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Technical Commission VII (B7)

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CC BY: Attribution 4.0 International. You can find more information here.

Bibliographic data

fullscreen: Technical Commission VII (B7)

Multivolume work

Persistent identifier:
1663813779
Title:
XXII ISPRS Congress 2012
Sub title:
Melbourne, Australia, 25 August-1 September 2012
Year of publication:
2013
Place of publication:
Red Hook, NY
Publisher of the original:
Curran Associates, Inc.
Identifier (digital):
1663813779
Language:
English
Additional Notes:
Kongress-Thema: Imaging a sustainable future
Corporations:
International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne
International Society for Photogrammetry and Remote Sensing
Adapter:
International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne
International Society for Photogrammetry and Remote Sensing
Founder of work:
International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne
International Society for Photogrammetry and Remote Sensing
Other corporate:
International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne
International Society for Photogrammetry and Remote Sensing
Document type:
Multivolume work

Volume

Persistent identifier:
1663821976
Title:
Technical Commission VII
Scope:
546 Seiten
Year of publication:
2013
Place of publication:
Red Hook, NY
Publisher of the original:
Curran Associates, Inc.
Identifier (digital):
1663821976
Illustration:
Illustrationen, Diagramme
Signature of the source:
ZS 312(39,B7)
Language:
English
Additional Notes:
Erscheinungsdatum des Originals ist ermittelt.
Literaturangaben
Usage licence:
Attribution 4.0 International (CC BY 4.0)
Corporations:
International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne
International Society for Photogrammetry and Remote Sensing
Adapter:
International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne
International Society for Photogrammetry and Remote Sensing
Founder of work:
International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne
International Society for Photogrammetry and Remote Sensing
Other corporate:
International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne
International Society for Photogrammetry and Remote Sensing
Publisher of the digital copy:
Technische Informationsbibliothek Hannover
Place of publication of the digital copy:
Hannover
Year of publication of the original:
2019
Document type:
Volume
Collection:
Earth sciences

Chapter

Title:
[VII/3: INFORMATION EXTRACTION FROM HYPERSPECTRAL DATA]
Document type:
Multivolume work
Structure type:
Chapter

Chapter

Title:
STUDY ON OIL-GAS RESERVOIR DETECTING METHODS USING HYPERSPECTRAL REMOTE SENSING Qingjiu Tian
Document type:
Multivolume work
Structure type:
Chapter

Contents

Table of contents

  • XXII ISPRS Congress 2012
  • Technical Commission VII (B7)
  • Cover
  • Title page
  • TABLE OF CONTENTS
  • International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Volume XXXIX, Part B7, Commission VII - elSSN 2194-9034
  • [VII/1: PHYSICAL MODELLING AND SIGNATURES IN REMOTE SENSING]
  • [VII/2: SAR INTERFEROMETRY]
  • [VII/3: INFORMATION EXTRACTION FROM HYPERSPECTRAL DATA]
  • CLASSIFICATION OF ROOF MATERIALS USING HYPERSPECTRAL DATA C. Chisense
  • SPECTRAL ANALYSIS OF DIFFERENT VEGETATION COVER USING THE HYPERION SENSOR - A CASE STUDY IN THE STATE OF RIO DE JANEIRO - BRAZIL E. M. F. R. de Souza, R. S. Vicens, A. E. P. Rosa, C. B. M. Cruz
  • Robust Metric based Anomaly Detection in Kernel Feature Space Bo Du, Liangpei Zhang, Huang Xin
  • COMPARISOM OF WAVELET-BASED AND HHT-BASED FEATURE EXTRACTION METHODS FOR HYPERSPECTRAL IMAGE CLASSIFICATION X.-M. Huang and P.-H. Hsu
  • ANALYSIS OF CONCRETE REFLECTANCE CHARACTERISTICS USING SPECTROMETER AND VNIR HYPERSPECTRAL CAMERA Jin-Duk Lee, Bon A. Dewitt, Sung-Soon Lee, Kon-Joon Bhang, Jung-Bo Sim
  • EXTRACTING TEMPORAL AND SPATIAL DISTRIBUTIONS INFORMATION ABOUT ALGAL GLOOMS BASED ON MULTITEMPORAL MODIS Lü Chunguang, Tian Qingjiu
  • HYPERSPECTRAL DATA CLASSIFICATION USING FACTOR GRAPHS Aliaksei Makarau, Rupert Müller, Gintautas Palubinskas, and Peter Reinartz
  • ROAD CLASSIFICATION AND CONDITION DETERMINATION USING HYPERSPECTRAL IMAGERY M. Mohammadi
  • ASSESSING THE SIGNIFICANCE OF HYPERION SPECTRAL BANDS IN FOREST CLASSIFICATION G. J. Newnham, D. Lazaridis, N. C. Sims, A. P. Robinson, D. S. Culvenor
  • ANOMALY DETECTION AND COMPARATIVE ANALYSIS OF HYDROTHERMAL ALTERATION MATERIALS TROUGH HYPERSPECTRAL MULTISENSOR DATA IN THE TURRIALBA VOLCANO J. G. Rejas, J. Martinez-Frias, J. Bonatti, R. Martinez and M. Marchamalo
  • STUDY ON OIL-GAS RESERVOIR DETECTING METHODS USING HYPERSPECTRAL REMOTE SENSING Qingjiu Tian
  • MAPPING THE WETLAND VEGETATION COMMUNITIES OF THE AUSTRALIAN GREAT ARTESIAN BASIN SPRINGS USING SAM, MTMF AND SPECTRALLY SEGMENTED PCA HYPERSPECTRAL ANALYSES D. C. White, M. M. Lewis
  • [VII/4: METHODS FOR LAND COVER CLASSIFICATION]
  • [VII/5: METHODS FOR CHANGE DETECTION AND PROCESS MODELLING]
  • [VII/6: REMOTE SENSING DATA FUSION]
  • [VII/7: THEORY AND EXPERIMENTS IN RADAR AND LIDAR]
  • [VII/3, VII/6, III/2, V/3: INTEGRATION OF HYPERSPECTRAL AND LIDAR DATA]
  • [VII/7, III/2, V/1, V/3, ICWG V/I: LOW-COST UAVS (UVSS) AND MOBILE MAPPING SYSTEMS]
  • [VII/7, III/2, V/3: WAVEFORM LIDAR FOR REMOTE SENSING]
  • [ADDITIONAL PAPERS]
  • AUTHOR INDEX
  • Cover

