Oil And Gas Abnormal Information Extraction Based On Multispectral Data In Shaanxi Dafosi Area

China’s proven recoverable oil resources is 43%, which has 57% of the remaining recoverable resources to be proven, overall belonging to oil exploration medium maturity stage. But more than 70% mainly distributed in the desert, the Loess Plateau, mountain and other areas,technical requirements and costs get higher because of the larger difficulty of exploration and development. Therefore, remote sensing technology has a great aid to finding oil effectively.Currently, using visible near-infrared bands of TM, ASTER data to extract hydrocarbon micro seepage alteration information technology is relatively mature. As early as in 1976, Goetz proposed shorter infrared wavelengths from 1.6μm to 2.21μm with the ratio between the two spectral reflectance(1.6μm / 2.2μm) can provide the maximum resolution of altered rocks and unaltered rock. Then they gradually formed a series of principal component-based information extraction technology, witch plays an important role in information extraction of altered rock. But the methods of alteration information extraction based on the band ratio and principal component are relatively simple,so this paper extracted hydrocarbon micro-seepage alteration information using these two methods and delineated the oil and gas target, then according to remote sensing images thermal infrared spectral anomalies phenomenon caused by temperature rise on the reservoir formations, this article inverse the temperature using split window algorithm and multi-channel algorithm in the study area, and draw the temperature anomalies areas matched the hydrocarbon target. Afterwards, we analyzed the target sample spectrum curve anomalies(especially the double absorption near 2.2μm and 2.33μm) using USGS spectral library and standard crude oil spectrum and combining a variety of methods to improve hydrocarbon micro-seepage alteration information extraction accuracy.Finally, in this paper, the temperature inversion using ASTER data to take into account if the study area is in high vegetation coverage, then due to the transpiration of vegetation or other reasons, the low temperature phenomenon will appear in vegetation coverage area and cover up the high temperature anomalies caused by the hydrocarbon micro seepage witch is not conducive to the oil and gas target delineation. Querying large amounts of data find that TVDI(Temperature Vegetation Drought Index) can normalize the temperature inversion results, effectively weaken the influence of vegetation, and make TVDI at a better resolution than Ts in vegetation growth area, to better reflect the real situation of bare surface temperature.