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Combining CSEM or gravity inversion with seismic AVO inversion, with application to monitoring of large-scale CO 2 injection
Computational Geosciences ( IF 2.5 ) Pub Date : 2020-03-09 , DOI: 10.1007/s10596-020-09934-9
Svenn Tveit , Trond Mannseth , Joonsang Park , Guillaume Sauvin , Remy Agersborg

A sequential inversion methodology for combining geophysical data types of different resolutions is developed and applied to monitoring of large-scale CO2 injection. The methodology is a two-step approach within the Bayesian framework where lower resolution data are inverted first, and subsequently used in the generation of the prior model for inversion of the higher resolution data. For the application of CO2 monitoring, the first step is done with either controlled source electromagnetic (CSEM) or gravimetric data, while the second step is done with seismic amplitude-versus-offset (AVO) data. The Bayesian inverse problems are solved by sampling the posterior probability distributions using either the ensemble Kalman filter or ensemble smoother with multiple data assimilation. A model-based parameterization is used to represent the unknown geophysical parameters: electric conductivity, density, and seismic velocity. The parameterization is well suited for identification of CO2 plume location and variation of geophysical parameters within the regions corresponding to inside and outside of the plume. The inversion methodology is applied to a synthetic monitoring test case where geophysical data are made from fluid-flow simulation of large-scale CO2 sequestration in the Skade formation. The numerical experiments show that seismic AVO inversion results are improved with the sequential inversion methodology using prior information from either CSEM or gravimetric inversion.

中文翻译:

将CSEM或重力反演与地震AVO反演相结合,可用于监测大规模CO 2注入

开发了一种结合不同分辨率的地球物理数据类型的序贯反演方法,并将其应用于大规模CO 2注入的监测。该方法是贝叶斯框架内的两步方法,其中首先将较低分辨率的数据反转,然后将其用于生成先前模型以反转高分辨率数据。用于CO 2的应用监测,第一步是使用受控源电磁(CSEM)或重力数据完成的,而第二步是使用地震振幅与偏移(AVO)数据完成的。通过使用集合卡尔曼滤波器或具有多个数据同化的集合平滑器对后验概率分布进行采样,可以解决贝叶斯逆问题。基于模型的参数化用于表示未知的地球物理参数:电导率,密度和地震速度。该参数设置非常适合于CO 2的识别羽的位置以及与羽内部和外部相对应的区域内的地球物理参数的变化。该反演方法应用于合成监测测试案例,其中地球物理数据是通过在Skade地层中大规模固存CO 2的流体流动模拟获得的。数值实验表明,利用CSEM或重力反演的先验信息,采用顺序反演方法可以改善地震AVO反演结果。
更新日期:2020-03-09
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