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Kansas Geological Survey, Open-file Report 2006-24


Decomposition Results of Multi-impact Source Sequence Records

by
Julian Ivanov and Richard D. Miller


KGS Open-file Report 2006-24

for
Rob Huggins
Geometrics, Inc.
2190 Fortune Drive
San Jose, CA 95131
June 2006

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Decomposition Results of Multi-impact Source Sequence Records

Decomposition of wacker input sequence

The decomposition method is a reliable processing approach that provides clear, impulsive first-arrivals with sufficient bandwidth for consistent first-arrival energy picks from coded impulsive sequence data necessary for classic refraction or tomography analysis.

Data preparation

We worked on a 52-channel, 64000-sample multi-impact (wacker) seismic record (number 74) in SEG-2 format, provided by Geometrics. To overcome the 2-byte integer header limitation of the KGS header format, only every other input sample was used. As a result, output data had 32000 samples at 1-ms sampling interval. The impact sequence was recorded on the first trace (channel #24) as non-zero amplitude spikes with a cycle time of around 100 ms and zeros for the rest. During the conversion, amplitudes that were at half-ms times on channel 24 were lost. Thus, information for some of the impacts was lost. To overcome this problem we converted to KGS format (from multi-impact shot record 74) only the first 32766 samples at 0.5-ms sample interval. The resulting trace was 16383 ms long. Thus, all the impact sequence information for the first 32766 samples was accurately retrieved. Then the times were rounded to the nearest millisecond. In such a manner, a 1-ms sampling interval impact sequence was obtained. Amplitudes on all traces were normalized with respect to the largest amplitude in the impulse sequence. Relative impulse times and amplitudes from 155 impacts were retrieved (Table 1, at end of report) and available to decompose the multi-impact record. Forty-eight channels of record 74 were used for the tests discussed here.

Decomposition results analysis

A single-impact shot record (Figure 1a) is compared with the proposed decomposition method of a multi-impact shot record (Figure 1b), which is then compared to the traditional cross-correlation algorithm (Figure 1c). The first-arrivals on the decomposed shot (Figure 1b) match very well the first-arrivals of the single shot record (Figure 1a) and are also better defined than those on the cross-correlated shot (Figure 1c). In addition, the reflections on the decomposed shot (Figure 1b) seem to posses greatest S/N ratio and fidelity compared to the other two records.

Figure 1. a) Regular seismic single-impact shot record 59, b) multi-impact shot record 74 after decomposition using 155 impulses, c) multi-impact shot record 74 after cross-correlation using 155 impulses.

three seismic records

The multi-impact shot has noticeably more low-frequency noise. To reduce the influence of noise, all shot records were filtered with a 20-40 Hz low-cut filter (Figure 2). The decomposed shot gather (Figure 2b) seems to have the better signal-to-noise ratio first-arrivals and reflections. Other low-cut filters were tested to reduce the low-frequency noise as much as possible without band limiting the data too much. The 30-60 Hz low-cut filter seemed to provide optimal results (Figure 3).

Figure 2. Low-cut filter 20-40 Hz applied to a) regular seismic single-impact shot record 59, b) multi-impact shot record 74 after decomposition using 155 impulses, c) multi-impact shot record 74 after cross-correlation using 155 impulses.

three seismic records

Figure 3. Low-cut filter 30-60 Hz applied to a) regular seismic single-impact shot record 59, b) multi-impact shot record 74 after decomposition using 155 impulses, c) multi-impact shot record 74 after cross-correlation using 155 impulses.

three seismic records

Again, the decomposed shot gather (Figure 3b) seems to have better coherency and signal-to-noise ratio first-arrivals and reflections. Optimizing the low-cut filter also seemed to enhance the first-arrival energy of the cross-correlated shot record (Figure 3c); however, this enhancement comes at a price, first-arrival-wavelet phase distortion. Such phase distortion can be an obstacle for some analysis techniques.

In this instance, filtering seemed to have removed the low-frequency component of the surface-wave, which probably stacked in during the cross-correlation process (because during the impact sequence generation surface-wave from a previous impact affects the record) and hence its appearance prior to the first-arrivals. In most cases successful surface-wave filtering is challenging and generally results in phase distortion of the first-arrival wavelet, making it difficult to recognize the actual onset of first-arrival energy.

