Application of seismic interferometry to seismic
data over a landfill: modelling studies
Laura Amalia Konstantaki
1, Deyan Draganov
2, Timo Heimovaara
1, Ranajit Ghose
21Section of Geoengineering, Dept. of Geoscience and Engineering, Delft Univ. of Technology, The Netherlands 2Section of Applied Geophysics, Dept. of Geoscience and Engineering, Delft Univ. of Technology, The Netherlands
e-mail: l.a.konstantaki@tudelft.nl
I. INTRODUCTION
For the last decades, municipal solid landfills have been an intense target of investigation for Dutch organizations. Problems such as formed methane gas and leachate emissions need to be adequately addressed. One of the main goals is achieving a fast stabilization of the landfill in order to minimize the aftercare period and the hazards associated with landfills. To achieve this, a good understanding of the chemical and physical processes taking place in the landfill needs to be established. A key factor to optimize the stabilization techniques is to characterize the heterogeneity of the system (e.g. Reichel et al., 2007). Electrical resistivity and induced polarization methods have so far been useful to characterize the chemical or ionic processes in the landfill, but they generally have limited success in resolving accurately the heterogeneities within the landfill, and hence the leachate and gas flow paths (e.g. Jolly et al., 2011). In this vein, high-resolution seismic surveys can be useful.
In the past, shallow seismic surveys have been conducted on landfills, but they have shown inadequate results due to noise and heavy scattering from diffractor-like objects (e.g. De Iaco et al., 2003). However, high-resolution seismics have the potential to provide a high-definition image of the landfill and the scatterers in it. The latter have a major influence on the possible flow paths. The change of the scatterers’ character-istics with the maturation of the landfill results in changes of the flow paths. Time-lapse seismic surveys can identify such changes. But the presence of multitude of scatterers impedes the utilization of the advanced 4D seismic techniques, as these techniques are based on single-scattering assumption. Another problem for time-lapse monitoring is the non-repeatability in seismic source positioning. To address these problems, we propose to apply seismic interferometry (SI) using controlled seismic sources.
II. THE RESULTS
The municipal landfills present a favorable case for appli-cation of SI with controlled sources, as they contain many scatterers. Figure 1(a) shows a model that mimics a landfill body. It is 100 m long and 25 m deep. We have considered using seismic shear waves for our synthetic study, because shear waves offer higher resolution in soft soils and the shear-wave velocity (VS) is directly linked to the stiffness. VS of
the background medium increases with depth from 200 m/s at the surface to 219.84 m/s at 25 m depth (representing compacting sand). The landfill contains 48 scatterers of size varying between 0.5 m to 1.8 m in height and 0.35 m to 3.89 m in length, randomly distributed in space and composed of 3 kinds of material e.g., plastic, glass, and metals, with VS 440
m/s, 1000 m/s and 1300 m/s, respectively. 0 5 10 15 20 25 D e p th (m) 0 5 10 15 20 25 D e p th (m) 260 280 300 320 340 360 Horizontal distance (m) 260 280 300 320 340 360 Horizontal distance (m) (a) (b) (c)
Fig. 1. (a) The landfill model used. (b) Subsurface image obtained from
migration of the recorded active source data. (c) Subsurface image obtained from migration of the retrieved SI reflection data. The migration results have been gained for visualization purposes. The red ellipses indicate the location of the subsurface scatterers.
We use the landfill velocity model in a seismic forward modelling (Thorbecke and Draganov, 2011) with a split spread geometry. We use 120 horizontal-component receivers divided in 5 cables each of 24, with a receiver spacing of 0.5 m. The first source is positioned at 226 m and the first receiver at 228 m. When the source position passes 4 cable lengths (96 receivers), the passed cables are moved to the back of the line. The modeled common-source gathers have their direct ar-rivals muted. They are then prestack depth-migrated using the correct landfill velocity. Figure 1(b) shows the subsurface
image with the superimposed scatterers. We see that the shallower scatterers are imaged, but at depth the image is not that clear. There is focused energy, but we see that it is not at positions of the scatterers. Using only this image, we can draw wrong conclusions about the structure of the landfill.
