next up previous [pdf]

Next: Encoded data test Up: Examples Previous: Experiment setup

Dip estimation

rtm12 dip1 rtm32 dip3
rtm12,dip1,rtm32,dip3
Figure 3.
Dip estimation from migration images. (a) RTM with initial velocity; (b) local dip map estimated from (a), which will be used for the first 30 iterations; (c) third RTM with updated velocity after 60 iterations (4-9 Hz data); (d) dip map estimated from (c) and used for the last 20 iterations (10-11 Hz data).
[pdf] [pdf] [pdf] [pdf] [png] [png] [png] [png] [scons]

Before we conduct the FWI with seislet regularization, we need to provide local-dip information for the seislet transform. We estimate the local dip from the RTM image using plane-wave destruction (Fomel, 2002). The dip estimation is computationally inexpensive compared to RTM. With the initial velocity, we can get an initial RTM image as shown in Figure 3a. Though some structures of the image appear at wrong locations, we can get an acceptable local dip map (Figure 3b). We use this initially estimated dip to perform the first 30 iterations (for the first 3 frequencies). After we finish the iterations at 6 Hz, a more accurate velocity is obtained, with which we can get a better RTM image. Then we can estimate the second dip for the next 30 iterations (for the frequencies 7-9 Hz). Similarly, we can perform the third RTM (Figure 3c) after the inversions with 9 Hz frequency, and get a much better dip (Figure 3d), which is used for the last 20 iterations (for the frequencies 10-11 Hz). Comparing Figure 3a and 3c, we can find that the previous position of structures in the central and deep parts has been corrected in the new RTM image. Note that we use un-encoded data to perform RTM in the encoded data test in order to avoid crosstalk artifacts in RTM images. In the noisy data test, the assumed noisy data is used to carry out RTM.


next up previous [pdf]

Next: Encoded data test Up: Examples Previous: Experiment setup

2017-10-09