2006•Journal of Oil and Gas TechnologyRequires access

Application of Logging Constrain and Seismic Inversion in Predicting Sandbody Distribution

Zhixian Gui

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Abstract

Inversion of Seismic data is one of the major tools for sandbody prediction. Inversion of sparse spike impedance is the most popular method for wave impedance inversion. It can be used for qualitative prediction of sandbody distribution under the condition of less wells. Based on examples inversion parameters are arranged by using actual problems, the effect of parameters of quality control(QC) on inversion result is particularly emphasized. The correctness of the parameter selection controls the quality of inversion. On the basis stated above, the sandbody distribution in 3rd member of Es_4 in YX Area is predicted, it is in correspondence with logging data.

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What this paper is about

Inversion of Seismic data is one of the major tools for sandbody prediction. Inversion of sparse spike impedance is the most popular method for wave impedance inversion. It can be used for qualitative prediction of sandbody distribution under the condition of less wells. Based on examples inversion parameters are arranged by using actual problems, the effect of parameters of quality control(QC) on inversion result is particularly emphasized. The correctness of the parameter selection controls the quality of inversion. On the basis stated above, the sandbody distribution in 3rd member of Es_4 in YX Area is predicted, it is in correspondence with logging data.

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Available abstract

Inversion of Seismic data is one of the major tools for sandbody prediction. Inversion of sparse spike impedance is the most popular method for wave impedance inversion. It can be used for qualitative prediction of sandbody distribution under the condition of less wells. Based on examples inversion parameters are arranged by using actual problems, the effect of parameters of quality control(QC) on inversion result is particularly emphasized. The correctness of the parameter selection controls the quality of inversion. On the basis stated above, the sandbody distribution in 3rd member of Es_4 in YX Area is predicted, it is in correspondence with logging data.

Key concepts: Inversion (geology), Correctness, Seismic inversion, Geology, Electrical impedance, Seismology, Computer science, Algorithm

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