Prestack land data examples

The hybrid adaptive subtraction technique has been tested on few shot records from a land data survey. My goal is to subtract multiple models from shot records. The preprocessing is described in () and the goal is to attenuate surface-related multiples only. Note that for these shot records primaries and multiples are strongly correlated.

To better accomodate for the spatial variability of the data, I do not estimate one filter only but many filters. Instead of estimating filters in patches, I estimate a bank of non-stationary time domain (t, x) filters for both 313#313 and 332#332 (, ).

Figures a and a show the land data and the multiple model respectively. Figures b and b display the estimated signal and noise respectively with the standard approach whereas Figures c and c show the estimated signal and noise with the hybrid approach. The hybrid subtraction improves the noise subtraction at far offsets. It also preserves the signal better as illustrated in Figure c around 1.4 seconds.

A different shot record is processed in Figure . The corresponding noise model and estimated multiples are displayed in Figure . The same conclusions hold true.

A more interesting shot record with its multiple model are shown in Figures a. In this example, the multiple attenuation is greatly improved with the hybrid approach.

 

comp_0
Figure 3 (a) Input data. (b) Estimated signal with the standard approach. (c) Estimated signal with the hybrid adaptive subtraction technique. The strong primary at 1.4 seconds is better preserved with the hybrid adaptive subtraction.

 

comp2_0
Figure 4 (a) Multiple model for the data in Figure . (b) Estimated noise with the standard approach. (c) Estimated noise with the hybrid adaptive subtraction technique. Far offset events are better subtracted.

 

comp_1
Figure 5 Another shot record. (a) Input data. (b) Estimated signal with the standard approach. (c) Estimated signal with the hybrid adaptive subtraction technique.

 

comp2_1
Figure 6 (a) Multiple model for the data in Figure a. (b) Estimated noise with the standard approach. (c) Estimated noise with the hybrid adaptive subtraction technique.

 

comp_4
Figure 7 Another shot record. (a) Input data. (b) Estimated noise with the standard approach. (c) Estimated noise with the hybrid adaptive subtraction technique.

 

comp2_4
Figure 8 (a) Multiple model for the data in Figure a. (b) Estimated noise with the standard approach. (c) Estimated noise with the hybrid adaptive subtraction technique. The hybrid adaptive subtraction approach attenuates more multiples. Far offset events are better subtracted too.

The land data examples illustrate the efficiency of the hybrid approach when noise and signal are correlated. In the next section I discuss some limitations of the method and illustrate them with a marine data example.