1) The static formation temperature (SFT) is required to determine the thermophysical properties and production parameters in geothermal and oil reservoirs. 2) A mathematical method to predict SFT based on a new function describing the relationship between bottom hole temperature (BHT) and shut-in time was proposed in this paper. The unknown coefficients of the function were then derived from least squares fit by Particle Swarm Optimization (PSO) algorithm. Besides, the ability to predict SFT based on very few BHT data (such as first 3, 4, or 5 ones of a data set) was also evaluated. 3) The accuracy of the proposed method to predict SFT was testified with a deviation percentage less thaną4%. High value of regression coefficient R^2 ( more than 0.98) represents the strong fitting ability of this method. The value of SFT estimate based on very few BHT data was close to the reported SFT. 4) The new method not only can estimate SFT satisfactorily from all BHT data in a set, but also can estimate SFT based on very few BHT data, both of which indicates that this method could be used as a practical tool in geothermal and oil wells.

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