Full text

calcite). It requires careful processing and analysis as diagnostic 
spectral feature of oil and gas hydrocarbons extracted, at 
diagnostic absorption features is weaker at 1720-1750nm. In 
order to effectively detect, we need high performance hyper 
spectral remote sensing instruments. Combing with the 
hydrocarbon alteration minerals (e.g.: kaolinite, illite, etc.) 
hyper spectral extraction models, we can also indirectly identify 
the target filed of land oil and gas reservoirs by using hyper 
spectral remote sensing technology. After hydrocarbons that 
naturally leaked from the undersea oil and gas reservoirs rise 
above the water, it will form a thin film in the sea surface, and 
then gradually spread to a thinner film layer. At present, the 
description of oil film is based on a series of changes of oil film 
in shape and hue, such as strip (Streamer), silver (Silver sheen) 
(Foudan et al., 2003) and so on, but it also need to distinguish 
oil films according to the variation of the spectrum of the film 
to facilitate the hyper spectral remote sensing exploration of oil 
slicks. 
U.S. West Virginia University successfully detected oil and gas 
microleakage of California, Santa Barbara coast, and found 
several oil and gas fields between 1998 and 1999 by delineating 
the distribution of the hydrocarbon leakage of mineral alteration 
on surface through the AVIRIS Airborne Hyperspectral Imager 
with 224 bands (Heather, 2003). U.S. Geosat Committee 
detected the process of hydrocarbon leakage and migration on 
Australia's Northwest Ocean basins in 2001 by utilizing Probe-1 
Hyperspectral Imager with 128 bands, then found several sea 
thin films with the length about 5-30 meters long sea thin films, 
and interpreted the distribution and transport of the oil 
film(Ellis et al, 2001) The GEOSCIENCE Company in 
Australia detected the process of hydrocarbon leakage and 
migration on Australia's Northwest Ocean basins in 2001 by 
utilizing HYMAP airborne hyperspectral remote sensing 
technology with 128 bands, then found several very thin oil 
films distribution areas on sea which were formed by the 
hydrocarbon microleakage of oil and gas undersea, and 
interpreted the distribution and transport of the oil film 
(William et al., 2002). After that, they successfully detected the 
surface hydrocarbon leakage and three undersea hydrocarbon 
microleakage reservoirs at offshore waters of USA California, 
Santa Barbara In 2003 by utilizing HYMAP Airborne 
Hyperspectral Imager with 128 bands which was developed by 
Hyvist Company in Australian, and combining with the 
effective identification and semi-quantitative analysis of 
components of hydrocarbon leakage oil and gas (Horig et al., 
2001). 
This article mainly researched the land and offshore oil and gas 
exploration of Qaidam Basin and the Liaodong Bay marine in 
China by combining with the spectrum of indoor and outdoor 
observation experiments and using of satellite HYPERION 
hyperspectral remote sensing technology. 
2. REMOTE SENSING DETECTION METHOD OF 
QAIDAM BASIN RESERVOIS 
2.1 Study Area and Hyperion Image Description 
SeBei gas filed in the eastern of Qaidam Basin, which located 
in northeastern of Tibetan Plateau, was chosen as study area. 
The Geological condition is Saline Lake, saline soil and salt 
rock. In addition, the district structure is quaternary. The mainly 
lithology is dark grey sandy shale, with a small part of clay 
siltstone and brown carbonaceous mudstone. Most of the 
  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
   
