小尺度散射体稀疏最小二乘逆时偏移方法研究

Sparse least-squares reverse time migration of small scatters in seismic exploration

地震勘探方法在深部固体矿产资源勘探中发展潜力巨大,同时也面临挑战.由于固体矿产资源地下分布呈现陡峭构造、尺度小,物性差异小的特点,常规偏移方法对小尺度矿体成像的分辨率提高有限.本文研究了一种基于稀疏促进约束的最小二乘逆时偏移方法.首先,将非均匀分布的矿体等效为随机介质,建立小尺度扰动的矿体模型;其次,改进现有最小二乘偏移方法,以稀疏模型为先验信息约束成像结果,并通过Curvelet变换压缩成像空间,经过多次迭代计算,可以提高小尺度散射体的成像分辨率;再次,对炮域记录进行随机震源编码,减少成像所需的炮集个数,通过稀疏促进约束条件,降低串扰噪声引起的成像误差.通过庐枞金属矿模型数值计算,验证本文方法可以较好的成像包含小尺度散射体的金属矿地质模型.

Seismic exploration has a great potential in exploration of mineral resources in the deep subsurface,while also faces many challenges.Due to the steep structure,small-scale scatters and small differences of physical properties between the background and the orebody,the conventional migration method has a low imaging resolution for small-scale orebodies.In this paper,we propose a least-squares reverse time migration based on a sparsity-promoting constraint.First,the non-uniformly distributed orebodies are assumed to be equivalent to a random medium,and a multi-scale orebody model for such a medium is established.Second,we improve the existing Least-Squares Migration(LSM)by using the sparse constraint as the priori information,and then compress the imaging space by Curvelet transform.After iterative calculations,the imaging resolution of small-scale scatters can be enhanced.Third,the random source encoding is used to reduce the number of gathers for LSM,which speeds up the computation.By the sparsity-promoting constraint,the imaging error caused by crosstalk noise is reduced greatly.Numerical calculation on the Luzong metallic deposit model indicates that the proposed method can image the metallogenetic geological model containing small-scale scatters with a relatively high resolution.