The invention discloses a 
Logging big data real time driving based in-service oil casing 
pipe defect automatic determination method. The method includes: determining the minimum wall thickness threshold and the 
maximum depth of an in-service oil casing 
pipe, the depth increment and the circumference increment recorded by a 
logging meter, and wall thickness 
big data of the oil casing 
pipe; performing a value compensation treatment and a 
smoothing treatment on the wall thickness 
big data of the oil casing pipe; determining a defect zone of the oil casing pipe; quantitatively calculating out basic parameters of the defect zone of the oil casing pipe; and determining the qualitative type of a defect of the oil casing pipe through a quantitative 
analysis method. The method can perform 
data treatment and analysis in real time according to the 
logging big data, can effectively detect the defect zone of the oil casing pipe, can quantitatively calculating out the basic parameters of the defect zone of the oil casing pipe so as to achieve accurate positioning of the defect zone, and can accurately determine the qualitative type of the defect of the oil casing pipe through the quantitative 
analysis method. The method is good in real-time performance, is high in accuracy, is high in reliability, is full in information, and is high 
in degree of 
automation.