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雙月刊,2016年6月創(chuàng)刊
主管:教育部
主辦:中國(guó)石油大學(xué)(北京)
   清華大學(xué)出版社有限公司
出版:清華大學(xué)出版社有限公司
編輯:《石油科學(xué)通報(bào)》編輯部
主編:陳勉
地址:北京市海淀區(qū)學(xué)院路20號(hào)院
   902信箱中國(guó)石油大學(xué)期刊社
郵編:100083
電話:010-82377349
?????????010-89734040
E-mail:[email protected]
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Injecting supercritical CO2 into underground reservoir space significantly alters the properties of the sequestered area, resulting in obvious time-lapse responses on post-stack seismic data. Time-lapse wave impedance inversion is an effective method to identify reservoir changes by calculating differential wave impedance with post-stack time-lapse differential data. Since reservoir parameters lapse are usually localized, the differential wave impedance often displays clear, block-like features, meaning that the reflectivity of differential wave impedance tends to exhibit sparsity. And due to the insufficient sparsity of the L2 or L1 regularization constraint term used in the conventional time-lapse wave impedance inversion method, it results in the problem of unclear boundary delineation in time-lapse difference imaging. In this paper, we propose to add L1-2 norms with stronger sparsity-promoting characteristics as a prior constraint into the differential wave impedance inversion to enhance the clarity of the inversion results at the boundary clarity. The L1-2 norm constraint improves the sharpness of the inversion results, especially at impedance interfaces. Through model testing and analysis, it is found that the L1-2 norm constraint provides the highest inversion resolution in the vertical direction when compared to L1 and L2 norms. Additionally, in order to overcome the problem of poor transverse continuity of the inversion results that may be caused by using the single-channel inversion method, this paper adopts the f-x filtering method for result enhancement. By applying the proposed method to the model data and the CO2 geological storage data in the deep saline layer of Sleipner, Norway, it is shown that the time-lapse wave impedance inversion method based on the constraints of L1-2 norms can characterize the time-lapse seismic differential response efficiently and accurately, and it can be used as a means to monitor the CO2 geological storage.


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