首页> 美国卫生研究院文献>Scientific Reports >Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site
【2h】

Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site

机译:地质碳储藏区的高于区域压力预测的概率评估

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Carbon dioxide (CO2) storage into geological formations is regarded as an important mitigation strategy for anthropogenic CO2 emissions to the atmosphere. This study first simulates the leakage of CO2 and brine from a storage reservoir through the caprock. Then, we estimate the resulting pressure changes at the zone overlying the caprock also known as Above Zone Monitoring Interval (AZMI). A data-driven approach of arbitrary Polynomial Chaos (aPC) Expansion is then used to quantify the uncertainty in the above zone pressure prediction based on the uncertainties in different geologic parameters. Finally, a global sensitivity analysis is performed with Sobol indices based on the aPC technique to determine the relative importance of different parameters on pressure prediction. The results indicate that there can be uncertainty in pressure prediction locally around the leakage zones. The degree of such uncertainty in prediction depends on the quality of site specific information available for analysis. The scientific results from this study provide substantial insight that there is a need for site-specific data for efficient predictions of risks associated with storage activities. The presented approach can provide a basis of optimized pressure based monitoring network design at carbon storage sites.
机译:将二氧化碳(CO2)存储到地质构造中被认为是减少人为排放到大气中的重要策略。这项研究首先模拟了二氧化碳和盐水从储层通过盖层泄漏的情况。然后,我们估算在覆盖层上方的区域(也称为“高于区域监测间隔”(AZMI))上产生的压力变化。然后,使用数据驱动的任意多项式混沌(aPC)扩展方法,基于不同地质参数中的不确定性来量化上述区域压力预测中的不确定性。最后,基于aPC技术对Sobol指数进行全局敏感性分析,以确定不同参数对压力预测的相对重要性。结果表明,泄漏区域周围的压力预测可能存在不确定性。预测中这种不确定性的程度取决于可用于分析的特定于站点的信息的质量。这项研究的科学结果提供了实质性的见识,即需要特定于站点的数据来有效预测与存储活动相关的风险。提出的方法可以为碳存储站点中基于压力的优化监控网络设计提供基础。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号