Remote sensing techniques for hydrocarbon Micro-Seepage detection in Raman mountain, Turkey


Çetin M., Aydinli H. O., Pashaei M. H., Guler U., Cakir M. D., Aydemir H. S., ...Daha Fazla

ENVIRONMENTAL EARTH SCIENCES, cilt.84, sa.8, 2025 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 84 Sayı: 8
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1007/s12665-025-12239-8
  • Dergi Adı: ENVIRONMENTAL EARTH SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, PASCAL, Aerospace Database, Agricultural & Environmental Science Database, Applied Science & Technology Source, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Compendex, Computer & Applied Sciences, Environment Index, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

Satellite images are valuable resources for detecting surface manifestations of hydrocarbon-induced soils and sediments in potential petroleum reservoirs, particularly in inaccessible areas where field surveys are challenging. This study employed band ratio (BR) and principal component analysis (PCA) techniques to investigate hydrocarbon micro-seepage in low API mature oil fields in Raman Mountain, T & uuml;rkiye, using Landsat-8 multi-spectral data. The BR and PCA analyses revealed clay and ferrous iron-rich areas within the study boundaries. The results showed that 329 out of 657 existing wells (52%) correlated with hydrocarbon presence, confirming the effectiveness of remote sensing techniques in oil and gas exploration. The study demonstrated that micro-seepage detection in heavy hydrocarbon areas with low permeability is feasible, challenging previous research that primarily focused on light hydrocarbons. Raman Mountain's heavy oil characteristics include low API gravity values between 7 and 12 and low permeability, complicating direct detection. The study applied band ratios to ferrous iron, clay minerals, and their combinations, using the Crosta Technique to delineate mineral alteration mapping. The eigenvalues and eigenvectors were determined based on existing literature. Overlays of BR and PCA maps with hydrocarbon well locations indicated significant correlations, with a precision score of 52.47%. This suggests that surface anomalies related to hydrocarbon micro-seepage can be reliably identified using Landsat-8 multi-spectral data. These findings support the theory that hydrocarbon micro-seepages are linked to chemical and mineralogical changes in rocks and soils. The results emphasize the importance of integrating RS techniques into hydrocarbon exploration strategies, providing a cost-effective and time-saving approach for detecting subsurface hydrocarbon reserves. Future research should further explore the role of fault systems and structural traps in hydrocarbon migration to refine detection methodologies.