  Magnetic flux leakage measurements help identify the position, size and shape
of corrosion-related defects in steel casings used to protect boreholes drilled
into oil and gas reservoirs. Images constructed from magnetic flux leakage data
contain patterns related to noise inherent in the method. We investigate the
patterns and their scaling properties for the case of delta-correlated input
noise, and consider the implications for the method's ability to resolve
defects. The analytical evaluation of the noise-produced patterns is made
possible by model reduction facilitated by large-scale approximation. With
appropriate modification, the approach can be employed to analyze
noise-produced patterns in other situations where the data of interest are not
measured directly, but are related to the measured data by a complex linear
transform involving integrations with respect to spatial coordinates.
