Joint inversion of crosshole radar and seismic traveltimes

The structural approach to joint inversion, entailing common boundaries or gradients, offers a flexible and effective way to invert diverse types of surface-based and/or crosshole geophysical data. The cross-gradients function has been introduced as a means to construct models in which spatial changes in two distinct physical-property models are parallel or antiparallel. Inversion methods that use such structural constraints also provide estimates of nonlinear and nonunique field-scale relationships between model parameters. Here, we jointly invert crosshole radar and seismic traveltimes for structurally similar models using an iterative nonlinear traveltime tomography algorithm. Application of the inversion scheme to synthetic data demonstrates that it better resolves lithologic boundaries than the individual inversions alone. Tests of the scheme on GPR and seismic data acquired within a shallow aquifer illustrate that the resultant models have improved correlations with flowmeter data in comparison with models based on individual inversions. The highest correlation with the flowmeter data is obtained when the joint inversion is combined with a stochastic regularization operator and the vertical integral scale is estimated from the flowmeter data. Point-spread functions show that the most significant resolution improvements offered by the joint inversion are in the horizontal direction.

[1]  P. N. Sen,et al.  A self-similar model for sedimentary rocks with application to the dielectric constant of fused glass beads , 1981 .

[2]  Michael A. Saunders,et al.  LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares , 1982, TOMS.

[3]  R. Parker,et al.  Occam's inversion; a practical algorithm for generating smooth models from electromagnetic sounding data , 1987 .

[4]  J. Vidale Finite-difference calculation of travel times , 1988 .

[5]  P. Podvin,et al.  Finite difference computation of traveltimes in very contrasted velocity models: a massively parallel approach and its associated tools , 1991 .

[6]  John A. Hole,et al.  Nonlinear high‐resolution three‐dimensional seismic travel time tomography , 1992 .

[7]  Amos Nur,et al.  COMPRESSIONAL VELOCITY AND POROSITY IN SAND-CLAY MIXTURES , 1992 .

[8]  S. Gorelick,et al.  Estimating lithologic and transport properties in three dimensions using seismic and tracer data , 1996 .

[9]  E. Haber,et al.  Joint inversion: a structural approach , 1997 .

[10]  H. Maurer,et al.  Stochastic regularization: Smoothness or similarity? , 1998 .

[11]  Gregory A. Newman,et al.  Image appraisal for 2-D and 3-D electromagnetic inversion , 2000 .

[12]  Y. Rubin,et al.  Estimating the hydraulic conductivity at the south oyster site from geophysical tomographic data using Bayesian Techniques based on the normal linear regression model , 2001 .

[13]  Brian J. Mailloux,et al.  Hydrogeological characterization of the south oyster bacterial transport site using geophysical data , 2001 .

[14]  Ari Tryggvason,et al.  Three-dimensional imaging of the P- and S-wave velocity structure and earthquake locations beneath Southwest Iceland , 2002 .

[15]  M. Meju,et al.  Characterization of heterogeneous near‐surface materials by joint 2D inversion of dc resistivity and seismic data , 2003 .

[16]  Alan G. Green,et al.  Discrete tomography and joint inversion for loosely connected or unconnected physical properties: application to crosshole seismic and georadar data sets , 2003 .

[17]  Timothy Scheibe,et al.  An Evaluation of Conditioning Data for Solute Transport Prediction , 2003, Ground water.

[18]  M. Meju,et al.  Joint two-dimensional DC resistivity and seismic travel time inversion with cross-gradients constraints , 2004 .

[19]  Michael D. Knoll,et al.  Multivariate analysis of cross‐hole georadar velocity and attenuation tomograms for aquifer zonation , 2004 .

[20]  F. Santos,et al.  Joint inversion of gravity and geoelectrical data for groundwater and structural investigation: application to the northwestern part of Sinai, Egypt , 2006 .

[21]  N. Linde,et al.  Local earthquake (LE) tomography with joint inversion for P‐ and S‐wave velocities using structural constraints , 2006 .

[22]  A. Binley,et al.  Improved hydrogeophysical characterization using joint inversion of cross‐hole electrical resistance and ground‐penetrating radar traveltime data , 2006 .

[23]  A. Tryggvason,et al.  FAST TRACK PAPER: A traveltime reciprocity discrepancy in the Podvin & Lecomte time3d finite difference algorithm , 2006 .

[24]  Stefan Finsterle,et al.  Inversion of tracer test data using tomographic constraints , 2006 .

[25]  L. Gallardo Multiple cross‐gradient joint inversion for geospectral imaging , 2007 .

[26]  Max A. Meju,et al.  Joint two‐dimensional cross‐gradient imaging of magnetotelluric and seismic traveltime data for structural and lithological classification , 2007 .

[27]  J. Carcione,et al.  Cross-property relations between electrical conductivity and the seismic velocity of rocks , 2007 .

[28]  Paul A. Bedrosian,et al.  Lithology-derived structure classification from the joint interpretation of magnetotelluric and seismic models , 2007 .