surface is covered with floury soil and salty sand soil. 
Groundwater is shallow, the content of salt easy to dissolve is 
high, much of that is ultra chlorine saline soil, and part salty soil 
(Palmer et al., 1999; Palmer et al., 1994). Accordingly, the 
vegetation in this area is sparse, and has less community 
composition, simple structure and low coverage. It is very 
suitable to explore oil and gas using hyperspectral remote 
sensing images for this area. A sight of Hyperion hyperspectral 
image acquired on August 11, 2005 was selected in the study, 
and its coverage was shown in Figure 1(O Hyperion Image 
Copyright 2005). The image coverage is within the scope in 
favour of developing gas, and the lower image covers most 
SeBei-2 gas field, lower of which is marsh, while the upper 
image is Hump mountain anticline structural belt. Hump 
Mountain and SeBei-1 gas field are respectively located in the 
upper and lower image. Meanwhile, we can identify clearly a 
small amount of cloud and cloud shadows. 
2.2 Spectrum Experiment and Analysis of Petroleum 
Hydrocarbon in Soil 
We measure the reflectance spectrum of soil with different 
content of oil in the lab, and analyses the sensibility to spectral 
response and spectral feature of crude oil in soil. Spectrometric 
instrument is Field Spec ASD field spectrometer produced in 
American spectrum Device Company. Spectral range from 350 
to 2500nm, with a spectral resolution of 3nm(350-1000nm)and 
10nm(1000-2500nm).Putting dry Qaidam soil samples weight 
of 100g into plastic disc with diameter of 10cm and depth of 
2cm, floating with glass bar, and measuring soil spectra without 
oil and water. Pouring the soil whose spectra had been 
measured into glass bottle, taking crude soil at a volume of 
0.5ml into the bottle using injector, putting the cap on the bottle, 
shake hardly until crude oil and soil fully mixing, and then 
putting the soil back the disc and floating, and measure the 
spectra. Determine repeatedly spectra of soil whose volume 
dose are respectively 1ml, 1.5ml, 2ml, 2.5ml, 3ml, 3.5ml, 4ml, 
4.5ml, 5ml, 5.5ml, 6ml, 6.5ml, 7ml, 7.5ml, 8ml, 8.5ml and 9ml . 
Measuring the spectrum of soil with different content of crude 
oil for five times, taking the average to mapping, and then 
comparative analyzing. As shown in Figure 1, with the 
increasing of the content of crude oil in soil, reflectance spectra 
curve present the following features: (1) the reflectance of 
whole spectrum curve is lower and lower; (2) the decrease of 
reflectance value of overall spectrum curve is more and more 
slowly; (3) gradually increased the double absorption peak 
feature occur around 1748nm, the primary peak around 1726nm, 
and the secondary around 1761nm, and their feature are more 
and more obvious; (4) gradually increased the double 
absorption peak feature occur around 2330nm, and their 
absorption depth increased gradually, primary and secondary 
peak feature is not obvious. 
Double absorption peak feature around 1748nm and 2330nm 
diagnosing that whether the soil contains oil hydrocarbons 
(Cloutis et al., 1989; Ellis et al., 2001). As shown in Figure 1, 
the peaks are located at 1670nm and 1748nm, around 1748nm. 
The primary absorption of the valley at 1726nm begins to occur 
when the content of crude oil in soil is up to 1.5ml/100g. As 
COs’ in soil at 2350nm generates the absorption feature that 
wide at left but narrow at night (Foudan et al., 2003), the 
absorption peak composing of three bands at 2330nm, 2348nm 
and 2348nm has already existed before adding crude oil. 
Moreover, with the increasing of the content of crude oil in soil, 
the reflectance values at 2308nm and 2349nm tend to be equal. 
  
  
	        

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