A new signal processing approach was proposed by M.Y. Soliman, U. Ebru, F. Siddiqi, A. Rezaei, and I. Eltaleb (2019) and 2020 was extended to use the continuous wavelet transform to identify the closure time and pressure. The new method was applied to synthetic and actual field data. The synthetic data were produced using commercially available fracture simulators based on fracture propagation and closure simulation principles with predefined fracture clossure. To determine this closure instant, we decompose the pressure fall-off signal as the output of the fracture system into multiple levels with different frequencies using the continuous wavelet transform. This "short wavy" function is stretched or compressed and placed at many positions along the signal to be analyzed. The wavelet is then multiplied term-by-term by the signal, and each product yields a wavelet coefficient value. The signal energy is observed during the fracture closure process (pressure fall-off) and the fracture closure event is identified when the signal energy stabilizes to a minimum level. This approach not only produce more reliable results. It lends itself more readily analytics applications.