Traveltime tomography: A comparison of popular methods

Noisy or inconsistent traveltime data yielded tomographic images that contain geologically unrealistic fluctuations. In addition to diverting attention away from structural patterns, these high‐wavenumber fluctuations can generate shadow zones and caustics that destabilize iterative solution schemes requiring ray tracing. We evaluated the performance of a number of popular methods that have been designed to reduce this effect, using synthetic crosswell data containing Gaussian noise. Quantitative comparisons between tomography methods were based on the misfit with the true model, solution stability under different sets of noise of the same level, and resolution‐covariance relationships. Other important factors included versatility and simplicity. Versatility is the ability to treat data with a wide range of noise levels as well as data generated by different structures. Simplicity is characterized by the number of adjustable inputs such as smoother shape, starting model, and damping or regularization para...

[1]  Sven Ivansson,et al.  Remark on an earlier proposed iterative tomographic algorithm , 1983 .

[2]  J. Orcutt,et al.  Waveform inversion of seismic refraction data and applications to young Pacific crust , 1985 .

[3]  G. Pavlis,et al.  Convolutional quelling in seismic tomography , 1989 .

[4]  D. Jackson.  The use of a priori data to resolve non‐uniqueness in linear inversion , 1979 .

[5]  J. Berryman,et al.  Fermat's principle and nonlinear traveltime tomography. , 1989, Physical review letters.

[6]  T. Jordan.  Estimation of the radial variation of seismic velocities and density in the earth , 1973 .

[7]  R. Kranz,et al.  Positive feedback fracture process induced by nonuniform high‐pressure water flow in dilatant granite , 1990 .

[8]  W. Menke.  Geophysical data analysis : discrete inverse theory , 1984 .

[9]  R. Lytle,et al.  Computerized geophysical tomography , 1979, Proceedings of the IEEE.

[10]  J. R. Evans,et al.  Active high-resolution seismic tomography of compressional wave velocity and attenuation structure at Medicine Lake Volcano, northern California Cascade Range , 1988 .

[11]  J. Scales.  Tomographic inversion via the conjugate gradient method , 1987 .

[12]  P. Bois,et al.  Well-to-well seismic measurements , 1972 .

[13]  S. Treitel,et al.  Fast l p solution of large, sparse, linear systems: application to seismic travel time tomography , 1988 .

[14]  I. M. Mason.  Algebraic reconstruction of a two‐dimensional velocity inhomogeneity in the High Hazles seam of Thoresby colliery , 1981 .

[15]  J. Scales,et al.  Regularisation of nonlinear inverse problems: imaging the near-surface weathering layer , 1990 .

[16]  Keiiti Aki,et al.  Determination of the three‐dimensional seismic structure of the lithosphere , 1977 .

[17]  G. F. West,et al.  Crosshole seismology and seismic imaging in crystalline rocks , 1983 .

[18]  G. W. Wecksung,et al.  Local basis-function approach to computed tomography. , 1985, Applied optics.

[19]  C. H. Chapman,et al.  Crosshole seismic tomography , 1989 .

[20]  John E. Peterson,et al.  Applications of algebraic reconstruction techniques to crosshole seismic data , 1985 .

[21]  W. Daily,et al.  Laboratory‐Determined Transport Properties of Core From the Salton Sea Scientific Drilling Project , 1988 .

[22]  J. Scales,et al.  Smoothing seismic tomograms with alpha-trimmed means , 1988 .

[23]  G. Backus,et al.  Numerical Applications of a Formalism for Geophysical Inverse Problems , 1967 .

[24]  Joel Franklin,et al.  Well-posed stochastic extensions of ill-posed linear problems☆ , 1970 .