EAR-PF: Quantifying heterogeneity in stratigraphy across scales

EAR-PF：量化跨尺度地层学的异质性

• 批准号: 1952772
• 负责人: Andrew Moodie
• 金额: $ 17.4万
• 依托单位: Moodie, Andrew J
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1952772&HistoricalAwards=false
• 关键词: EAR; PF; Quantifying; heterogeneity; stratigraphy

Dr. Andrew J. Moodie has been awarded an NSF EAR Postdoctoral Fellowship to carry out research and education plans at The University of Texas at Austin and Stanford University in collaboration with mentors Dr. Paola Passalacqua and Dr. Jef Caers respectively. This study aims to investigate the properties of sedimentary rocks across multiple scales, to draw connections between large scale geological variability (~10 m) and smaller-scale variability (~10 cm). Geophysical imaging is unable to resolve small-scale geological variability, however, Dr. Moodie expects to constrain this variability using statistical models and observations of larger-scale variability. This research is critical to the sustainability of coastal river-deltas, because these environments are impacted by a limited understanding of subsurface geology and flow pathways that are controlled by small-scale geological variability. Improved understanding of fluid-flow pathways will influence many fields, in particular, results of this research will inform pollutant transport modeling, groundwater resource management, shallow geothermal and carbon sequestration operations, as well as hydrocarbon production. Dr. Moodie’s education plan includes mentoring students, organizing a reading seminar about machine learning in the geosciences, and developing active learning modules for topics in sedimentary rock stratigraphy. The sustainability of coastal river-deltas is impacted by a multitude of natural and anthropogenic factors, including a limited understanding of subsurface flow patterns. Geological heterogeneity strongly influences flow pathways and thus rates of contaminant transport and groundwater aquifer recharge, which limits our ability to sustainably manage water resources and mitigate health risks in river-delta environments. Smaller-scale subsurface heterogeneity due to channel and bedform dynamics (of less than 1 m) is typically under-constrained, because it is below the resolution that can be imaged by existing geophysical techniques. Theory and some evidence suggest that stratigraphic sequences may be scale invariant, which opens a pathway to constrain smaller-scale heterogeneity via observation of larger-scale heterogeneity. This project directly addresses the question: can patterns and information gleaned from subsurface heterogeneity at one spatial scale be used to constrain uncertainty at another scale? The EAR Postdoctoral Fellowship, will allow Dr. Moodie to 1) rigorously investigate scale invariant properties of stratigraphy, and 2) integrate these findings into a quantitative method to constrain subsurface heterogeneity. He will use a combination of approaches, including field measurement, numerical modeling, statistical data analysis, and machine learning. Measures from information theory will quantify scale invariance in stratigraphy, and an existing generative adversarial neural network method will be modified to map heterogeneity across spatial scales. This project was co-funded by the Sedimentary Geology and Paleobiology program in the Earth Science division (EAR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

安德鲁·J·穆迪（Andrew J. Moodie）博士分别与德克萨斯大学奥斯汀大学和斯坦福大学的大学一起，分别与导师Paola Passalacqua博士和Jef Caers博士合作。这项研究旨在研究跨多个尺度的沉积岩的特性，以在大规模地质变异性（〜10 m）和较小规模的变异性（〜10 cm）之间建立联系。地球物理成像无法解决小规模的地质变异性，但是，穆迪博士希望使用统计模型和更大尺度可变性的观察来限制这种可变性。这项研究对于沿海河流河的可持续性至关重要，因为这些环境受到对地下地质和流道的有限理解的影响，而小规模对流体流动途径的了解得到了改善的理解，这将影响许多领域，尤其会影响该研究的结果，尤其会影响该研究的结果，将为污染，地下水资源管理，地球地球层层次层层次层层次层造型效果以及水分层造型。穆迪博士的教育计划包括心理学生，组织有关地球科学中机器学习的开创性的阅读，并为沉积岩层层学主题开发主动学习模块。沿海河 - 戴尔达斯河的可持续性受到多种自然和人为因素的影响，包括对地下流动模式的了解有限。地质异质性强烈影响流道，从而影响污染物运输和地下水含水层补给的速率，这限制了我们可持续管理水资源并减轻河流环境中健康风险的能力。由于通道和床形动力学（小于1 m）引起的较小尺度的地下异质性通常不受限制，因为它低于现有地球物理技术可以成像的分辨率。理论和一些证据表明地层序列可能是规模不变的，这为通过观察大规模异质性而开辟了限制较小规模异质性的途径。该项目直接解决了以下问题：使用一个空间尺度的地下异质性收集的模式和信息可以用来限制另一个量表的不确定性吗？耳朵博士后奖学金将使穆迪博士到1）严格研究地层学的规模不变特性，2）将这些发现整合到一种定量方法中，以约束地下异质性。他将使用多种方法，包括现场测量，数值建模，统计数据分析和机器学习。信息理论的措施将量化层学中的尺度不变性，现有的通用对抗性神经元网络方法将被修改以在空间尺度上绘制异质性。该项目是由地球科学部（EAR）的沉积地质和古生物学计划共同资助的。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，通过评估被认为是珍贵的支持。

项目成果

pyDeltaRCM: a flexible numerical delta model

pyDeltaRCM：灵活的数值增量模型

• DOI: 10.21105/joss.03398
• 发表时间: 2021
• 期刊: Journal of Open Source Software
• 作者: Moodie, Andrew;Hariharan, Jayaram;Barefoot, Eric;Passalacqua, Paola
• 通讯作者: Passalacqua, Paola

Modeling the Dynamic Response of River Deltas to Sea‐Level Rise Acceleration

• DOI: 10.1029/2022jf006762
• 发表时间: 2022-09
• 期刊: Journal of Geophysical Research: Earth Surface
• 作者: J. Hariharan;P. Passalacqua;Zhongyuan Xu;H. Michael;E. Steel;A. Chadwick;C. Paola;A. Moodie

SedEdu: software organizing sediment-related educational modules

SedEdu：组织沉积物相关教育模块的软件

• DOI: 10.21105/jose.00129
• 发表时间: 2022
• 期刊: Journal of Open Source Education
• 作者: Moodie, Andrew;Carlson, Brandee;Foreman, Brady;Kwang, Jeffrey;Naito, Kensuke;Nittrouer, Jeffrey
• 通讯作者: Nittrouer, Jeffrey