DOI: 10.1306/04061009175
Scopus记录号: 2-s2.0-78149369474
论文题名: Mapping facies distributions on modern carbonate platforms through integration of multispectral Landsat data, statistics-based unsupervised classifications, and surface sediment data
作者: Kaczmarek S.E. ; Hicks M.K. ; Fullmer S.M. ; Steffen K.L. ; Bachtel S.L.
刊名: AAPG Bulletin
ISSN: 0149-1902
EISSN: 1558-9632
出版年: 2010
发表日期: 2010
卷: 94, 期: 10 起始页码: 1581
结束页码: 1606
语种: 英语
Scopus关键词: Bahamas
; Benthic sediments
; Carbonate platforms
; Carbonate reservoir
; Carbonate sediments
; Classification results
; Conventional mapping
; Facies belt
; Facies distribution
; Global data
; Hydrocarbon exploration
; Image analysis algorithms
; Indian ocean
; LANDSAT
; LandSat 7
; Me-xico
; Multi-spectral
; Multispectral satellite data
; Occurrence and distribution
; Persian Gulf
; Predictive relationships
; Spatial dimension
; Spatial variability
; Statistical algorithm
; Surface sediments
; Time-efficient methods
; Unsupervised classification
; Carbonation
; Hydrocarbons
; Mapping
; Petroleum prospecting
; Sedimentology
; Sediments
; algorithm
; carbonate platform
; data set
; depositional environment
; facies
; geological mapping
; hydrocarbon exploration
; image analysis
; image classification
; Landsat
; marine sediment
; satellite data
; spatial variation
; unsupervised classification
; Arabian Sea
; Atlantic Ocean
; Bahamas
; Belize [Central America]
; Caicos Platform
; Caribbean Sea
; Cocos (Keeling) Islands
; Glovers Reef
; Indian Ocean
; Mesoamerican Barrier Reef
; Mexico [North America]
; Persian Gulf
Scopus学科分类: Energy
; Earth and Planetary Sciences
英文摘要: Benthic sediment facies maps were constructed for a series of large, isolated carbonate platforms, including (1) Great and Little Bahamas Banks; (2) Caicos Platform, British West Indies; (3) Chinchorro Bank, Mexico; (4) Glovers Reef, Belize; (5) south Cocos (Keeling) atoll, Indian Ocean; and (6) Bu Tini shoal, Persian Gulf. Facies maps were generated by applying statisticsbased image analysis algorithms, called unsupervised classifications, to Landsat 7 multispectral satellite data. Classification results were subsequently validated with sediment data to create geologic fades maps. Landsat-derived facies maps demonstrate 82-85% agreement when compared to sediment data. At the platform scale, Landsat-derived facies maps accurately capture the principal depositional facies observed on each platform and are in general agreement with published maps generated through conventional mapping techniques. Examination at more detailed scales reveals that Landsat-derived maps differ from conventional maps with respect to the spatial dimensions and shapes of facies bodies. Landsat-derived maps show a level of complexity and heterogeneity that is more realistic than shown in previously published maps, which are characterized by broad, homogeneous facies belts. These results suggest that application of statistical algorithms to Landsat data, coupled with sediment data, provides a cost- and time-efficient method for quantitatively mapping spatial variability of depositional facies in modern carbonate environments. Landsat-derived facies maps, like the ones presented here, provide depositional analogs for subsurface carbonate reservoirs as well as a global data set for extracting predictive relationships between the occurrence and distribution of carbonate sediments that can aid in global hydrocarbon exploration and production. Copyright © 2010. The American Association of Petroleum Geologists. All rights reserved. URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-78149369474&doi=10.1306%2f04061009175&partnerID=40&md5=1811b1da814e92650410e94ff49cf98c
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/13471
Appears in Collections: 过去全球变化的重建 影响、适应和脆弱性 科学计划与规划 气候变化与战略 全球变化的国际研究计划 气候减缓与适应 气候变化事实与影响
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Recommended Citation:
Kaczmarek S.E.,Hicks M.K.,Fullmer S.M.,et al. Mapping facies distributions on modern carbonate platforms through integration of multispectral Landsat data, statistics-based unsupervised classifications, and surface sediment data[J]. AAPG Bulletin,2010-01-01,94(10)