Method for analyzing cement integrity in casing strings using machine learning

A system for analyzing cement integrity in a cased wellbore traversing a formation, wherein the cased wellbore includes a multiple string casing with an innermost annulus disposed inside at least one outer annulus, the system comprising:

• a sonic tool configured to generate waveforms that travel into the casing of the cased wellbore and configured to record the waveforms to obtain sonic data;
• an ultrasonic sonic tool configured to generate waveforms that travel into the casing of the cased wellbore and configured to record the waveforms to obtain ultrasonic data;
• and
• a processing system configured to:
• (i) process ultrasonic data obtained from ultrasonic measurements on the depth interval of the wellbore to determine properties of the innermost annulus;
• (ii) process sonic data obtained from sonic measurements on the depth interval of the wellbore to extract features of the sonic data;
• (iii) determine properties of the innermost annulus located between an innermost casing and a surrounding casing and the least one outer annulus using machine learning processing, wherein the properties of the innermost annulus and the least one outer annulus include at least one property characterizing state of material in the innermost annulus and at least one property characterizing state of material in the at least one outer annulus, and wherein the features of the sonic data from process (ii) are inputs to the machine learning processing;
• (iv) analyze the cement integrity based on the determined properties.