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A continuation approach to regularization for traveltime tomography

Conference ·
OSTI ID:80327
 [1];  [2]
  1. Univ. of Washington, Seattle, WA (United States)
  2. Chevron Petroleum Technology, La Habra, CA (United States)
In most geometries in which seismic traveltime tomography is applied the slowness field is not well-determined from traveltimes alone. Nonuniqueness is common. Even when the slowness field is uniquely determined, small changes in the measured traveltimes can lead to large errors in the computed slowness field. A priori information is often available--well-logs, initial rough estimates of the slowness from structural geology, etc. This a priori information can be incorporated into a traveltime inversion algorithm using penalty terms. To further regularize the problem, smoothing constrains can also be incorporated using penalty terms by penalizing derivatives of the slowness field. A major decision to be made is the selection of the weights on the penalty terms, particularly the smoothing penalty weights. The authors use a continuation approach for selecting the smoothing penalty weights. Instead of fixing the smoothing penalty weights, they decrease the smoothing penalty weights in a step-by-step fashion, using the slowness model computed using the previous (larger) weights as the initial slowness model for the next step using the new (smaller) weights. A surprising outcome in synthetic problems is that the model error continues to decrease as they continue to decrease the smoothing penalty weights even after the data error had leveled off at the noise level. This continuation approach can solve synthetic problems more accurately than with fixed smoothing penalty weights, and appears to yield more features of interest in real-data applications of traveltime tomography.
OSTI ID:
80327
Report Number(s):
CONF-941015--
Country of Publication:
United States
Language:
English

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