New PDF release: Basic earth imaging(ver.2.4)

By Claerbout J.F., Black J.L.

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12), shows they are reasonable when the desired result is near the guessed center of the range. Otherwise, the moment is biased towards the initial guess. This bias can be reduced in stages. At each stage we shrink the width of the zone used to compute the moment. 10. )/(alpha*t) )) slow(it) = reg(it) } do irange= ns/4, 5, -1 { # shrink the fairway do it= 1, nt { t= t0 + dt*(it-1) do is= 1, ns { s= s0 + ds*(is-1) if( s > slow(it) + irange*ds) scan(it,is) = 0. if( s < slow(it) - irange*ds) scan(it,is) = 0.

Linear moveout is the only application where I have ever encountered this difficulty. 5001”. The problem disappears if we use a more accurate sound velocity or if we switch from nearest-neighbor interpolation to linear interpolation. 3. 3 29 Muting Surface waves are a mathematician’s delight because they exhibit many complex phenomena. Since these waves are often extremely strong, and since the information they contain about the earth refers only to the shallowest layers, typically, considerable effort is applied to array design in field recording to suppress these waves.

6 the early signals are too weak to see. This results from the small number of traces at early times because of the mute function. ) To make the stack properly, we should divide by the number of nonzero traces. The fact that the mute function is tapered rather than cut off abruptly complicates the decision of what is a nonzero trace. In general we might like to apply a weighting function of offset. How then should the stack be weighted with time to preserve something like the proper signal strength?

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Basic earth imaging(ver.2.4) by Claerbout J.F., Black J.L.

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