Measurements of longitudinal relaxation time (T₁), transverse relaxation time (T₂), self-diffusion coefficient (D₀),T₂-T₁ and T₂-D₀ are central in NMR-based oil logging. The SGSE sequence is commonly used to measure D₀, in which the interval time between the 90° and 180° pulses (T_d) is increased incrementally to probe into the diffusion behaviors of liquids. However, the starting point, step size and end point of T_d must be properly set in order to get accurate measurement of T₁ and D₀. Currently, tuning of such parameters is often done manually, and thus time-consuming and difficult to use. The final outcome also relies heavily on operator's experience. In this study, a large number of random simulations were carried out by a Monte Carlo algorithm. The algorithm predicted the parameters for next measurement based on the results from previous measurements and thus was capable of updating the parameter settings in real time for automatic measurements. The algorithm was validated for T₁, D₀ measurements, and demonstrated reduced measurement threshold and shortened measurement time.