Rapid Source Attribution of Illegal Crude Oil Dumping Using GC–FID Fingerprinting and Multivariate Analysis in the Rokan Field

Abstract

Illegal crude oil dumping constitutes a significant environmental offense that threatens ecosystem integrity and necessitates reliable forensic methodologies for accurate source attribution. This study proposes a rapid, practical, and cost-effective forensic framework that integrates routine gas chromatography–flame ionization detection (GC–FID) fingerprinting with multivariate statistical analysis using MALCOM software. The developed approach is intended to provide a scientifically defensible method for source correlation in operational oil fields, where timely identification of contamination sources is critically important. Soil and water samples were collected from two suspected dumping sites, designated Spot A and Mud Pit B, and compared with crude oil samples obtained from three reference wells: Wells 3D, 4D, and 1E. Source attribution was evaluated through comparative chromatographic fingerprint analysis, diagnostic biomarker ratios (Pr/Ph, Pr/n-C17, and Ph/n-C18), hierarchical clustering via dendrogram analysis, and cosine similarity to quantify chemical relationships among samples. The results revealed that the soil sample from Spot A exhibited an exceptionally high cosine similarity value (>0.999) and clustered closely with crude oil from Wells 3D and 4D, strongly indicating a common origin and supporting evidence of illegal discharge from these sources. In contrast, samples from Mud Pit B displayed distinct chromatographic characteristics and lower similarity values (<0.997), suggesting a different source and/or significant weathering. These findings demonstrate that integrating widely accessible GC–FID data with multivariate statistical tools offers a rapid, robust, and economically feasible approach for environmental forensic investigations and source attribution of illegal crude oil dumping incidents.