Abstract Accurately determining fracture closure pressure is essential for optimizing hydraulic fracture treatments in gas reservoirs, especially in tight sandstone formations with low permeability. Traditional methods, like the G-function, estimate closure pressure from pressure decline during flowback, but they often rely on simplifying assumptions that can lead to inaccurate results, given the complex nature of fracture propagation and closure. In this study, we introduce a cutting-edge approach using wavelet transform analysis for signal processing. This technique allows for a more precise interpretation of fracture data, enabling the accurate identification of closure moments and pressures, ultimately improving the reliability of fracture treatment designs. Mini-frac data from the X field in northern Oman, located at depths of 4000 to 5000 meters, were analyzed using wavelet transform techniques. Daubechies wavelets were selected for their effectiveness in representing complex functions, allowing for a detailed decomposition of pressure signals. The methodology developed includes energy distribution plots, using discrete wavelet coefficients to decompose pressure signals into high-pass and low-pass components. By decomposing pressure falloff signals into multiple levels with different frequencies, the energy distribution within the signal was analyzed to identify fracture closure pressure and other significant points in the fracturing process. Comparative analysis with G-function results was performed to validate the proposed approach. The wavelet transform analysis accurately determined fracture closure pressure without making specific assumptions about fracture geometry or well type. This is because of their ability to handle non-stationary signals, such as pressure signals. The analysis initially utilized three mini-frac cases, showing a lower difference with the G-function results. This difference may arise because, in our approach, the closure point represents the full closure of the fracture, whereas in the G-function method, it means the beginning of the closing process. To further validate the proposed approach, A comparative analysis of the results obtained from G-function and wavelet analyses reveals striking similarities in capturing closure events, demonstrating the robustness and reliability of wavelet analysis in diverse geological settings. This close match validates the reliability and efficiency of the proposed approach. This novel approach offers a non-assumptive method for fracture closure pressure determination, eliminating the need for assumptions about fracture geometry or well type. Its effectiveness is validated through comparative analysis with conventional methods, providing a promising tool for tight gas sandstone reservoirs, such as those in Northern Oman.