@article{scholars7895, volume = {2016}, note = {cited By 3}, year = {2016}, doi = {10.1155/2016/2848750}, publisher = {Hindawi Limited}, journal = {International Journal of Geophysics}, title = {Influence of Error in Estimating Anisotropy Parameters on VTI Depth Imaging}, abstract = {Thin layers in sedimentary rocks lead to seismic anisotropy which makes the wave velocity dependent on the propagation angle. This aspect causes errors in seismic imaging such as mispositioning of migrated events if anisotropy is not accounted for. One of the challenging issues in seismic imaging is the estimation of anisotropy parameters which usually has error due to dependency on several elements such as sparse data acquisition and erroneous data with low signal-to-noise ratio. In this study, an isotropic and anelliptic VTI fast marching eikonal solvers are employed to obtain seismic travel times required for Kirchhoff depth migration algorithm. The algorithm solely uses compressional wave. Another objective is to study the influence of anisotropic errors on the imaging. Comparing the isotropic and VTI travel times demonstrates a considerable lateral difference of wavefronts. After Kirchhoff imaging with true anisotropy, as a reference, and with a model including error, results show that the VTI algorithm with error in anisotropic models produces images with minor mispositioning which is considerable for isotropic one specifically in deeper parts. Furthermore, over-or underestimating anisotropy parameters up to 30 percent are acceptable for imaging and beyond that cause considerable mispositioning. {\^A}{\copyright} 2016 S. Y. Moussavi Alashloo et al.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973149483&doi=10.1155\%2f2016\%2f2848750&partnerID=40&md5=15df30b3d90d7b07c2d4997e3db69e98}, keywords = {algorithm; anisotropy; data acquisition; genetic algorithm; imaging method; parameter estimation; seismic anisotropy; travel time; wave velocity}, author = {Moussavi Alashloo, S. Y. and Ghosh, D. P. and Bashir, Y. and Wan Ismail, W. Y.}, issn = {1687885X} }