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CO2 Injection Monitoring Using Transient Electromagnetic in Ground-borehole Configuration

Authors: Kai Li; Huaifeng Sun; Ming Cheng; Jianlei Guo;

CO2 Injection Monitoring Using Transient Electromagnetic in Ground-borehole Configuration

Abstract

ABSTRACT Using geophysical methods, specifically transient electromagnetic (TEM), for CO2 monitoring is an effective way to detect CO2 diffusion. In this work, a multi-scale finite-difference time-domain (FDTD) algorithm was established to monitor CO2 by defining new iterative relations and approximating boundary conditions, which achieves unification in the time and space domain. The response curve characteristics of different forms of CO2 were acquired by changing the receiver's depth and position, CO2 resistivity, scale, and injection stage. Different models considering a planar, tilted, and large-scale CO2 bodies, which were established to test the capacity of TEM monitoring for CO2. The TEM response of injected CO2 bodies had obvious characteristics and the response curve had distinguishable differences from background. This phenomenon could provide reference models for real TEM CO2 monitoring.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
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