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Sensor systems to monitor injection and long-term subsurface storage of carbon dioxide

Sensor systems to monitor injection and long-term subsurface storage of carbon dioxide
用于监测二氧化碳注入和长期地下储存的传感器系统
批准号:
RGPIN-2015-03968
负责人:
Wild, Peter
金额:
$2.48万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2016
资助国家:
加拿大
项目状态:
已结题
起止时间:
2016-01-01 至 2017-12-31

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中文摘要
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英文摘要
Carbon capture and sequestration is an emerging technology in which CO2 is captured or separated at the emission source, liquefied and then injected into deep geologic reservoirs for long term storage. This process has the potential to play a central role in mitigating rising levels of anthropogenic CO2 in the atmosphere. However, widespread adoption will require accurate and reliable long term monitoring to provide assurance of secure storage. State-of-the-art monitoring methods cannot provide this assurance.  Geophysical methods are unable to detect dissolved and mineralized CO2 in deep formations while geochemical methods are based on down hole sampling which precludes high sample rates and is confounded by changes of state that occur as the sample is raised to the surface. There is, therefore, an urgent need for methods to gather high frequency CO2 concentration data in situ from the deep formations where CO2 is injected and in adjacent formations into which CO2 may migrate. The proposed Research Program addresses this need through research and development of fiber optic sensors to monitor concentrations of CO2 in and adjacent to the storage formation. Fiber optic sensor systems are well-suited to the downhole environment due to their high spatial and temporal resolution, low signal loss over long transmission distances and immunity to electromagnetic interference and short circuits. The sensors that we will research and develop will monitor CO2 concentrations of downhole fluids in situ using fiber optic devices that will include: Long Period Gratings, Photonic Crystal Fiber Mach-Zehnder Interferometers and Fiber Tip Refractometers. These sensors will gather refractive index data that will be used to determine CO2 concentrations in the multi-fluid downhole environment. These sensors will also be used to determine phase and species (e.g. brine, liquid hydrocarbon, gaseous methane, liquid CO2) which will enable monitoring of possible leakage of CO2 at deep ocean injection sites where CO2 and methane can both be present and can be challenging to distinguish. The proposed Research Program includes development and testing of sensors in the laboratory and field deployments at both land-based and deep ocean sites. The proposed Research Program will also have application beyond monitoring of CO2 storage sites. In particular, higher sensitivity to CO2 concentrations will enable these sensors to be used for measurements of natural levels and fluxes of CO2 in the shallow subsurface which are essential to assessing the impacts of human activity on CO2 concentrations in the atmosphere. Enhanced RI sensitivity will also enable a wide range of non-CO2 applications in which RI is or has potential to be a key indicating parameter.
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Sensor systems to monitor injection and long-term subsurface storage of carbon dioxide
  • 批准号:
    RGPIN-2015-03968
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2019
  • 负责人:
    Wild, Peter
  • 依托单位:
Sensor systems to monitor injection and long-term subsurface storage of carbon dioxide
  • 批准号:
    RGPIN-2015-03968
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2018
  • 负责人:
    Wild, Peter
  • 依托单位:
Sensor systems to monitor injection and long-term subsurface storage of carbon dioxide
  • 批准号:
    477917-2015
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
  • 资助金额:
    $2.91万
  • 财政年份:
    2017
  • 负责人:
    Wild, Peter
  • 依托单位:
Sensor systems to monitor injection and long-term subsurface storage of carbon dioxide
  • 批准号:
    RGPIN-2015-03968
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2017
  • 负责人:
    Wild, Peter
  • 依托单位:
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