Statistical methods for assessing downhole casing integrity and predicting casing leaks

A system for predicting downhole casing leaks of hotspots, comprising:

• a memory;
• and
• at least one hardware processor interoperably coupled with the memory and configured to:
• obtain, from corrosion logs generated by an electromagnetic (EM) logging tool, raw EM corrosion data for a hotspot, wherein the raw EM corrosion data includes a metal thickness loss value for the hotspot;
• determine a corrosion parameter based on the raw EM corrosion data, wherein the corrosion parameter includes a corrosion rate that is calculated based on an original thickness value, a remaining thickness value, and a number of years;
• generate a probability distribution curve for the corrosion parameter;
• generate a corrosion severity classification matrix based on the probability distribution curve, wherein the corrosion severity classification matrix includes a plurality of corrosion severity classes and cutoff values for each of the plurality of corrosion severity classes;
• assign the hotspot into one of the plurality of corrosion severity classes based on a comparison of the cutoff values for the plurality of corrosion severity classes in the corrosion severity classification matrix and the corrosion parameter of the hotspot;
• and
• generate a service alert for the hotspot based on the assigned corrosion severity class.