, such as, porosity, permeability and fluid saturation, all of which are allowed to vary laterally within each of the sublayers. In the final chapter, we shall review prestack and poststack amplitude inversion methods to infer petrophysical properties of reservoir rocks from seismic data as an aid to reservoir modeling.
See also
- 3-D structural inversion applied to seismic data from the Northeast China
- 3-D DMO processing
- 3-D prestack time migration
- From RMS to interval velocities
- Structural inversion
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