V017
Data-Driven Discoveries in Volcanology, Geochemistry and Petrology
Session ID#: 74549
Session Description:
The increasing generation velocity, volume and variety (3Vs) of geoscience data, combined with the advancement in data science techniques (e.g., data mining, machine learning and deep learning), provide geoscientists new perspectives about knowledge discovery by utilizing large and complex data. In this session, we welcome presentations including but not limited to: 1) Volcanology studies about magmas and volatiles erupted from volcanoes at hotspots, island and continental arcs and ocean ridges etc; 2) Geochemistry and petrology studies about compositions and evolution of Earth’s interior; 3) Deep-time Earth studies about mineralogy and interactions of the geosphere and biosphere; 4) Cross disciplinary and multivariate analysis through the integration of physical, chemical and biological characterizations of the natural systems, e.g., critical zone studies.
Co-Organized:
Index Terms:
0498 General or miscellaneous [BIOGEOSCIENCES]
1099 General or miscellaneous [GEOCHEMISTRY]
1916 Data and information discovery [INFORMATICS]
3699 General or miscellaneous [MINERALOGY AND PETROLOGY]
Primary Convener: Fang Huang, Rensselaer Polytechnic Institute, Tetherless World Constellation, Troy, NY, United States
Conveners: Shaunna M Morrison, Geophysical Laboratory of the Carnegie Institution for Science, Washington, DC, United States, Tao Wen, Pennsylvania State University, Earth and Environmental Systems Institute, University Park, PA, United States and Anirudh Prabhu, Rensselaer Polytechnic Institute, Tetherless World Constellation, Troy, NY, United States
Primary Liaison: Shaunna M Morrison, Geophysical Laboratory of the Carnegie Institution for Science, Washington, DC, United States
Contextualising Paleomagnetic Records with Multiscale Microscopy, Microanalytics and Machine Learning (490925)
Joshua Franz Einsle, Imperial College London, Department of Earth and Enviromental Scicences, London, United Kingdom, Rich Taylor, University of Cambridge, Earth Sciences, Cambridge, United Kingdom, Luke Daly, University of Glasgow, School of Geographical & Earth Sciences, Glasgow, United Kingdom, Helen M. Williams, University of Durham, Durham, United Kingdom; University of Cambridge, Cambridge, United Kingdom, Ian MacLaren, University of Glasgow, SCHOOL OF PHYSICS & ASTRONOMY, Glasgow, United Kingdom, Adrian R Muxworthy, Imperial College London, Earth Science and Engineering, London, United Kingdom and Richard J Harrison, Univ Cambridge, Cambridge, United Kingdom
A comparison of dimensionality reduction techniques in hydrogeochemistry (495896)
Jon K Golla, University of Illinois at Urbana-Champaign, Department of Geology, Urbana, IL, United States and Cary Lindsey, University of Nevada Reno, Great Basin Center for Geothermal Energy, Reno, NV, United States
Abiotic hydrocarbon formation in serpentinization experiments: network analysis on a comprehensive dataset (503690)
Fang Huang1, Samuel Barbier2,3, Muriel Andreani3, Renbiao Tao3, Jihua Hao3, Ahmed Eleish1, Anirudh Prabhu1, Osama Minhas4, Kathleen S Fontaine1, Peter Arthur Fox1 and Isabelle Daniel3,5, (1)Rensselaer Polytechnic Institute, Tetherless World Constellation, Troy, NY, United States, (2)TOTAL - Centre Scientifique et Technique Jean Feger, Pau, France, (3)University Claude Bernard Lyon 1, Villeurbanne, France, (4)Rensselaer Polytechnic Institute, Troy, NY, United States, (5)Ecole Normale Supérieure Lyon, Lyon, France
Geochemical database of Japanese islands based on published domestic data: standardization of data and high-precision location coordinates (505213)
Satoru Haraguchi1, Kenta Ueki2, Kenta Yoshida2, Tatsu Kuwatani2, Mika Mohamed2 and Hikaru Iwamori1, (1)Earthquake Research Institute, the University of Tokyo, Tokyo, Japan, (2)JAMSTEC Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan
Unsupervised learning exposes magma dynamics during the 2014-2015 Holuhraun-Bardarbunga eruption (Iceland) (505542)
Luca Caricchi1, Tom Sheldrake2, Enikő Bali3, Maurizio Petrelli4, Laura Pioli5 and Guy Simpson1, (1)University of Geneva, Geneva, Switzerland, (2)University of Geneve, Earth Sciences, Geneve, Switzerland, (3)University of Iceland, NordVulk, Institute of Earth Sciences, Reykjavik, Iceland, (4)University of Perugia, Perugia, Italy, (5)University of Cagliari, Dipartimento di Scienze Chimiche e Geologiche, Cagliari, Italy
Blind Source Separation of Large Geochemical Datasets to Understand Recharge, Assimilation, and Fractional Crystallization Within Crustal Magma Reservoirs (509793)
Rachel Hampton, University of Oregon, Eugene, OR, United States and Leif Karlstrom, University of Oregon, Department of Earth Sciences, Eugene, OR, United States
Data-driven discovery in mineralogy: Insights from natural kind clustering (Invited) (518673)