We selected data from channel 27 (third trace from the left on shot records) to compare wavelets from the different data sets. Channel 27 was extracted from the single-impact shot record 59 (Figure 1a), from the decomposed shot 74 (Figure 1b), from the cross-correlated shot 74 (Figure 1c), from the 30-60-Hz low-cut filtered decomposed shot 74 (Figure 3b), and from the 30-60-Hz low-cut filtered cross-correlated shot 74 (Figure 3c). All the traces were gathered into a single trace gather No 5974 and their channel numbers were renumbered (Figure 4).

Figure 4. The first 100 ms of 1000 ms are displayed to better observe the first-arrival wavelet. A common trace gather is displayed using identical channel numbers from five different shot gathers. The first trace is from the single-impact shot record 59, the second trace is from the decomposed shot 74, the third trace is from the cross-correlated shot 74, the forth trace is from the 30-60-Hz low-cut filtered decomposed shot 74, and the fifth trace is from the 30-60-Hz low-cut filtered cross-correlated shot 74.

close up of 5 traces

To numerically evaluate the match between the traces, the first trace was cross-correlated with all the traces. The corresponding cross-correlation coefficients between trace 1 and the rest of traces from the common trace gather are as follows:

Trace number Coefficient
1 1.000000
2 0.940079
3 0.884428
4 0.681591
5 0.660563

It is evident from the above data that trace 1, from the single-impact shot record 59, correlates best with trace 2, which is from the decomposed shot 74.

Comparing the frequency spectra of the five traces (Figure 5) provides additional information about the data. The trace from the single-impact shot record 59 has better frequency content than the trace from the decomposed shot 74 (Figure 5). At the present moment any degradation in spectra due to the decomposing algorithm is not expected. Therefore, the richer frequency content of trace number 1 could be because the single-shot record contains more high-frequency noise (i.e. air wave, ambient noise, etc.) than the decomposed record. However, the trace from the decomposed shot has the richest frequency content compared to the rest of the traces.

Figure 5. Frequency spectra of the five traces from the combined shot gather 5974. The red line with triangles is from the single-impact shot record 59, the green line with circles is from the decomposed shot 74, the light blue line with squares is from the cross-correlated shot 74, the black line is from the 30-60-Hz low-cut filtered decomposed shot 74, and the blue line with stars is from the 30-60-Hz low-cut filtered cross-correlated shot 74.

frequency spectra

The first 70 ms of all the traces were graphically displayed for closer observation (Figure 6). It is evident that the decomposed trace has greatest similarity with the single-impact trace. The 1-ms shift of the decomposed trace, necessary to make the match, is likely related to different near-surface conditions, which affected the travel-time and frequency content of the wacker and single-impact data differently.

Figure 6. First-arrival wavelet comparison of channel 57 from the corresponding record. The decomposed trace was shifted (delayed) with 1 ms for better match with the single-impact shot.

wavelet comparison

We used a first-arrival automatic picker (developed at the KGS) to determine which data set was best suited to automatic routines for first-arrival picking. The software requires manual selection of an initial starting point and a range of traces to estimate the first-arrivals. Accordingly, we selected the starting point for first-arrival picking to be channel 26 (trace #2) at 20 ms and the range of traces from channel 26 to channel 65 (trace #41). The first-arrival picker estimated the first-arrivals for channels 26 through 45 well and failed for channels 46 to 65 because of the noise, specifically noise on channels 48 to 52 (Figure 7).

Figure 7. First-arrival picking on the single-impact shot record 59.

First arrival picking

Using the same starting point and range of traces, the first-arrival picker had fewer difficulties on the decomposed record. The first-arrivals for channels 26 through 58 were estimated fairly well, but the picker failed for channels 59 to 65 because of the noise (Figure 8).

Figure 8. First-arrival picking on the decomposed shot 74.

