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《Progress in Geophysics》 2012-06
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Research and application of the thickness quantitative predictions of carbonate cavity reservoir

DU Bin-shan1,2,HE Zhen-hua1,YONG Xue-shan2,CAO Zheng-lin2,WANG Xu-ben1,ZHANG Ping2 (1.Chengdu University of Technology,Chengdu 610059,China;2.Research Institute of Petroleum Exploration & Development-Northwest,PetroChina, Lanzhou 730020,China)  
Aimming at the problems such as the seismic inversion has strong multiple solutions for the thickness prediction of thin-bed reservoir,and the constrained seismic inversion is difficult to adapt the horizontal change of the layers for carbonate cavity reservoir prediction,and hardly meets the requirements of quantitative description and reserve calculation.By overall considering the pairing seismic characters of the reservoir's top and bottom reflections,and analyzing the characteristics of reservoir thickness changes with synthetic waveform and energy,a building reservoir thickness spectrum and thickness quantitative prediction technique is proposed in this paper.The technique mainly includes: accurately extracting seismic wavelet,building seismic responses of models with various-different thickness reservoirs,building the reservoir thickness spectrum with constrains of waveform and energy characteristics by border using cosine factor,analyzing of prediction error,and 3D reservoir thickness quantitative predictions.The method makes full use of the differences from the reservoir seismic responses between waveform and energy caused by thickness changes,does not need constrained by well and horizon data,overcomes partly human disturbance and lowers multiplicity.Vertical resolution of prediction breaks through limit of λ/4,usually up to λ/20~λ/40,also up to λ/8 for thin beds.(λ is wavelength).Theoretic simulations and actual data applications proposed that the method has a good application and popularization for the heterogeneous reservoirs of carbonate rocks.
【Fund】: 中石油重大科技项目“柴达木盆地建设千万吨油气田综合配套技术研究”;; 国家科技重大专项“大型油气田及煤层气开发”(2011zx05007-006)联合资助
【CateGory Index】: P631.4
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