Numerical Estimation of Multiple Positions of Seepage of Dissolved Matter From Seafloor

Shunsuke Kanao, Toru Sato
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Abstract

To mitigate global warming, it is necessary to emit less CO2 into the atmosphere and the Carbon dioxide Capture and Storage (CCS) attracts attention these days as one of the solutions against the problem. Off Tomakomai coast, Japan, a CCS project has been demonstrated since 2016. However, there may be a risk of CO2 leakage and consequent seepage from the seafloor, even if the probability of such an event is almost nil. In this research, we assumed that CO2 seeps from multiple points on the seafloor and aimed at estimating the seepage locations, time and fluxes, by using CO2 concentration data observed by several sensors set on the seafloor. We adopted the adjoint marginal sensitivity method, which is a probabilistic time-backward method: an adjoint location probability is released by each sensor and spreads in the time-backward direction. The adjoint location probabilities are used to estimate the seepage fluxes. We also combined the least squares method with the adjoint marginal sensitivity method to estimate the seepage fluxes. We considered that CO2 seeps from 2 points in 2-dimensional horizontal domains as test calculations with changing seepage flux ratios, such as 1:1, 1:0.1 or 1:0.01.
海底溶解物多位置渗流的数值估计
为了减缓全球变暖,必须减少向大气中排放二氧化碳,而二氧化碳捕获和储存(CCS)作为解决这一问题的方法之一,受到了人们的关注。自2016年以来,在日本Tomakomai海岸,一个CCS项目一直在进行演示。然而,可能会有二氧化碳从海底泄漏和随之而来的渗漏的风险,即使这种事件的可能性几乎为零。在本研究中,我们假设CO2从海底的多个点渗漏,并利用设置在海底的多个传感器观测到的CO2浓度数据来估计渗漏的位置、时间和通量。我们采用伴随边缘灵敏度法,这是一种概率时间向后方法,每个传感器释放一个伴随定位概率,并在时间向后方向扩散。利用伴随位置概率估计渗流通量。并结合最小二乘法和伴随边际灵敏度法对渗流通量进行估计。我们考虑CO2从二维水平域中的两个点渗出作为试验计算,其渗流通量比变化为1:1、1:0.1或1:0.01。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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