3-D cross-gradient joint inversion of seismic refraction and DC resistivity data

Shi, Zhanjie; Hobbs, Richard W.; Moorkamp, Max; Tian, Gang; Jiang, Lu

Abstract

We present a 3-D cross-gradient joint inversion algorithm for seismic refraction and DC resistivity data. The structural similarity between seismic slowness and resistivity models is enforced by a cross-gradient term in the objective function that also includes misfit and regularization terms. A limited memory quasi-Newton approach is used to perform the optimization of the objective function. To validate the proposed methodology and its implementation, tests were performed on a typical archaeological geophysical synthetic model. The results show that the inversion model and physical parameters estimated by our joint inversion method are more consistent with the true model than those from single inversion algorithm. Moreover, our approach appears to be more robust in conditions of noise. Finally, the 3-D cross-gradient joint inversion algorithm was applied to the field data from Lin_an ancient city site in Hangzhou of China. The 3-D cross-gradient joint inversion models are consistent with the archaeological excavation results of the ancient city wall remains. However, by single inversion, seismic slowness model does not show the anomaly of city wall remains and resistivity model does not fit well with the archaeological excavation results. Through these comparisons, we conclude that the proposed algorithm can be used to jointly invert 3-D seismic refraction and DC resistivity data to reduce the uncertainty brought by single inversion scheme

Citation

Shi, Z., Hobbs, R. W., Moorkamp, M., Tian, G., & Jiang, L. (2017). 3-D cross-gradient joint inversion of seismic refraction and DC resistivity data. Journal of Applied Geophysics, 141, 54-67. https://doi.org/10.1016/j.jappgeo.2017.04.008

• Journal Article Type: Article
• Acceptance Date: Apr 12, 2017
• Online Publication Date: Apr 29, 2017
• Publication Date: Apr 29, 2017
• Deposit Date: Jul 18, 2017
• Publicly Available Date: Apr 29, 2018
• Journal: Journal of Applied Geophysics
• Print ISSN: 0926-9851
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 141
• Pages: 54-67
• DOI: https://doi.org/10.1016/j.jappgeo.2017.04.008