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Next: Real Electroseismic data Up: Haines and Guitton: Electroseismics Previous: Introduction

Synthetic Electroseismic data

We begin by testing the processing approach on simple synthetic data containing three interface response events, three coseismic arrivals, and a small amount of random noise (Figure [*]a). For our first processing example we chose models for the PEF estimation (Figure [*]c and d) that simply contain amplitude-normalized versions of the events in the synthetic data, plus random noise. For the noise model, this choice is not entirely unrealistic; horizontal geophone data collected with electroseismic data closely resembles the coseismic noise in the electroseismic record Garambois and Dietrichz (2001) and could be used in this capacity. For the signal model, this choice is rather unrealistic, as we would generally be looking for previously unknown interface response signal that might be entirely obscured by coseismic and background noise. The purpose of this first example is to verify that the method is effective, and this is demonstrated by the final result shown in Figure [*]b. Virtually all of the coseismic noise has been removed, leaving only the interface response energy.

 
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Figure 1
a) Simple synthetic data, with horizontal interface response events created using equation (1) and an arbitrary velocity function. Coseismic noise is created with the same velocity function. b) Result after non-stationary PEF signal/noise separation. c) Normalized version of synthetic interface response, used as model used for the estimation of the signal PEF's. d) Normalized version of coseismic noise, used as model for the estimation of the noise PEF's.
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Our second synthetic processing example (Figure [*]a) employs the same data and noise model as Figure [*], and a more general signal model. We use the amplitude pattern predicted by equation (1) to produce a model for signal PEF estimation (Figure [*]c). We normalize the amplitude pattern in the time direction so that the PEF estimation equally considers deeper and shallower parts of the amplitude pattern. Because we use one-dimensional PEF's Haines and Guitton (2002), this choice of signal model is quite reasonable. If we were to use two-dimensional signal PEF's, we could not use this model as the PEF's would be trying to model waveform information that is not present in the model. An alternative option would be to use the amplitude pattern (Figure [*]c) to scale synthetic wavelets, and then to estimate 2-D signal PEF's on that model. But this approach would lose some generality as we would have to assign particular arrival times to those arrivals, and is not necessary since we find one-dimensional PEF's to be at least as effective as two-dimensional PEF's. The final result (Figure [*]b) is nearly as good as that of Figure [*]b, and shows that the generality of this choice of signal model does not bring with it a significant degradation of the final result.

 
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Figure 2
a) Synthetic data, same as Figure [*]a. b) Result after signal/noise separation. c) Model used for estimation of signal PEF's, based on equation (1). d) Normalized version of coseismic noise, used as model for estimation of noise PEF's.
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Our third synthetic example (Figure [*]) adds an important element of realism to the synthetic data. Electroseismic data is collected using electrode dipoles pounded into the Earth. The coupling of these electrodes with the ground is hardly uniform and results in amplitude variations between adjacent traces. We simulate this coupling variation by multiplying each trace of the synthetic by a random scalar (between 0.7 and 1.0), producing the data shown in Figure [*]a. We use the same signal and noise models as in the previous example (Figure [*]), and obtain the result shown in Figure [*]b. This result contains more remnant coseismic noise than the previous examples, but the interface response energy is significantly stronger, and would dominate a stack of the gather.

 
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Figure 3
a) Synthetic data, same as Figure [*]a, but each trace is multiplied by a random number to simulate the imperfect electrode coupling that impacts electroseismic data. b) Result after signal/noise separation. c) Model used for estimation of signal PEF's, based on equation (1). d) Normalized version of coseismic noise, used as model for noise PEF estimation.
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next up previous print clean
Next: Real Electroseismic data Up: Haines and Guitton: Electroseismics Previous: Introduction
Stanford Exploration Project
7/8/2003