During the production and transportation of crude oil, a large amount of sludge is inevitably produced, which is loaded with high concentrations of toxic, teratogenic, and carcinogenic substances that can significantly damage the ecosystem. Laser-induced fluorescence (LIF) technology is currently one of the most effective methods for detecting oil spills. Soil is a common natural porous medium that allows oil droplets to enter its pores when mixed with it. This unique structure causes multiple reflection and absorption of light, leading to differences in the fluorescence distribution obtained by LIF for the detection of soil petroleum contaminants. Recent studies have shown that LIF technology can effectively detect soil petroleum contaminants. However, studies regarding the microscopic analysis of photon transmission in oily soils are limited. Based on the optical transmission theory, building a fluorescence simulation model of oily soil and analyzing its fluorescence distribution can provide theoretical support for the LIF detection of soil petroleum contaminants. Therefore, this study uses the Monte Carlo method combined with the implicit function representation of porous media to build a fluorescence simulation model of soil petroleum contaminants to simulate the transmission process of laser and fluorescence photons in soil petroleum contaminants, and to analyze the impact of the detection and soil parameters on the fluorescence signal.

Based on the varying amounts and distribution characteristics of the soil oil content, we classify soil petroleum contaminants into oil sludge and oil-containing soil. A simulation model is established for soil petroleum contaminants using the Monte Carlo method in conjunction with a representation of the implicit function of porous media. In this model, the soil particles are viewed as a framework of porous media with petroleum hydrocarbon pollutants filling the pores. To track the exact path of photons (laser and fluorescence) within the soil petroleum contaminants, the position of the photons is first determined in the soil petroleum contaminants based on the implicit function values, followed by determining the phenomena occurring on the surface of the soil particles. During the simulation, photons enter the medium with the initial information (including position, direction, and weight), and the motion process is accompanied by changes in the photon weight. When the photon weight is too small or radiates out of the calculated area, the next photon is emitted. This process is repeated until all photons are emitted, after which the information regarding the fluorescent photon emission is collected. By simulating the fluorescence conversion efficiency of the oil sludge and oil-containing soil polluted by the different types of oil under various incident zenith angles, porosities, and pores per inch, we analyze the influence of the different oils, LIF system parameters, and soil factors on the fluorescence distribution.

The simulation results indicate that for the same type of oil pollution, the oil sludge generates a stronger fluorescence signal than oil-containing soil owing to the higher oil content of the sludge (Fig. 4). The fluorescence intensity of the soil petroleum contaminants increases as the porosity increases. When the soil contaminated with light oil is irradiated with a laser, the resulting fluorescence signal is weaker than that of the soil contaminated with heavy oil owing to the lower oil absorption coefficient (Fig. 5). The incident angle of the laser also affects the power of the LIF light received. Overall, the energy received by the receiver is mainly concentrated in the direction of incidence. When the laser is vertically incident, the fluorescence signal collected by the LIF system is the strongest, whereas an increase in the incident angle causes the fluorescence signal to gradually decrease (Fig. 6). The number of pores per inch of the medium is closely related to the average pore size, which affects the emission of the fluorescent photons. The results demonstrate that the fluorescence signal decreases as the number of pores per inch increases because when the pores per inch is low, the average pore size is larger, allowing more fluorescence photons to be emitted through the pores (Fig. 8).

Based on the Monte Carlo method and implicit function representation of the porous media, a fluorescence simulation model of the soil petroleum contaminants is established. By simulating the transmission of photons in the soil petroleum contaminants, the relationship between the fluorescence signal based on the LIF reception and various parameters is obtained. First, the fluorescence conversion efficiencies of the oil sludge and oil-containing soil under the same oil pollution are simulated. The oil content of the soil petroleum contaminants is found to have a certain impact on the fluorescence signal. Subsequently, the numerical values of the fluorescence conversion efficiency of the oil sludge and oil-containing soil polluted with different oils at various porosity rates are simulated. A comparison of the results indicates that both the porosity of the soil petroleum contaminants and absorption coefficient of the oil affect the fluorescence signal. The signal intensity increases as the porosity increases, and the fluorescence signal of the light oil is weaker than that of the heavy oil. Subsequently, the effect of the pores per inch of the soil petroleum contaminants on the fluorescence signal is investigated, and the fluorescence signal is found to decrease as the number of pores per inch increases. Finally, the fluorescence conversion efficiency values of the oil sludge at different incident angles are compared, revealing that the intensity of the fluorescence signal received by the system gradually decreases as the laser incidence angle increases. Therefore, the laser incidence angle should not be excessively large when detecting soil petroleum contaminants. This study presents the optimal range of the detection angle for the LIF detection system as well as the effects of the oil content, structural parameters, and types of oil in the soil petroleum contaminants on the fluorescence signal, providing theoretical support for the LIF detection of terrestrial oil spill pollution.