ANDERSON: BOTTOM PROPERTIES FOR LONG-RANGE PROPAGATION PREDICTION 



greatly increase the speed of propagation. In the latter case, the 

 sediment essentially looks like it is partially lithified. 



Figure 6 shows the interval velocity for a region and Hamilton's 

 estimate of the best fit line to the instantaneous velocity data. In 

 this example, the instantaneous velocity, which is the one that would 

 go into a propagation model, is nonlinear over an extended depth 

 interval. However, the interval velocity, which is the average 

 velocity over the measured depth interval, remains somewhat linear. 



Compressional-wave attenuation is another important parameter. 

 Figure 7 is a compilation from a large number of sources of data for 

 acoustical attenuation in dB per meter versus frequency. These re- 

 sults are for measurements which were made in clays and silts. It 

 is a presentation which is similar to what Hamilton uses. 



Several things can be seen. One is the order of magnitude of 

 the attenuation. Another is the absence of any data for anything 

 below 1 kHz. 



Another observation is that over short frequency intervals in 

 any given sediment the attenuation may not vary linearly with fre- 

 quency. But if we take the overall behavior as we go down the graph, 

 attenuation varies linearly with frequency. If this is true, and 

 certainly these data seem to indicate that it is, then it suggests 

 a way to get a number for the attenuation at low frequencies. We 

 must decide what value we are going to accept for attenuation at 

 some high frequency and extrapolate linearly downward to a lower 

 frequency of interest. We hope to improve upon this extrapolation 

 in the future . 



If we accept that attenuation is described as a linear function 

 of frequency — that is, the attenuation coefficient is equal to 



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