Carbonate contents are closely ralated to oil and gas exploration,especially for unconventional oil and gas exploration in hydraulic fracturing. Obtaining carbonate content mainly relies on laboratory experiments, which take a long time and money. In addition, it is complicated to select enough samples for systematic research. This paper focuses on the analysis and comparison of well-logs data and carbonate content in seven wells in Dongying Depression with SPSS. We found a good relative relationship, demonstrating high-Pearson data, between well-logs and carbonate contents-R25,AC,GR and CNL, meanwhile, we develop a regression line between well-logs and carbonate contents, and measured well log data calculated the carbonate content. Subsequently, the measured data is used to check the calculated carbohydrate content and to screen out better log groups to illustrate a better match. We recognized better groups like AC&CNL and R25&CNL, and multiple-log groups like AC&R25&CNL ,R25&GR&CNL and AC&R25&GR&CNL, especially the AC&R25&CNL which was selected to calculate carbonate contents in the end. It is convenient and inexpensive to calculate carbonate contents of diverse wells using this model.