The present invention provides a
carbonate rock thin reservoir
porosity prediction method based on an seismic even and odd functions. The method comprises the following steps of: the step 101, employing a moving time window with
fixed duration to capture short-term seismic signals, and obtaining an even function and an odd function of original signals on a
time domain in the moving time window; the step 102, employing a well-
logging curve standard and well-side seismic data to obtain a real seismic
wavelet to perform
standardization of amplitude spectrums of the odd function and an even function, and calculating peak amplitude attributes of the odd function and the even function; and the step 103, allowing the even function peak amplitude attributes and related
seismic attribute characteristics to commonly form a multi-attribute
data set, and employing multi-attribute analysis to perform fitting of actually measured reservoir
porosity data, to obtain a reservoir
porosity prediction result in a large scale. The method provided by the invention employs a
wavelet standardization method and a method of even function and odd function extraction of seismic data to obtain attributes onlyrelated to the
carbonate rock reservoir porosity, and combines a seismic multi-attribute
analysis method to perform accurate prediction of the reservoir porosity.