forward model to cortical surface using BEM, given pial triangles and SEEG recordings

Hi Community,
Starting on my first forward modelling. The goal is to input SEEG recordings (mostly in cortex, some hippocampus) and .pial files made by freesurfer. As output, I want to use BEM to estimate the signal at the surface of the cortex, and then compare this to actual signals that were simultaneously recorded using surface strips and grids. I don’t need to estimate the sources, only do the forward modeling. My interest is in how the depth/surface distinction modifies the signals and the kind of spatio-temporal dynamics that can be observed, depending on volume conduction effects, contact spacing etc.
Anyone could point me to an existing python script that I can modify, it would be much appreciated. All of my searches so far have found EEG/MEG head models, or been rather exotic.