1. ADAPS multiple removal demo. The upper halves of the slides in this series show the input gathers.The bottoms show the same data with multiples removed. The slides are 20 depth points apart, from inline 154.The data starts at 200 milliseconds and continues to 1300 ms. This is the full record length. The system logic first subtracts the initial stack energy from a working buffer copied from the input. It then enters a “pass” loop. Here it finds the velocity that shows maximum coherency. If strong enough, it subtracts this energy from the working buffer.and from the original data. If it can no longer find a high enough ratio, it exits, otherwise it goes back to try again..

2. No random noise here! The major lesson to be learned from this exercise is that what we are seeing on this input data is the mixture of overlapping coherent events. If you look closely you will see the real reflections poking through. If the interference were random, my logic would not see it, since it depends on coherency across the band of traces. The next great lesson is the power of the stack. It is looking through the interference and while the treated results produce a better stack, it isn’t “day and night” better., this logic has “won the battle” of multiples, but not the final resolution war.

3. Continuing the random noise thing – Remember we’re looking at gathers here. The improvement we see below is on individual traces, not on the stack. There may be a way to lift random noise off a single gather member, but if there is, I don’t know it. In short, successful improvement proves to me the problem is, in fact, coherent noise.

4. That the stack was powerful enough to see through the interference, does not mean that it was not distorted by the noise. When we come to depend on wavelet purity for such things as inversion, this distortion becomes crucial. The remarkable similarity of wave shapes between traces tells us there is almost no random noise. Looking at the individual events we see no side lobes. The pre-processing has apparently done an efficient job (even though whitening the spectrum might have hurt us otherwise).

5. I’ve marked two “multiple” vestiges. It takes some eye training to see them, since they often only show up when they are in phase with another wavelet.

6. The X’s you see represent the mute that is calculated from an input parameter. In general it follows the input pattern.

7. Take some time to study the absence of side lobes. Current synthetic trace methods always seem to show significant legginess. The ADAPS logic typically says they don’t exist. Since we know they were there at the beginning, we have to assume that they were collapsed by early deconvolutions.

8. And so we go on for a few more.

12. The end - Click on this oval to repeat. Or on this one for main router. Email me at dpaige1@sbcglobal.netdpaige1@sbcglobal.net