In the field of thin layer prediction,geostatistical methods and waveform inversion techniques are currently the two main approaches.However,geostatistical inversion faces challenges in constructing accurate variograms in areas with sparse well points,making it difficult to accurately predict thin layers.Although waveform inversion is less dependent on the distribution of well net-works,its high-frequency components are insufficient in describing the spatial variation of seismic amplitudes.To overcome these limitations,this paper proposes pre-stack seismic structure morphology inversion technology,an innovative reservoir prediction method.This technique effectively predicts the spatial distribution of target lithologies by comparing the lateral changes in energy and frequency characteristics within the seismic data volume.It fully utilizes the lateral information of the seismic data volume,with high-frequency information that closely matches the spatial energy variations of the seismic data.Through ray elastic imped-ance analysis,the method is able to extract more elastic parameters,and its results are consistent with Amplitude Variation with Offset(AVO)characteristics,thereby enhancing the accuracy in reflecting the lateral changes in energy across different ray do-mains in pre-stack seismic data.This enables it to accurately predict various lithology types.In study areas with sparse well net-works,this method demonstrates a marked advantage in predicting complex lithological interlayers.The method has shown excel-lent results in practical applications in multiple oil fields,with a prediction accuracy rate of over 80％for interlayers of more than 1 meter.Compared with traditional inversion techniques,it is more conducive for predicting complex lithological interlayers in areas with sparse well networks.
sparse well networkseismic structure morphology inversionray elastic impedancecomplex lithological interlayer
维普
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