The Bayes Sparse Spike Inversion Based on Spatial Variable Impedance Coefficient

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.