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Next: Ray-based tomography Up: Shen: Q estimation Previous: Introduction

Methods Review

In this section, I review previous studies which have addressed Q estimation, and discuss how they solve the challenges listed above. Generally, Q tomography algorithms are classified into two main categories. One category is ray-based tomography (Rickett, 2007; Plessix, 2006; Rickett, 2006; Quan and Harris, 1997), where the relationship between the measurements and the inverse of Q is assumed to be linear. The other category is wave-equation-based tomography (Xin et al., 2008; Liao and McMechan, 1996; Pratt et al., 2003; Watanabe et al., 2004; Gao et al., 2005; Hicks and Pratt, 2001), which is formulated as a nonlinear optimization problem.