Submerged oil is a type of oil spill that remains suspended and drifting in seawater for extended periods. Existing detection methods find it difficult to obtain the essential information of submerged oil over a considerable range, including concentration, type, composition, distribution, and boundary, making it difficult to conduct in-depth studies on its source tracking, tracking, and prediction. To this end, a chain-type multi-node sensor array for detecting submerged oil in marine environments was developed, consisting of alternating main and auxiliary nodes. The main nodes employ a high-sensitivity underwater detection device based on laser-induced time-resolved fluorescence spectroscopy to obtain information such as oil type, concentration, and composition, while the auxiliary nodes utilize low-cost six-electrode conductivity sensors to measure concentration, distribution, and boundary. The six-electrode sensor is composed of six annular electrodes arranged in a specific geometric configuration. By measuring the voltage between multiple pairs of electrodes, local resistivity data are obtained, based on which a regression model relating resistivity to the concentration of submerged oil is constructed. Finally, experimental validation demonstrated that the model exhibits strong generalization capability and high measurement accuracy, with coefficients of determination of 0.95 and 0.96 for the calibration and validation sets, respectively. This study provides a novel chain-type sensor array and concentration calculation method for large-profile, three-dimensional detection of submerged oil at sea, effectively addressing the measurement requirements for the fundamental parameters in such detection.