As we have applied three different migration algorithms to three velocity modeling, we can compare the results to see which time migration algorithm on which velocity model gives the accurate and more explicit information about the Magruder fault while we know any minor change in velocity modeling could mainly affect the outcome.
In the 1st velocity model, the image derived from FK-Stolt time migration (Figure 57-a) shows the consistency with the geology of the area. The Kirchhoff time migration produces an image with smoother boundaries but appears to lose the contrast with depth.
The FD time migration algorithms seem to create better images of the subsurface, and they show the faults grow most efficiently by the coalescence of different smaller faults (e.g., Peacock and Sanderson, 1991; Willemse, 1997; Cartwright et al., 1995). So as we see the results obtained from the FD migration with different solutions, the fault appears on the seismic image at 180 ms and its shape shows undulation with a dip angle of 30º south and depth of almost 140 m.
Figure 57-a. F-K time migration of 1st model. Blue circle represents the Magruder fault area.
Figure 57-b. Kirchhoff time migration of 1st model. Blue circle represents the Magruder fault area.
Figure 57-c. FD-15 time migration of 1st model. Blue circle represents the Magruder fault area.
Figure 57-d. FD-45 time migration of 1st model. Blue circle represents the Magruder fault area.
Figure 57-e. FD-65 time migration of 1st model. Blue circle represents the Magruder fault area.
Figure 57-f. Depth section of the FD-15 time migrated of 1st model.
Blue circle represents the Magruder fault area.
In the 2nd velocity model, while we picked the high-velocity events for constructing the velocity model, the image that we obtained from FK-Stolt time migration didn’t show us the precise shape of the fault. The FD time migration algorithms appear to produce the images with more details about the subsurface. Also, the 45-degree solution provides the more accurate shape of the fault while it doesn’t distort the information of the deeper layers.
In addition, in the depth section, the fault’s location is at almost 120 m (Figure 58).
Figure 58-a. F-K time migration of 2nd model. Blue circle represents the Magruder fault area.
Figure 58-b. Kirchhoff time migration of 2nd model.
Blue circle represents the Magruder fault area.
Figure 58-c. FD-15 time migration of 2nd model. Blue circle represents
the Magruder fault area.
Figure 58-d. FD-45 time migration of 2nd model. Blue circle represents the Magruder fault area.
Figure 58-e. FD-65 time migration of 2nd model. Blue circle represents the Magruder fault area.
Figure 58-f. Depth section of the Kirchhoff time migrated of 2nd model.
Blue circle represents the Magruder fault area.
In the 3rd velocity model, the image that we obtained from FK-Stolt time migration shows us the better shape of the fault, and it also gives us the information about the other probable geological features. The Kirchhoff migration provides the smoother boundaries, but it doesn’t show the dip angle of the fault. The FD time migration algorithms appear to produce the images that provide more information about subsurface, while they tend to split the fault line to small segments, and it seems that the obtained results are over migrated which decreases the depth location of the fault to almost 130 m with the dip angle of 25º south.
Figure 59-a. F-K time migration of 3rd model. Blue circle represents the Magruder fault area.
Figure 59-b. Kirchhoff time migration of 3rd model.
Blue circle represents the Magruder fault area.
Figure 59-c. FD-15 time migration of 3rd model. Blue circle represents the Magruder fault area.
Figure 59-d. FD-45 time migration of 3rd model. Blue circle represents the Magruder fault area.
Figure 59-e. FD-65 time migration of 3rd model. Blue circle represents the Magruder fault area.
Figure 59-f. Depth section of the F-K time migrated of 3rd model.
Blue circle represents the Magruder fault area.
Our trials showed that the depth migration results in distortion of the time-migrated images which is consistent with the geology of the area.
In addition, according to the results of the time migration algorithms on three
velocity modeling, we can conclude that the first velocity model gives us the better result as we picked
the Vrms in short time step. The presence of high-velocity layer in the first 100 ms is due to the presence of coastal plain sediments with the velocity of 2050-2256 m/s. Then we would see sudden decreasing in the velocity due to the presence of Pliocene unit containing the sand and shale in the 1st layer.
The velocity range for sand varies between 1900 m/s-1500 m/s.At 140 ms, we would observe the probable Magruder fault that causes an increase in velocity with depth.
The layer of shale would be observable at 410 ms with the velocity range of 2110 m/s- 1940 m/s.
At 580 ms, the 2nd layer is observed which belongs to Eocene which means the contact would be noticeable at this time. Sand and shale are also the major materials of this unit and we would see that the velocity range for shale varies between 1963 m/s-2246 m/s and for sand it varies between 1926 m/s -1635 m/s.
As the applied migration algorithms do not create significant improvement in the image quality, we would like to use different and novel optimization algorithms on this velocity model in future in order to improve the existing migration algorithms in the sense of increasing the accuracy of the result while providing more information about the subsurface stratigraphic and structural features.
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VITA MOONES ALAMOOTI
No1, Brevard Hall, University of Mississippi 38677, University, Mississippi (662) 202-7737 • [email protected]
EDUCATION
M.Sc., Engineering Geology, University of Mississippi, May 2018
Thesis: A Comparative Case Study of Reflection Seismic Imaging Method B.Sc., Geology, University of Tehran, July 2010
Teaching Assistant in “Rock Mechanics”. Spring Semester of 2016
Ranked top 0.5 % of Iran’s nationwide university entrance exam for Bachelor of Engineering and Science among more than 400,000 participants.
2015 Summer Research Assistantship Awards
Selected as the first 10 graduate students among more than 120 graduate students in the first round 3 Minutes Thesis Competition in 2015
2017 Summer Research Assistantship Awards
Selected as the first 5 graduate students among more than 120 graduate students in the first round in 3 Minutes Thesis Competition in 2017
CONFERENCE ABSTRACTS AND POSTERS
Symposium on the Application of Geophysics to Engineering and Environmental Problems(SAGEEP), March 2017
Geological Society of America (GSA) Section Meetings, March 2017
Alamooti, M. & Aydin, A. (2017), Advances in Full Waveform Modeling, Inversion, and Imaging II Posters session at 2017 Fall Meeting, AGU, New Orleans, LA, 11-15 Dec.
81st Annual Mississippi Academy of Sciences Meeting, February 2018.
CONFERENCE PAPERS
Alamooti, M. & Aydin, A. (2017, September). Seismic Data Processing, presented at engineering graduate seminar, University of Mississippi
Alamooti, M. & Aydin, A. (2017, September). A Comparative Case Study of Reflection Seismic Imaging Method. Paper presented at the annual meeting of the Geological Society of America, Seattle, Washington.