This is -exactly- the problem that kriging was designed for. You have easily enough data to estimate the variogram, and you likely have a polynomial trend surface; so, universal kriging would be appropriate to the problem.
The issue is the processing time for universal kriging. One very simple way to deal with this problem rather than any statistical interpolation method is to just use the deterministic interpolation built into the terrain dataset in arcgis.
Create an x,y,z point dataset, where the z value is your Coil Response mV. Load this in as the mass points in your terrain dataset and simply load the set into a map document ArcMap will take care of the on the fly IDW to visualize the dataset at different map scales.
Also, you might want to check out this video series:
The 2nd video in the series discusses how to choose the correct neighborhood radius for IDW using Moran's I.