Robert M Hazen1, Shaunna M Morrison1, Shuang Zhang1, Asmaa Boujibar1, Anirudh Prabhu2, Peter Arthur Fox2, Ahmed Eleish2, Fang Huang2, Chao Liu1, Chao Ma3, Xiaogang Ma4, Ross Raymond Large5, Daniel Gregory6, Samantha Howell1 and Larry R Nittler7, (1)Carnegie Institution for Science, Geophysical Laboratory, Washington, DC, United States, (2)Rensselaer Polytechnic Institute, Tetherless World Constellation, Troy, NY, United States, (3)University of Idaho, Moscow, United States, (4)University of Idaho, Moscow, ID, United States, (5)University of Tasmania, Hobart, Australia, (6)University of Toronto, Toronto, ON, Canada, (7)Carnegie Institution of Washington, Washington, DC, United States
Use of Statistical Methods and Geospatial Techniques in Understanding Riverine Geochemistry (533608)
Lino Yovan1, Alakendra N Roychoudhury2, K Balakrishna1, Mohandas Chadaga1 and Udayashankar H N1, (1)Manipal Institute of Technology, Manipal, India, (2)Stellenbosch University, Earth Sciences, Stellenbosch, South Africa
Compiling geochemistry, geochronology and physical information of EAR explosive events to constrain the spatial and temporal evolution of the rift. (547539)
Sara Mana, Salem State University, Salem, MA, United States, Karen Fontijn, Université libre de Bruxelles, Brussels, Belgium and Erin DiMaggio, Penn State University, State College, PA, United States
Natural kind clustering of presolar silicon carbides and its astrophysical implications (556586)
Asmaa Boujibar1, Shuang Zhang1, Samantha Howell2, Anirudh Prabhu3, Shweta Narkar3, Grethe Hystad4, Ahmed Eleish3, Shaunna M Morrison1, Robert Hazen1 and Larry R Nittler5, (1)Carnegie Institution for Science, Geophysical Laboratory, Washington, DC, United States, (2)Washington College, Department of Physics, Chestertown, MD, United States, (3)Rensselaer Polytechnic Institute, Tetherless World Constellation, Troy, NY, United States, (4)Purdue University Northwest, Mathematics, Statistics and Computer Science, Hammond, DC, United States, (5)Carnegie Institution for Science, Department of Terrestrial Magnetism, Washington, DC, United States
Strombolian Eruption Detection Using an Onsite-Ready Convolutional Neural Network on Mount Erebus, Antarctica (567564)
Brian Dye, Environmental Protection Agency, Dallas, TX, United States, Taylor Privat, University of Louisiana at Lafayette, Lafayette, LA, United States and Gabriele Morra, University of Louisiana at Lafayette, Department of Physics and School of Geosciences, Lafayette, LA, United States
Tracking the evolution of our planet using large scale geochemistry and metagenomic data (Invited) (584054)
Donato Giovannelli1, Joy Buongiorno2, Anirudh Prabhu3, Ahmed Eleish3, Fang Huang3, Peter Arthur Fox3, Robert Hazen4 and Shaunna M Morrison4, (1)University of Naples Federico II, Department of Biology, Naples, Italy, (2)University of Tennessee, Knoxville, TN, United States, (3)Rensselaer Polytechnic Institute, Tetherless World Constellation, Troy, NY, United States, (4)Carnegie Institution for Science, Geophysical Laboratory, Washington, DC, United States
Statistical Coupling of Geography, Mantle History and Isotope Geochemistry in MORB (597132)
Xiang Ling1, Jonathan Snow1,2 and Wynne W. Chin3, (1)University of Houston, Earth and Atmospheric Sciences, Houston, TX, United States, (2)Louisiana State University, Geology & Geophysics, Baton Rouge, TX, United States, (3)University of Houston, Decision & Information Sciences, Houston, TX, United States
A machine learning-based ensemble model to detect methane contamination in groundwater within hydrocarbon production areas across the United States (598514)
Tao Wen1, Mengqi Liu2, Zhenhui (Jessie) Li2 and Susan Brantley1,3, (1)Pennsylvania State University, Earth and Environmental Systems Institute, University Park, PA, United States, (2)Pennsylvania State University, College of Information Sciences and Technology, University Park, PA, United States, (3)Pennsylvania State University, Department of Geosciences, University Park, PA, United States
Rich, Accurate Real-time Event Catalogs for the Island of Hawaiʻi - an Application of Machine Learning to Earthquake Detection in a Volcanic Context (599050)
Ian Pritchard, Andrew Reynen, Emrah Yenier, Dario Baturan, Andrew Moores, David Shorey and Neil Spriggs, Nanometrics Inc, Kanata, ON, Canada
H2O or fO2? Deciphering the Dominant Determinant of Differentiation trends:a Monte Carlo MELTS Methodology (611340)
Bradley William Pitcher1, Guilherme A R Gualda2, Mark S Ghiorso3, Genna Chiaro1, Lydia Harmon1, Susanne Seitz1, Blake M Wallrich1 and Lei Yang4, (1)Vanderbilt University, Earth and Environmental Sciences, Nashville, TN, United States, (2)Vanderbilt University, Department of Earth and Environmental Sciences, Nashville, TN, United States, (3)OFM Research, Redmond, CA, United States, (4)University of Chinese Academy of Sciences, Beijing, China
