What’s new in exploration

	Vol. 231 No. 6
CHRISTOPHER LINER, PROFESSOR, UNIVERSITY OF HOUSTON

House of mirrors

Let’s take a ride on a seismic wave. The setting is offshore, and a cylindrical steel airgun is just now charging up, the pressure building until a signal triggers the release of compressed air. The gas expands rapidly, generating a bubble and a pressure wave in the water; a seismic wave is born. The wave takes off in every direction, but let’s follow it straight down toward the seafloor.

This wave has a certain amplitude and a corresponding amount of energy. Striking the seafloor, it splits into two parts, an upgoing reflected wave and a downgoing transmitted wave. Whether the seafloor is hard or soft, not much of the wave passes through the water-sediment interface. This may seem surprising. since we have all seen beautiful offshore 3D seismic images created from waves bouncing around deep in the earth. But the fact is that only a small fraction of the wave action gets through the seafloor to make these images.

For a soft seafloor, something like 45% of the wave is reflected back up into the water, and over 60% for a hard seafloor. Now remember, we are following a vertical wave, so this reflection heads back toward the ocean surface. The trip upward is not very exciting until the wave hits the water/air interface (also known as the free surface).

You might think, with air being so compressible and low density compared to water, that the sound wave would pass right on through. In fact, the opposite is true. Nothing gets through, and the wave reflects at full strength back to the seafloor. Half of it bounces there, then all of that signal reflected off the seafloor reflects again from the free surface, and so on.

The multiples are periodic, each round trip taking the same amount of time. Have you ever been at a carnival and wandered into the house of mirrors? Every movement reveals an infinite puzzle of repeating images. That is the situation for a receiver in the water as these waves ping back and forth between the seafloor and the surface. These are called free-surface multiples since they are bouncing off the air/water interface. Another kind of multiple can occur deeper in the earth, where extra bounces are taken in one or more layers. These are termed internal multiples.

Multiples of any kind are big trouble to seismic imaging. First, the strong free-surface multiple will continue bouncing the entire time we are recording data. Eventually, there will be a weak reflection from somewhere deep in the earth, and a multiple is likely to crash right into it. It is all too common in offshore seismic  surveys around the world that delicate, carefully nurtured reservoir reflections sit under big, strong multiples.

Imaging also suffers for a more subtle reason. For half a century researchers have been devising ever-better ways to migrate seismic data. But almost all of them have one thing in common: Only primary (single bounce) reflections are used for imaging, not multiples. Offshore data is typically full of multiples, but we consider it noise, not signal. That means multiples have to be removed before migration.

So how do we get rid of these multiples? The classic method is deconvolution, a word with a lot of meaning. It can be used for spectral whitening, source signature removal or wave-shaping, as well as multiple removal. Deconvolution goes back to the earliest days of digital seismic processing, and also goes by the more descriptive name of prediction error filtering.

As an analogy, imagine that you are walking across a parking lot on a completely dark night. As you pace along, you suddenly bump your toe on a curb. Stepping over it, you continue and hit another curb farther on, and another. After a while, you start counting steps and find you can predict the next curb—not perfectly at first, but you get better and finally can avoid them. In effect, this is what the mathematical machinery of deconvolution does when processing a seismic trace. Based on earlier data values, decon predicts what will come a few time steps ahead, then goes there, checks the value, updates the prediction, and keeps trying. Since our multiple is periodic, decon will be able to predict it and thus remove it from the data.

Reflections due to deeper geology, however, are by nature unpredictable and will not be removed. Decon has the remarkable ability to find the multiple pattern, or patterns, embedded in a random sequence of geological reflections. Very clever.

Going back to the dark parking lot, what if we change the situation so the repeating curbs are very far apart. So far, in fact, that you only hit one or two as you walk across the entire parking lot. In that case, you would not be able to figure out the repeat pattern because you get too few looks at it. In the same way, decon is great for short-period multiples from shallow water, but fails for long-period multiples that occur in deep water. Over the last 20 years or so, a completely different multiple removal technique has been developed for exactly this situation. It has the cumbersome name of surface-related multiple elimination (SRME).

SRME is a vital tool in the modern exploration for deepwater resources. It can handle much more complicated cases than the simple, vertical multiple described above. SRME works in situations where decon breaks down, like seafloor topography, nonvertical waves and 3D scattering effects. The way SRME works is by considering the raypath for a particular free-surface multiple, and breaking it down to look like two primary reflections glued together. This insight allows a free-surface multiple that shows up only one time to be neatly and effectively removed. It has led to a vast improvement in detailed image quality in the deepwater Gulf of Mexico and elsewhere.

Better ways of multiple removal are constantly under development for offshore data, many of them linked to new acquisition methods like wide-azimuth shooting. Nothing is simple in a house of mirrors, but this arsenal of tools can afford us a clear view of what is really important, the reservoir.  

ACKNOWLEDGMENTS

I would like to thank Larry Rairden of EOS Energy and Mary Edrich of Geokinetics for useful discussions and sharing of information.