基于伴随方法的线性台阵背景噪声面波和远震体波联合成像研究

伴随层析成像（Adjoint Tomography）通过求解全波方程来准确模拟地震波在复杂介质中的传播，并利用波形信息来反演地下结构，是新一代的高分辨率成像方法.其中3-D伴随层析成像需要庞大的计算资源，而2-D反演相对更具计算效率.面波和远震体波是研究地壳上地幔速度结构的重要方法，它们对S波速度及Moho面的敏感度不同，通过联合反演，可以得到更为准确的S波速度结构及Moho面.通过两种数据的高度互补性，本文提出基于伴随方法的线性台阵背景噪声面波和远震体波联合成像方法，同时约束台阵下方S波速度结构及Moho面形态.我们将该方法应用到符合华北克拉通岩石圈典型结构特征的理论模型上，测试结果表明联合反演方法优势明显，相比于面波伴随层析成像，能获得更高分辨率的S波速度结构，同时能精准约束Moho面形态.相比于体波伴随层析成像，联合反演能有效压制高频假象，降低波形反演过程中的非线性化程度.本研究有望提供一种更为高效精准的线性台阵成像方法，搭建联合伴随层析成像理论框架，提升岩石圈成像分辨率，并为后续其他类型波形数据的引入提供思路和方法.

Joint inversion of linear array ambient noise surface-wave and teleseismic body-wave data based on an adjoint-state method

Adjoint tomography is one of state-of-the-art imaging methods with high resolution. It can get better-resolved models by solving full wave equations to accurately simulate the propagation of seismic waves, and by considering full waveform information in inversion. However, the computational cost and storage requirement of 3-D adjoint tomography are high. Relatively, 2-D adjoint tomography is much more computationally efficient. Surface waves and teleseismic body waves provide essential data for studying crustal and uppermost mantle structures. Due to different sensitivities to shear wave velocity at depths and Moho discontinuity, joint inversion of both datasets can resolve the Vs model and Moho interface better. To take advantages of the two different types of data, we propose a strategy of joint inversion for ambient noise surface waves and teleseismic body waves recorded by linear arrays based on the adjoint-state method, which can be used to yield a fine Vs model and Moho topography. We perform various synthetic imaging experiments, in which the model has typical features of crustal structures in North China Craton (NCC). Compared to the surface wave inversion only, joint inversion improves the resolution of images as well as constraining discontinuity undulations better. Compared to the body wave inversion only, joint inversion can suppress high frequency artifacts and reduce the nonlinearity during inversion. This study could provide an efficient alternative to image fine velocity structures beneath linear arrays and also build a framework for joint inversion. It could improve the resolution of lithospheric imaging and also provide strategies of incorporating other waveforms in the future.