The spatial distribution of external corrosion defects in buried pipelines is usually described as a Poisson
process, which leads to corrosion defects being randomly distributed along the pipeline. However, in
real operating conditions, the spatial distribution of defects considerably departs from Poisson statistics
due to the aggregation of defects in groups or clusters. In this work, the statistical analysis of real
corrosion data from underground pipelines operating in southern Mexico leads to conclude that the negative
binomial distribution provides a better description for defect counts. The origin of this distribution
from several processes is discussed. The analysed processes are: mixed Gamma-Poisson, compound Poisson
and Roger’s processes. The physical reasons behind them are discussed for the specific case of soil
corrosion.