Rapid prediction of oil spill transport is crucial for effective emergency response and environmental protection. This work studies oil spill modelling using a Lagrangian particle approach, where oil motion is described by stochastic equations accounting for sea currents and turbulence. Because particle trajectories are independent, the model is naturally parallel and well suited to advanced computing methods. We explore the use of emerging quantum algorithms to accelerate key calculations in oil spill risk assessment. Quantum simulations are implemented using IBM Qiskit and NVIDIA CUDA-Q, and their performance and scalability are evaluated. The results demonstrate the potential of quantum computing techniques for future high-fidelity oil spill modelling, while highlighting the role of quantum simulators as practical tools for algorithm development.