Preprints

Filtering by Subject: Multivariate Analysis

Sedimentary structures discriminations with hyperspectral imaging on sediment cores

Kévin Jacq, Rapuc William, Benoit Alexandre, Coquin Didier, Fanget Bernard, Yves Perrette, Pierre Sabatier, Wilhelm Bruno, Debret Maxime, Fabien Arnaud

Published: 2020-07-18
Subjects: Analytical Chemistry, Chemistry, Earth Sciences, Environmental Chemistry, Environmental Monitoring, Environmental Sciences, Multivariate Analysis, Optics, Physical Sciences and Mathematics, Physics, Sedimentology, Statistical Models, Statistics and Probability

Hyperspectral imaging (HSI) is a non-destructive high-resolution sensor, which is currently under significant development to analyze geological areas with remote devices or natural samples in a laboratory. In both cases, the hyperspectral image provides several sedimentary structures that need to be separated to temporally and spatially describe the sample. Sediment sequences are composed of [...]

Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe

Dominik Paprotny, Heidi Kreibich, Oswaldo Morales-Nápoles, Attilio Castellarin, Francesca Carisi3, Kai Schröter

Published: 2020-07-06
Subjects: Earth Sciences, Hydrology, Multivariate Analysis, Physical Sciences and Mathematics, Statistics and Probability

Commercial assets comprise buildings, machinery and equipment, which are susceptible to floods. Existing damage models and exposure estimation methods for this sector have limited transferability between flood events. In this study we introduce two methodologies aiming at broader applicability: (1) disaggregation of economic statistics to obtain detailed building-level estimates of replacement [...]

Seasonal impact-based mapping of compound hazards

John Hillier, Richard Dixon

Published: 2020-06-17
Subjects: Applied Mathematics, Atmospheric Sciences, Climate, Earth Sciences, Environmental Sciences, Hydrology, Mathematics, Multivariate Analysis, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistics and Probability

Impact-based, seasonal mapping of compound hazards is proposed. It is pragmatic, identifies phenomena to drive the research agenda, produces outputs relevant to stakeholders, and could be applied to many hazards globally. Illustratively, flooding and wind damage can co-occur, worsening their joint impact, yet where wet and windy seasons combine has not yet been systematically mapped. Here, [...]

Comparison of permeability predictions on cemented sandstones with physics-based and machine learning approaches

Frank Male, Jerry L. Jensen, Larry W. Lake

Published: 2020-02-06
Subjects: Chemical Engineering, Earth Sciences, Engineering, Hydrology, Multivariate Analysis, Petroleum Engineering, Physical Sciences and Mathematics, Statistics and Probability

Permeability prediction has been an important problem since the time of Darcy. Most approaches to solve this problem have used either idealized physical models or empirical relations. In recent years, machine learning (ML) has led to more accurate and robust, but less interpretable empirical models. Using 211 core samples collected from 12 wells in the Garn Sandstone from the North Sea, this [...]

Advanced ML and AI Approaches for Proxy-based Optimization of CO2-Enhanced Oil Recovery in Heterogeneous Clastic Reservoirs

Watheq J. Al-Mudhafar, Dandina N Rao, Sanjay Srinivasan

Published: 2019-12-05
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Design of Experiments and Sample Surveys, Earth Sciences, Multivariate Analysis, Other Earth Sciences, Physical Sciences and Mathematics, Programming Languages and Compilers, Statistics and Probability

The EOS-compositional reservoir simulation, Design of Experiments, and Proxy Modeling were integrated to obtain the optimal future performance scenario and to construct the most accurate simplified model alternative to the complex reservoir flow simulation. This integrated workflow was adopted on a sector of the main pay/upper sandstone member in the South Rumaila oil field, located in Iraq. [...]

Statistics and segmentation: Using Big Data to assess Cascades Arc compositional variability

Bradley W Pitcher, Adam J.R. Kent

Published: 2018-09-25
Subjects: Applied Mathematics, Applied Statistics, Earth Sciences, Geochemistry, Geology, Multivariate Analysis, Physical Sciences and Mathematics, Statistics and Probability, Volcanology

Primitive lavas erupted in the Cascades arc of western North America demonstrate significant patterns of along-arc heterogeneity. Such compositional diversity may be the result of differences in mantle melting processes, subduction geometry, regional tectonics, or compositions of the slab, mantle or overlying lithosphere. Previous authors have partitioned the arc into four geochemically distinct [...]

Higher potential compound flood risk in Northern Europe under anthropogenic climate change

Emanuele Bevacqua, Douglas Maraun, Michalis I. Vousdoukas, Evangelos Voukouvalas, Mathieu Vrac, Lorenzo Mentaschi, Martin Widmann

Published: 2018-07-18
Subjects: Applied Mathematics, Atmospheric Sciences, Climate, Earth Sciences, Environmental Sciences, Hydrology, Multivariate Analysis, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Other Oceanography and Atmospheric Sciences and Meteorology, Other Physical Sciences and Mathematics, Physical Sciences and Mathematics, Physics, Statistics and Probability

The published version of this article is available at https://advances.sciencemag.org/content/5/9/eaaw5531. Compound flooding (CF) is an extreme event taking place in low-lying coastal areas as a result of co-occurring high sea level and large amounts of runoff, caused by precipitation. The impact from the two hazards occurring individually can be significantly lower than the result of their [...]

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