Abstract

This study explores the effect of different phases of unconventional shale gas well-pad development on ambient air quality and the relationship between ambient concentrations of air pollutants and operator activity. The U.S. Department of Energy’s National Energy Technology Laboratory operated a mobile air-monitoring laboratory on two shale well pad sites in Pennsylvania and six shale well pad sites in West Virginia. The purpose of this study is to integrate expert knowledge and collected ambient air monitoring data by developing a Bayesian network (BN) model. The monitoring period included well-pad site development; construction, including vertical and horizontal drilling; hydraulic fracturing; flowback; and production. The observed data includes meteorological data with high time resolution and air quality data (volatile organic compounds (VOCs), ozone, methane and carbon isotopes in methane, carbon dioxide (CO₂) and carbon isotopes in CO₂, coarse and fine particulate matter (PM₁₀ and PM_2.5), and organic and elemental carbon). The results provide useful information for evaluating the influence of on- and off-site pollutant sources and determining future research efforts for building the BN model. The overall results of the developed six scenarios show that the prediction power of the proposed model for the vertical drilling phase is 94%. The high concentration of methane increases the probability of fracturing phase as source; the low concentration of PM₁₀ and O₃ occurrence increases the same probability to 82%; the low concentration of ethane and CO₂ increases the probability to 98%. This study shows how expert Bayesian models can improve our ability to predict future air pollution risk associated with unconventional shale gas development.

摘要

本研究探讨了非常规页岩气井垫开发不同阶段对环境空气质量的影响以及环境空气污染物浓度与操作员活动之间的关系。美国能源部的国家能源技术实验室在宾夕法尼亚州的两个页岩井垫站点和西弗吉尼亚州的六个页岩井垫站点上运行了一个移动式空气监测实验室。本研究的目的是通过开发贝叶斯网络（BN）模型来整合专家知识和收集的环境空气监测数据。监测期包括开发井场；施工，包括垂直和水平钻孔；水力压裂; 飘回去; 和生产。观测数据包括具有高时间分辨率的气象数据和空气质量数据（挥发性有机化合物（VOC），₂）和CO ₂，粗粒和细粒物质（PM ₁₀和PM _2.5）以及有机碳和元素碳中的碳同位素。研究结果为评估现场和非现场污染物源的影响以及确定建立BN模型的未来研究工作提供了有用的信息。所开发的六个方案的总体结果表明，所提出的模型在垂直钻井阶段的预测能力为94％。高浓度的甲烷增加了压裂相作为源的可能性。低浓度的PM ₁₀和O _3的出现将相同的可能性提高到82％。乙烷和CO ₂浓度低将该机率提高到98％。这项研究表明专家贝叶斯模型如何提高我们预测与非常规页岩气开发相关的未来空气污染风险的能力。