Application of Spot 5 Satellite image to Oil-contaminated soils Identification and statistical analyzes in Marun Oilfield – Khuzestan

Introduction

In recent years, using remote sensing technology and variety of satellite images as one of the main sources of information have evaluated to monitor the optimal utilization of resources, soil pollution, water pollution and land. Remote sensing application technology (satellite image data) in different domains has led to its application in areas such as oil and gas. The soil pollution is a form of pollution due to human activity in which huge amount of crude oil is leak aged or released into the field and soil. The recovery and cleaning process is very difficult and take more times. Some oil spills may take even years to clean up. This process depends upon various factors such as the type of oil spilled, soil and environmental factors. Several oil spills occurred at oil platforms in Marun oil field, Ahvaz. The oil spills were subsequently imaged by different types of satellite sensors, The object of paper is identify oil pollution in soil using satellite imagery for identify oil pollution in soils and find source of pollution in the Marun oil filed Khuzastan, south of Iran.

Material and methods

The study area is an oil field, located in the Khuzestan province of Iran and is the second-largest oil field in Iran. Marun oil field is situated in the southwest of Iran in the south of North Dezful Embayment between Kupal, Aghajari, Ramin, Shadegan and Ramshir oil fields. This field consists of Asmari and Bangestan reservoirs producing oil and Khami reservoir comprising mainly gas. This field is an asymmetric anticline with NW-SE trend. The dimensions of Marun oil field at the Asmari oil reservoir horizon are 67 and 7 kilometers in length and width, respectively. The GPS data were collected in the WGS-84 (World Geodatic Systems-84) datum in the latitude/longitude system and were subsequently transformed into the Universal Transverse Mercator (UTM) Zone 39-North system. The GCP coordinates within the UTM projection were then integrated with the satellite images using the software for georeferencing. The satellite images were enhanced using an image processing software package (Envi 5.0) to facilitate the pre-processing and processing of the study area. High precision, were used to capture data at several identifiable points on the images to be used as ground control points (GCPs).

Results & Discussion

This paper aims to identify oil pollution in soil using SPOT5 satellite imagery. In this study, SPOT5 satellite images are used with supervised classification methods that created two color threshold, Low to High of petroleum products in the study area. In the study area the high threshold have the most pollution. Grounds point control are used for accuracy and validation of results, five point with certain color threshold, for identification polluted soils. In the study area, results of statistical analysis show that metal concentrations Ni and Co elements compared with World Shale Standard are contaminated with high amount and average concentrations of all three metals Ni, Co and V compared with non-contaminated soil standard are also polluted with high range. Soil salinity factor in the study area is plotted at saline range according of saline soils classification. According to statistical results, high correlation between pH, Oil / Grease, V and EC are showed that Vanadium is characteristic of oil pollution ,also the salinity and pollution oil / grease in soil due to crude oil been created. The correlation between Ni and Co elements, indicates that the source of them are same and due to the geological factors. Principal component analysis show that first factor is most effective factor in the contamination of soil which has a high correlation with pH, Oil / Grease, V and the EC which can dominated the same source of these parameters with crude oil. The second factor is shown high correlation between Co and Ni have same source that due to material of soil in the study area.