The research on method of interlayer modeling based on seismic inversion and petrophysical facies

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• 作者：Chao Cheng ; ^{105964461@qq.com" class="auth_mail" title="E-mail the corresponding author} ; ^{ylksh@163.com" class="auth_mail" title="E-mail the corresponding author} ; Wengang Yu¹ ; ^{771895476@qq.com" class="auth_mail" title="E-mail the corresponding author} ; Xiaojun Bai² ; ^{1790781818@qq.com" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Interlayer ; Vertical resolution ; L1-L2 combined norm constrained inversion ; Petrophysical facies ; Geological model
• 刊名：Petroleum
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：2
• 期：1
• 页码：20-25
• 全文大小：2067 K

文摘

Currently, the three-dimensional distribution of interlayer is realized by stochastic modeling. Traditionally, the three-dimensional geological modeling controlled by sedimentary facies models is built on the basis of logging interpretation parameters and geophysical information. Because of shallow gas-cap, the quality of three-dimensional seismic data vertical resolution in research area cannot meet the interlayer research that is below ten meters. Moreover, sedimentary facies cannot commendably reveal interlayer distribution and the well density is very sparse in research area. So, it is difficult for conventional technology to finely describe interlayers. In this document, it uses L₁-L₂ combined norm constrained inversion to enhance the recognition capability of interlayer in seismic profile and improve the signal to noise ratio, the wave group characteristics and the vertical resolution of three-dimensional data and classifies petrophysical facies of interlayer based on core, sedimentary facies and logging interpretation. The interlayer model which is based on seismic inversion model and petrophysical facies can precisely simulate the distribution of reservoir and interlayer. The results show that the simulation results of this new methodology are consistent with the dynamic production perfectly which provide a better basis for producing and mining remaining oil and a new interlayer modeling method for sparse well density.