Integrated environmental monitoring and multivariate data analysis-A case study

Area of Science:

• Environmental Science
• Marine Biology
• Oceanography

Background:

• Offshore oil exploration requires rigorous environmental monitoring.
• Understanding the impact of drilling discharges on marine ecosystems is crucial.

Purpose of the Study:

• To integrate environmental monitoring and discharge data for impact assessment.
• To interpret data using multivariate statistics, including principal component analysis (PCA) and partial least squares (PLS) regression.
• To evaluate the relationship between offshore drilling activities and marine sediment characteristics.

Main Methods:

• Conducted environmental monitoring at the Peregrino oil field, Brazil, using sensor platforms and sediment traps.
• Measured physical parameters (currents, turbidity, temperature, conductivity) and analyzed sediment chemistry (alkanes, PAHs, N, C, CaCO3, Ba).
• Integrated monitoring data with daily discharge records of drill cuttings and drilling fluid, applying multivariate statistical analyses.

Main Results:

• No systematic differences in sediment composition were observed across monitoring campaigns or locations.
• Strong covariation between suspended particulate matter and organic carbon/nitrogen suggested natural, biogenic origins.
• Multivariate regression revealed no correlation between drill cuttings discharge and sediment trap or turbidity data, even when accounting for current dynamics.

Conclusions:

• Drilling discharges from the Peregrino oil field showed no detectable impact on the monitored marine environment.
• Sediment characteristics were primarily influenced by natural and biogenic processes.
• Combined statistical analysis and chemical indicators confirmed the lack of correlation with drilling activities.