We apply SI by cross-correlation to the muted common-source gathers to obtain virtual common-common-source gathers with spacing between the virtual sources of 0.5 m (note that the real source spacing is 2.0 m). Obtained virtual gathers are normalized to their maximum amplitude. Further, we applied wavelet deconvolution to compensate for pulse-broadening due to the correlation and then band-pass filtered to suppress energy outside the frequency band of the original signal. We then use the same migration algorithm like for the active data. The result is shown in Figure 1(c). Comparing this result (c) with the result of active source seismic imaging (b), we see that in (c) the shallower scatterers are better defined. The SI dataset contained about five times more traces than the active one, so its imaging capabilities are better. Furthermore, we see that some of the focused deeper energy in the active-source image is not as focused as in the SI image. This means that the two images can be used in a complementary fashion to distinguish between the physical scatterers and the artifacts due to prevalent imaging algorithm (which assumes single scattering). Focused energy present in both images represents physically meaningful scatterers.
0 5 10 15 20 25 D e p th (m) Distance [m] D e p th [ m] 260 280 300 320 340 360 Horizontal distance (m) 0 5 10 15 20 25 D e p th (m) 260 280 300 320 340 360 Horizontal distance (m) (a) (b) (c) (d)
Fig. 2. Images of the landfill obtained from prestack depth migration applied to (a) the original active source dataset, b) the repeat active source dataset with source non-repeatability, (c) the original SI dataset and (d) the repeat SI dataset obtained from the repeat active source dataset with source non-repeatability. No visualization gaining is applied to the images.
Next, we test the two methods for monitoring time-lapse changes in the landfill. Acquisition reproducibility between two measurement campaigns is a key requirement in time-lapse seismics. Source non-repeatability is a notorious
prob-lem. Because of this we model a second active dataset, in which the source positions have random positioning errors varying between 0 and 1 m compared to the positions of the sources in the original survey. No changes in the landfill have taken place. To the new dataset we apply the same processing like the original one. Figures 2(a,b) show the obtained images for the original and the repeat survey using the active datasets. We can observe that due to the sources mispositioning, the scatterers in the image from the repeat survey are not well-focused and that a new scatterer-like event has appeared at the shallower part at horizontal distance of 310 m and depth of 7 m. On the other hand, the focused artifacts are quite well imaged again. Taking the difference between the two images, as is standard in time-lapse monitoring, would result in a big difference. This can lead to the wrong conclusion that there have been changes in the landfill body. Comparing the images obtained from the SI datasets in Figures 2(c,d) from the active datasets used for (a) and (b), respectively, we can see that the repeatability of the imaged scatterers is much better. The difference panel between these two images would result in much smaller differences and thus would give us the possibility to monitor the landfill for real changes.
III. CONCLUSIONS
The multitude of scatterers typically present in a municipal landfill can be a problem in usual seismic reflection surveys, which are based on single-scattering assumption. Seismic interferometry (SI) takes advantage of significant multiple scattering that takes place in such a medium. Because of the increased number of sources and hence a denser illumination of the subsurface, the scatterers are better imaged when SI is applied to active source data. Also some of the deeper scatterers appear to be visible for the first time. Our results indicate that the problem due to source irreproducibility in time-lapse seismic imaging of the landfill can greatly be alle-viated by application of SI to active-source seismic imaging. These initial synthetic results illustrate the strong potential of SI in seismic imaging, characterization and monitoring of the municipal landfill, as a supplement to electrical and IP studies.
REFERENCES
De Iaco, R., Green, A.G., Maurer, H.R., Horstmeyer, H., 2003: A combined seismic reflection and refraction study of a landfill and its host sediments. Journal of Applied Geophysics,v.52, p.139-156.
Jolly, J.M., Beaven, R.P., Barker, R.D., 2011: Resolution of electrical imaging of fluid movement in landfills. Waste and resoursce Management,v.164, p.79-96.
Reichel, T., Ivanova, L.K., Beaven,R.P., Haarstrick,A., 2007: Modelling decomposition of MSW in a consolidating anaer-obic reactor. Environmental Engineering Science., v.24(8). Thorbecke, J., Draganov, D., 2011: Finite-difference modelling
