CNH-Ex: A Model for Groundwater Allocation and Management at the Bakken Shale in Western North Dakota

自2008年以来，由于水力压裂技术（也称为“水力压裂”）的进步，美国的非常规石油和天然气产量急剧增加。根据时代杂志（2013年10月14日），自2008年以来，北达科他州西部巴肯页岩的石油产量增加了约10倍，而二叠纪盆地和德克萨斯州鹰福特页岩的石油产量在同一时期增加了一倍多。宾夕法尼亚州和纽约的马塞勒斯页岩以及怀俄明州和科罗拉多的尼奥布拉拉页岩也有类似的情况。而陆上页岩油气开发无疑增加了国家？由于缺乏对这一新课题领域的研究和数据收集，人们对能源生产及其对自然环境的影响，特别是对当地水资源的影响仍然知之甚少。该项目是对北达科他州西部巴肯页岩的能源-水关系的试点研究，利用数学建模更好地了解该地区人类和自然系统之间的复杂相互作用，这些系统正在导致前所未有的经济发展和水资源的利用。这项跨学科研究还将揭示当前行业实践与政府政策之间的差距。鉴于水力压裂的使用仍在增加，巴肯页岩研究的结果将对该国水力压裂产油区及其周围的政策制定者和社区具有重要意义。北达科他州西部能源丰富但水资源稀缺的地区非常规油气生产的快速扩张催生了一种新颖的水分配系统--蓄水库，分配大量淡水用于农村地区的工业用途。该地区最大的含水层，福克斯山-地狱溪（FH-HC）含水层，是北达科他州和蒙大拿州农村牲畜饮水的唯一可靠水源。然而，由于石油工业的大规模用水需求，人们越来越关注FH-HC含水层现有和潜在的取水问题。必须了解以水库为基础的水分配系统的动态及其与地下水系统的相互作用。该项目将开发一个综合水文经济模型，研究耦合的蓄水池-地下水系统的动态，以便制定适当的政策工具，管理区域地下水资源，供长期、可持续使用。将采用以下方法来实现这一目标。(1)将开发一个基于代理的模型来研究北达科他州西部巴肯页岩的基于水库的水分配系统的应急模式和动态。(2)基于代理的模型将与区域地下水模型相结合，以模拟未来社会经济和气候情景下FH-HC含水层水位的变化率。(3)由于参数不确定和模型结构不精确，将开发贝叶斯模型平均法，以估计与地下水模型预测相关的方差。

Unconventional oil and gas production in U.S. has increased dramatically since 2008 due to advancement in hydraulic fracturing technology (also known as "fracking"). According to Time Magazine (October 14, 2013), the oil production at the Bakken Shale of western North Dakota increased about ten times since 2008 while the combined oil production at the Permian Basin and Eagle Ford Shale in Texas more than doubled in the same time period. Similar stories can also be told for the Marcellus Shale in Pennsylvania and New York and the Niobrara Shale in Wyoming and Colorado. Whereas the onshore shale oil and gas development has indisputably increased the nation?s energy production, its impact on natural environment, especially on local water resources, remains poorly understood due to the lack of research and data collection for this new subject area. This project is a pilot study of the energy-water nexus at the Bakken Shale of western North Dakota, using mathematical modeling to gain a better understanding of the complex interactions between the region's human and natural systems that are leading to unprecedented economic development and use of water resources. This interdisciplinary study will also shed light on the gaps between current industry practices and government policy. Given that the use of hydraulic fracturing is still on the rise, the findings from this Bakken Shale study will be of great importance to policymakers and communities in and around the hydraulic fracturing oil regions in the country.The rapid expansion of unconventional oil and gas production in western North Dakota, a region rich in energy but scarce in water, has given birth to a novel water allocation system - water depots, to distribute a large quantity of freshwater for industrial uses in rural areas. The region's largest aquifer, the Fox Hills-Hell Creek (FH-HC) aquifer, is the sole reliable water source for livestock watering in rural North Dakota and Montana. However, there are growing concerns about the existing and potential water withdrawal from the FH-HC aquifer due to the large-scale water demand by the oil industry. It is imperative to understand the dynamics of the water depot-based water allocation system and its interactions with the underlying groundwater systems. This project will develop an integrated hydro-economic model to study the dynamics of the coupled water depot-groundwater system so that appropriate policy tools may be devised to manage the regional groundwater resources for long-term, sustainable use. The following methods will be employed to achieve this goal. (1) An agent-based model will be developed to study the emergent patterns and dynamics of the water depot-based water allocation system at the Bakken Shale in western North Dakota. (2) The agent-based model will be integrated with the regional groundwater model to simulate the rate of changes in the water levels of the FH-HC aquifer under future socioeconomic and climate scenarios. (3) A Bayesian model averaging method will be developed to estimate the variance associated with groundwater model predictions due to uncertain parameters and imprecise model structures.