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.

Andrew J. Moodie 博士获得了 NSF EAR 博士后奖学金，将分别与导师 Paola Passalacqua 博士和 Jef Caers 博士合作，在德克萨斯大学奥斯汀分校和斯坦福大学开展研究和教育计划。研究多尺度沉积岩的特性，以建立大尺度地质变化（~10 m）和小尺度变化（~10 cm）之间的联系。地球物理成像无法解决小尺度地质变化，然而，穆迪博士希望利用统计模型和对更大规模变化的观察来限制这种变化，这项研究对于沿海河流三角洲的可持续性至关重要，因为这些环境受到对地下地质和流动路径的有限了解的影响。对流体流动路径的进一步了解将影响许多领域，特别是，这项研究的结果将为污染物输送模型、地下水资源管理、浅层地热和碳封存操作以及碳氢化合物生产提供信息。 。穆迪博士的教育计划包括指导学生、组织有关地球科学机器学习的阅读研讨会，以及开发沉积岩地层学主题的主动学习模块沿海河流三角洲的可持续性受到多种自然和人为因素的影响。包括对地下水流模式的有限了解，强烈影响水流路径，从而影响污染物迁移和地下水含水层补给的速度，这限制了我们可持续管理水资源和减轻河流三角洲健康风险的能力。由于河道和地床形态动力学（小于 1 m）造成的较小规模的地下非均质性通常受到限制，因为它低于现有地球物理技术可以成像的分辨率，并且一些证据表明地层序列可能会受到限制。是尺度不变的，这开辟了一条通过观察较大尺度异质性来约束较小尺度异质性的途径，该项目直接解决了这样的问题：从一个空间尺度的地下异质性中收集的模式和信息是否可以用于约束不确定性。 EAR 博士后奖学金将使 Moodie 博士能够 1）严格研究地层学的尺度不变特性，2）将这些发现整合到定量方法中以限制地下异质性。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将量化地层学中的尺度不变性，并且将修改现有的生成对抗神经网络方法以绘制跨空间的异质性。该项目由地球科学部门 (EAR) 的沉积地质学和古生物学项目共同资助。该奖项是 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

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: 2022-10
• 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

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

模拟河流三角洲对海平面上升加速度的动态响应

• DOI: 10.1029/2022jf006762
• 发表时间: 2022-09
• 期刊: Journal of Geophysical Research: Earth Surface
• 作者: Hariharan, Jayaram;Passalacqua, Paola;Xu, Zhongyuan;Michael, Holly A.;Steel, Elisabeth;Chadwick, Austin;Paola, Chris;Moodie, Andrew J.
• 通讯作者: Moodie, Andrew J.

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: 2021-08
• 期刊: Journal of Open Source Software
• 作者: Moodie, Andrew;Hariharan, Jayaram;Barefoot, Eric;Passalacqua, Paola
• 通讯作者: Passalacqua, Paola