  To maximize the accuracy of background simulation and event reconstruction,
high-energy neutrino telescopes require detailed knowledge of light propagation
over a large volume of detection medium. If light scattering and absorption
leng ths in the medium are of the same scale as the detector size, this problem
can only be handled numerically. Any inhomogeneity of optical properties in the
medium further complicates the problem, requiring large computational
resources. We present a treatment based on combining ray-tracing Monte Carlo
and neural network techniques which offers a reasonable compromise between
solution accuracy, computer memory and CPU usage.