First arrival picking

The first-arrival picker performed poorly (using the same parameters) on the cross-correlated record. It was misguided by low-frequency noise on channels 31 through 40 and failed because of the noise on channels 59 to 65 (Figure 9).

Figure 9. First-arrival picking on the cross-correlated shot 74.

First arrival picking

The first-arrival picker performed best on the low-cut filtered shots, both decomposed (Figure 10) and cross-correlated (Figure 11); picking quality was nearly identical. Low-cut filters usually cause phase-shift (time shift) errors, a problem evident on these data. Considering the possibility of phase shift errors due to low-cut filtering, the decomposed shot gather appears to be the best candidate for first-arrival picking.

Figure 10. First-arrival picking on the 30-60-Hz low-cut filtered decomposed shot 74.

First arrival picking

Figure 11. First-arrival picking on the 30-60-Hz low-cut filtered cross-correlated shot 74.

First arrival picking

Discussion

Random or precise-interval impact sequences are not necessary for the decomposition method. Randomness is not a requirement. At the present moment, knowing the time and the amplitude of the impact sequence are the only requirements for decomposing the multi-impact data. This could be tested if non-random data are provided.

Further test with this data showed that decomposing data with a number of impacts lesser than 155 may still provide good enough quality for the purposes of first-arrival picking.

Summary

The decomposed data have better frequency content than the cross-correlated data (Figure 5), its first-arrival shape matches best and is almost identical to the first-arrival pattern on the single-impact shot, and it is most accurate for first-arrival picking by the automatic picker used.

Furthermore, when examining the reflection events at 190 ms, 250 ms, and 300 ms (Figures 1, 2, and 3), the decomposed data provide more continuous reflections with higher signal-to-noise ratio then the other data sets.

Table 1. Impact sequence of 155 impulses.

TraceTimeValue
500.4273
1500.395
2430.3641
3290.4466
4180.4336
5120.4425
6150.4256
7130.4064
9530.1775
10830.7178
11870.5482
12950.1364
13750.2807
14690.2354
15560.3669
16440.2699
17280.465
18230.3791
19210.4089
20200.5139
21160.4033
22050.2776
23000.2794
23990.4402
25200.4409
26190.3023
27060.4214
27960.4636
28820.5474
29690.5174
30590.5445
31530.4679
32440.8082
33310.7231
34280.433
35270.46
36330.3399
38460.1242
41610.5634
42670.6888
43760.5988
44750.2327
45570.4306
46570.4229
47570.3562
48570.4228
49910.1271
50750.3973
51740.6907
52600.5411
53530.447
54390.5208
55270.4846
56110.5193
57090.4785
58100.2445
59140.6072
60230.3711
62170.6607
63570.2813
64500.4416
65390.6599
66310.6098
67160.614
68040.5186
68890.5974
69840.449
70710.7703
71680.4102
72510.611
73510.5138
74470.4844
75660.5865
77250.0619
78160.1588
80950.7068
81870.6875
82800.5752
83680.3511
84490.6308
85380.7221
86210.7034
87090.593
87920.581
88820.4625
89610.6085
90570.4251
91360.7232
92380.3107
93220.6669
94390.5051
95460.3787
96870.472
97960.6209
98910.8673
100010.4824
101250.2735
102260.2496
103590.1242
104420.4586
105490.7873
106410.6636
107410.4768
108440.0613
109170.589
110220.4124
111230.6111
112210.2354
112961
113920.6714
114820.5736
115710.2624
116480.617
117530.3828
118430.6102
119370.4991
120240.3648
121070.5039
121960.6108
122940.6319
123950.6923
124900.7483
125930.6034
127610.8781
128620.819
129530.4677
130520.4999
131530.5933
132910.6912
136840.1748
139950.8377
141040.781
142100.7144
143130.4133
143940.7002
144890.6815
145710.631
146630.4711
147480.6656
148440.5638
149300.6745
150270.4924
151120.7296
152180.4851
153110.5395
154150.5586
155140.4809
156150.4404
157160.2653
158210.3895
159340.5447
160410.5764
161470.6174
162530.3629
163530.2781

Kansas Geological Survey, Geophysics
Placed online July 12, 2006
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