Preview

Devices and Methods of Measurements

Advanced search

Application of Satellite Image Processing Methods for Hydrocarbon Field Search

https://doi.org/10.21122/2220-9506-2019-10-4-373-381

Abstract

The object of the study is software methods of the Earth surface images processing obtained from the VRSS-2 satellite to determine the spectral composition of the vegetation cover to detect the presence of carotenoids during prolonged exposure to hydrocarbons.

The photosynthetic pigments of higher plants (chlorophylls, carotenoids and phytobiliproteins) were analyzed. In the chloroplasts of higher plants, chlorophyll and carotenoids are present in a ratio of about 3:1. The presence of hydrocarbons increases the amount of carotenoids. Carotenoids have absorption bands in the blue-violet region from 400 to 500 nm and a high reflection coefficient in the red-orange and yellow spectral regions, which corresponds to the multispectral MSS operating mode (B2) of the VRSS-2 satellite camera. An analysis of the vegetation growing in the study area of the Puerto Kumarebo settlement showed that the best indicator of the presence of hydrocarbons in the soil is Prosopis juliflora – CUJI with a deep root system of up to 50 m, growing in the study area.

Using ENVI software, a comparative evaluation of the efficiency of photographs image processing was carried out using the normalized relative vegetation index (NDVI) and the structure-insensitive pigment index (SIPI) to detect changes in the color of green vegetation. It has been established that the SIPI index is more applicable for hydrocarbon search tasks. Moreover, the recorded index fluctuations in the area of uniform vegetation at the level of 2.5 % are characteristic of normal growing conditions and cannot serve as evidence of the presence of factors indicating the presence of hydrocarbons in the soil. For a more detailed assessment of the presence of carotenoids in the foliage and the presence of hydrocarbons in the soil, photographs with high optical resolution of objects on the surface are required.

About the Authors

R. V. Fiodоrtsev
Belarusian National Technical University
Belarus

Address for correspondence: R.V. Fiodоrtsev – Belarusian National Technical University, Nezavisimosty Ave., 65, Minsk 220013, Belarus      e-mail: feodrw@gmail.com; dmkz.1408@gmail.com



A. R. Silie Cuenca
Belarusian National Technical University; National Experimental University “Antonio José de Sucre” UNEXPO
Venezuela, Bolivarian Republic of
Nezavisimosty Ave., 65, Minsk 220013, Belarus; 

Corpahuaico avenue, Barquisimeto – Lara, 3001 Venezuela



D. A. Kozhevnikov
Belarusian National Technical University
Belarus
, Nezavisimosty Ave., 65, Minsk 220013


V. M. Medina
National Experimental University “Antonio José de Sucre” UNEXPO
Venezuela, Bolivarian Republic of
Corpahuaico avenue, Barquisimeto – Lara, 3001


R. Delgado
Bolivarian Agency for Space Activities ABAE
Venezuela, Bolivarian Republic of
Francisco Fajardo Avenue, Generalissimo Francisco de Miranda Air Base, La Carlota, Caracas 1064 Venezuela


References

1. Trofimov D.M. Remote sensing: new technologies – new opportunities for oil and gas exploration. Geomatics, 2009, no.1, рр. 17–24.

2. Aerosols of Siberia. Integration projects. Ed. K.P. Kutsenogogo. FSUE Publishing House SB RAS, 2006, iss. 9. – 555 p.

3. Lincoln Taiz, Eduardo Zeider. Plant Physiology. Sinauer Associates, 2002, chapter 7, 690 p. (P. 115). ISBN: 0878938230.

4. Cherepanov A.S., Druzhinina E.G. Spectral properties of vegetation and vegetation indices. Geometry, 2009, no. 3, рр. 28–32.

5. VRSS-2 or Antonio José de Sucre is Venezuela. https://www.n2yo.com/satellite/?s=42954

6. 6. Mountain Encyclopedia / Ch. ed. E.A. Kozlovsky; Ed. col.: M.I. Agoshkov, N.K. Baibakov, A.S. Boldyrev et al. Sov. encyclopedia, Geosystem, 1984, vol. 1, 560 p.

7. 7. Renny Calleja. Cuenca geológica Falcón en Venezuela.Parte2.Monografía.CUENCAPETROLÍFERA DE FALCÓN. UNIVERSIDAD DEL ZULIA, 2002, 28 p. https://rdv-files.nyc3.cdn.digitaloceanspaces.com/pub/pdf/files_pdf/5/8/5/00031585.pdf

8. 8. Al-Wassai F.A., Kalyankar N.V. Image fusion technologies in commercial remote sensing packages. Journal of Global Research in Computer Science, 2013, 4(5), рр. 44–50.

9. Quirós E., Polo M.E. Recursos abiertos de información geográfica para investigación y documentación científica. Revista Española de Documentación Científica, 2018, vol. 4, no. 3, рр. 126– 138. DOI: 10.3989/redc.2018.3.1512

10. Dan Bruton. Approximate RGB values for Visible Wavelengths, 1996. Internet: http://www.physics.sfasu.edu/astro/color/spectra.html

11. Spectral Indexes on Top of NDVI To Make Your Vegetation Analysis Complete. Earth Observing System EOS. 22.02.2019. https://eos.com/blog/6-spectralindexes-on-top-of-ndvi-to-make-your-vegetationanalysis-complete/?utm_source=Email&utm_medium=educationalcontent&utm_campaign=button


Review

For citations:


Fiodоrtsev R.V., Silie Cuenca A.R., Kozhevnikov D.A., Medina V.M., Delgado R. Application of Satellite Image Processing Methods for Hydrocarbon Field Search. Devices and Methods of Measurements. 2019;10(4):373-381. https://doi.org/10.21122/2220-9506-2019-10-4-373-381

Views: 1204


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2220-9506 (Print)
ISSN 2414-0473 (Online)