relation: https://khub.utp.edu.my/scholars/3817/
title: Seepage detection on hydrocarbon using hyperspectral remote sensing analysis
creator: Jamaludin, M.I.
creator: Matori, Abd.N.
creator: Mokhtar, M.R.M.
description: Phenomena of macro and micro seeps mostly referred to the signs of hydrocarbon anomaly existence at the surface of the earth and the water either through the soils vegetation or sea. This scenario contributes to the major global problems such as oil spills and pipe leaks, polluting soils, air, vegetation and water. Nevertheless in total, 85 of oil and gas reservoirs have the phenomena of oil seepage leakage throughout the surface. Nowadays current petroleum exploration used geological surveys and seismological methods for detecting possibilities and revealing the petroleum deposits from the geology underneath. As the above methods mention, it is clearly time consuming, costly, involving many parties and surely harmful to the environment. The revolution of satellite remote sensing with hyper spectral sensor consists of contagious bands offers a non-destructive investigation method and has a significant added value rather than the typical oil and gas exploration and acquisition. As reported in Forestry Statistics, for the year 2011, almost 84.51 of Malaysia is covered by primary and secondary forest, mangrove, plantation and etc. It means the best medium to detect hydrocarbon is through the stress of vegetation. Therefore, this paper focuses the outline of research concern about the detection of seepage hydrocarbon influence on vegetation and the preliminary result of FLAASH. The Hyperion EO-1 sensor has been chosen as it comprises the most required band for the analysis and the availability of study area scene, Miri, Malaysia in the USGS archive. Spectral library of vegetation stressed of the study area is to be developed in the form of lab scale simulation. It is expected that a relatively new method in identifying hydrocarbon seepage through hyper spectral remote sensing analysis will be discovered. Copyright © (2013) by the Asian Association on Remote Sensing.
publisher: Asian Association on Remote Sensing
date: 2013
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Jamaludin, M.I. and Matori, Abd.N. and Mokhtar, M.R.M.  (2013) Seepage detection on hydrocarbon using hyperspectral remote sensing analysis.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903445521&partnerID=40&md5=d2d17e0afeb803f7f62931cdc40b7469