Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2021WR029622 |
Probabilistic Reconstruction of Hydrofacies with Support Vector Machines | |
Nutchapol Dendumrongsup; Daniel M. Tartakovsky | |
2021-04-23 | |
发表期刊 | Water Resources Research
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出版年 | 2021 |
英文摘要 | Delineation of geological features from limited hard and/or soft data is crucial to predicting subsurface phenomena. Ubiquitous sparsity of available data implies that the reliability of any delineation effort is inherently uncertain. We present probabilistic support vector machines (pSVM) as a viable method for both hydrofacies delineation from sparse data and quantification of the corresponding predictive uncertainty. Our numerical experiments with synthetic data demonstrate an agreement between the probability of a pixel classifier predicted with pSVM and indicator Kriging. While the latter requires manual inference of a variogram (two‐point correlation function) from spatial observations, pSVM are highly automated and less data intensive. We also investigate the robustness of pSVM with respect to its hyper‐parameters and the number of measurements. Having investigated these features of pSVM, we deploy it to delineate, from lithological data collected in a number of wells, the spatial extent of an aquitard separating two aquifers in Southern California. This article is protected by copyright. All rights reserved. |
领域 | 资源环境 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/324027 |
专题 | 资源环境科学 |
推荐引用方式 GB/T 7714 | Nutchapol Dendumrongsup,Daniel M. Tartakovsky. Probabilistic Reconstruction of Hydrofacies with Support Vector Machines[J]. Water Resources Research,2021. |
APA | Nutchapol Dendumrongsup,&Daniel M. Tartakovsky.(2021).Probabilistic Reconstruction of Hydrofacies with Support Vector Machines.Water Resources Research. |
MLA | Nutchapol Dendumrongsup,et al."Probabilistic Reconstruction of Hydrofacies with Support Vector Machines".Water Resources Research (2021). |
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