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Travel-time Tomography For High Contrast Media based on Sparse Data

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Travel-time Tomography For High Contrast Media based on Sparse Data. Yenting Lin. Signal and Image Processing Institute Department of Electrical Engineering University of Southern California. February 3, 2013. Computed Travel-time Tomography.

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slide1

Travel-time Tomography For High Contrast Media based on Sparse Data

Yenting Lin

Signal and Image Processing Institute

Department of Electrical Engineering

University of Southern California

February 3, 2013

slide2

Computed Travel-time Tomography

  • Computed travel-time tomography is a powerful tool to produce tomographic image
      • Measure the signal response on the boundary
    • Slices of specific area of the object, Non-destructive detection
      • Widely used in geophysical and medical imaging
slide3

Problems

  • Not enough data - samples may be expensive
    • Travel-time tomography in geophysical application: Very expensive to setup sensors, drilling costs much time and money
    • Under-determined nonlinear inverse problem
  • High contrast structure
    • Some natural structure have high contrast property
    • Only need to separate the target structure and the background
    • Typical grid-based model and iterative reconstruction won’t work well in this case
slide4

Our work

  • Reconstruct high contrast structure based on sparse travel-time data
    • Object based model – reduce the dimensionality
    • The solution is not unique - estimate the probability distribution of different models by randomized sampling techniques

Grid based model

Object based model

slide5

Water-flood tomography

  • Apply our algorithm in petroleum application
    • Water is injected to support the pressure in the reservoir
    • Use well injection and production data to estimate the equivalent travel-time between well pairs
    • Estimate the high permeability areas in an oil field

Ground truth in Simulator

Probability map of high perm