Detection of organic-rich oil shales of the green river formation, Utah, with ground-based imaging spectroscopy

R. Greenberger, B. Ehlmann, P. Jewell, L. Birgenheier, R. Green
{"title":"Detection of organic-rich oil shales of the green river formation, Utah, with ground-based imaging spectroscopy","authors":"R. Greenberger, B. Ehlmann, P. Jewell, L. Birgenheier, R. Green","doi":"10.1109/WHISPERS.2016.8071807","DOIUrl":null,"url":null,"abstract":"Oil shales contain abundant immature organic matter and are a potential unconventional petroleum resource. Prior studies have used visible/shortwave infrared imaging spectroscopy to map surface exposures of deposits from satellite and airborne platforms and image cores in the laboratory. Here, we work at an intermediate, outcrop-scale, testing the ability of field-based imaging spectroscopy to identify oil shale strata and characterize the depositional environments that led to enrichment of organic matter in sedimentary rocks within the Green River Formation, Utah, USA. The oil shale layers as well as carbonates, phyllosilicates, gypsum, hydrated silica, and ferric oxides are identified in discrete lithologic units and successfully mapped in the images, showing a transition from siliciclastic to carbonate- and organic-rich rocks consistent with previous stratigraphic studies conducted with geological fieldwork.","PeriodicalId":369281,"journal":{"name":"2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WHISPERS.2016.8071807","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

Oil shales contain abundant immature organic matter and are a potential unconventional petroleum resource. Prior studies have used visible/shortwave infrared imaging spectroscopy to map surface exposures of deposits from satellite and airborne platforms and image cores in the laboratory. Here, we work at an intermediate, outcrop-scale, testing the ability of field-based imaging spectroscopy to identify oil shale strata and characterize the depositional environments that led to enrichment of organic matter in sedimentary rocks within the Green River Formation, Utah, USA. The oil shale layers as well as carbonates, phyllosilicates, gypsum, hydrated silica, and ferric oxides are identified in discrete lithologic units and successfully mapped in the images, showing a transition from siliciclastic to carbonate- and organic-rich rocks consistent with previous stratigraphic studies conducted with geological fieldwork.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于地面成像光谱的犹他州绿河组富有机质油页岩探测
油页岩含有丰富的未成熟有机质,是一种潜在的非常规石油资源。先前的研究使用可见光/短波红外成像光谱来绘制来自卫星和机载平台以及实验室图像核心的沉积物表面暴露图。在这里,我们在中间露头尺度上进行工作,测试基于现场的成像光谱识别油页岩地层的能力,并表征导致美国犹他州绿河组沉积岩中有机质富集的沉积环境。油页岩层以及碳酸盐、层状硅酸盐、石膏、水合二氧化硅和氧化铁在离散的岩性单元中被识别出来,并成功地在图像中绘制出来,显示了从硅屑到碳酸盐和富含有机物的岩石的过渡,这与之前通过地质野外工作进行的地层研究一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Hyperspectral and color-infrared imaging from ultralight aircraft: Potential to recognize tree species in urban environments Mapping land covers of brussels capital region using spatially enhanced hyperspectral images Morpho-spectral objects classification by hyperspectral airborne imagery Land-cover monitoring using time-series hyperspectral data via fractional-order darwinian particle swarm optimization segmentation Nonnegative CP decomposition of multiangle hyperspectral data: A case study on CRISM observations of Martian ICY surface
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1