Extraction Of Hydrocarbon Microseepage Information From Multi-source Remote Sensing Images

Hydrocarbon microseepage above oil and gas reservoirs is a common phenomenon,which results in special anomalies on the earth surface.These anomalies may be identified by remote sensing technology,which is helpful for oil and gas exploration.Landsat image or ASTER image are currently most used data for the extraction of information related to hydrocarbon microseepage for oil and gas exploration.Due to the different spectral information and spatial resolution of different images,the extracted information related to hydrocarbon microseepage from a certain single image is limited,while the integration of multi-source images can give full play to the advantages of different images,make it possible to extract hydrocarbon microseepage information more accurately.However,there are few studies in this field,in particular,the study of using Sentinel-2 MSI data to extract hydrocarbon microseepage information.To deal with this issue,the fuzzy fusion method was used in this thesis to extract the information related to hydrocarbon microseepage by using Landsat OLI image,ASTER image and Sentinel-2 MSI image with the expectation of improvement of the accuracy of the results.The thesis takes Marsel block of Chu-Sarysu Basin in Kazakhstan as a case study.Firstly,geological data and remote sensing images of the study area were collected,including Landsat OLI,ASTER and Sentinel-2 MSI images,followed by their preprocessing,including radiometric calibration,atmospheric correction,geometric correction,image mosaic and cropping,and so on.According to the response mechanism of remote sensing anomalies of hydrocarbon microseepage,the appropriate bands are selected,and principal component analysis(PCA)and band ratio methods were used to extract the alteration mineral anomalies related to hydrocarbon microseepage.Subsequently,the fuzzy fusion method was used to fuse different information,including different information extracted from the same image by different methods,and different information extracted from different images,and the final integrated information extracted from multi-source remote sensing image.Finally,the geological and seismic data of Marsel block were used to validate the result.The results show that,fuzzy set based fusion of information extracted by different methods from same image can give full play to the advantages of each method and improve the accuracy of results.While,the fuzzy fusion of different information related to different altered minerals can integrate anomalies related to various altered minerals and improve the accuracy of hydrocarbon microseepage information extraction from single image.Finally,the fuzzy fusion of multi-source remote sensing images gives full play to the advantages of different remote sensing images,and improves the accuracy and reliability of hydrocarbon microseepage information in the study area.The results can be used to assist oil and gas exploration and verify the results of oil and gas exploration.