基于空变阻抗约束的贝叶斯稀疏脉冲反演
The Bayes Sparse Spike Inversion Based on Spatial Variable Impedance Coefficient
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摘要: 常规的基于贝叶斯理论的稀疏脉冲反演中,各约束项的拉格朗日算子均采用的是恒定的常系数。反演实际资料发现,波阻抗反演剖面与钻井资料的油气显示并不能很好地对应。考虑到反演不同地震道数据时,低频趋势模型所起的约束作用应当不同。本文在常规反演的基础上做出了改进,假定阻抗约束系数是一个空间变量,由各地震道的实际地震数据与合成记录之间的振幅残差来确定该道的阻抗约束系数。实际资料应用表明,改进后的反演结果更稳定,能更准确地反映地下阻抗信息。Abstract: In the conventional sparse spike inversion which based on Bayesian theory, the Lagrange operator of the constraint term always been valued as a constant coefficient. After inversed the field data, we found that the impedance inversion profile can't match well with the oil and gas by drilling. Considering that the seismic trace data is different, the effect of the low frequency trend model should be different, so on the basis of conventional inversion, this text made some improvement and we assumed that impedance constraint coefficient which determined by the difference between the actual seismic data and the synthetic record is a spatial variable. The practical application shows that the improved inversion results are more stable and can reflect the underground impedance information more accurately.