A composite seismic attribute used to estimate the sand thickness for thin bed and thin interbed
WANG Yanguang1, LI Hao2, LI Guofa2, LIU Libin1, CAO Guoming3, ZHANG Huiqing3
1. Geophysical Research Institute, SINOPEC Shengli Oilfield, Dongying, Shandong 257022, China; 2. CNPC Key Laboratory of Geophysical Exploration, China University of Petroleum(Beijing), Beijing 102249, China; 3. Research Institute of Exploration and Development, Dagang Oilfield Company, PetroChina, Tianjin 300280, China
Abstract：Amplitude and frequency,the two basic seismic attributes,are often used to predict formation thickness when the thickness is smaller than a quarter of the wavelength.However,these two attributes have a non-linear relationship with formation thickness,and it reduces the quantitative prediction accuracy of sand body thickness.In addition,the function that relates the two attributes to sand body thickness is derived from single sand body wedge model.When it is applied to thin interbed model,the estimation error is inevitable.To solve this problem,a composite seismic attribute composed of amplitude and frequency was proposed in this paper.Firstly,a single sand body wedge model was used to test its precision in sand thickness estimation.Secondly,based on an interbed model superimposed by two sand wedges,the composite seismic attribute was used to estimate the cumulative sand thickness.Finally,the composite seismic attribute was used in real data to estimate the cumulative thickness of thin interbed sand bodies.The results showed that the composite seismic attribute not only improves the estimation accuracy of single thin sand body thickness,but also can be applied to the quantitative prediction of the cumulative thickness of thin interbed sand bodies.
王延光, 李皓, 李国发, 刘立彬, 曹国明, 张会卿. 一种用于薄层和薄互层砂体厚度估算的复合地震属性[J]. 石油地球物理勘探, 2020, 55(1): 153-160.
WANG Yanguang, LI Hao, LI Guofa, LIU Libin, CAO Guoming, ZHANG Huiqing. A composite seismic attribute used to estimate the sand thickness for thin bed and thin interbed. Oil Geophysical Prospecting, 2020, 55(1): 153-160.
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