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.