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ANNL0G technique for seismic wave impedance inversion and its application effect

Cheng Sheng and 'Duan Yu.Fu Liyun,(Geoscince Department, Petroleum University ,Changping County,Beijing City,.102200)  
A nonlinear seisimc convolution model is constructed by performing the multi-stage decomposition and multistage nonlinear transform of seismic wavelets. Com-bining this model with the neural network that is based on neuron F-P functionmodel forms a ANNLOG technique for high-resolution wave impedance inversionunder the c0nstraints of logging and stratigraphic data. This technique involves fol-lowing essential points:. Multistage nonlinear transform causes fast iterative convergence and veryhigh resolution in vertical direction.. According to the lateral dynamic characteristic variation of seismic data,theneural networks storing multistage seismic wavelets (F-P model) enable reliableadaptive extrapo1ation inversion, and make continuous vertical resolution be stablein azimuthal direction.. Stratigraphic restrained inversion makes ANNLOG technique suitable to complexgeologic structures such as big throw faults,pinchouts and so on.
【CateGory Index】: P631.4
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