%0 Journal Article
%T Dynamic Extraction and Method Optimization of T2 Cutoff Values in Super-Deep Reservoirs
%A Shixuan Lin
%J Open Access Library Journal
%V 12
%N 10
%P 1-12
%@ 2333-9721
%D 2025
%I Open Access Library
%R 10.4236/oalib.1114293
%X The accuracy of the T2 cutoff value directly impacts the precision of calculating bound fluid saturation, mobile fluid porosity, and permeability in nuclear magnetic resonance (NMR) measurements. The porous structure of deep tight sandstone reservoirs is complex, characterized by low porosity, low permeability, and strong heterogeneity. As a result, fixed T2 cutoff values are not suitable for these reservoirs. In order to improve the calculation precision of T2 cutoff values in deep tight sandstone reservoirs, this study relies on NMR experimental measurements of deep tight sandstone samples to establish dynamic extraction methods based on classification Gaussian distribution, multi-fractal analysis, and petrogenesis classification. These methods were used to extract the T2 cutoff values in the deep tight sandstone reservoirs located in Baodao Island offshore area. Research results indicate that when there are a sufficient number of diverse test points available for analysis based on multifractal theory parameters and their relationship with nuclear magnetic resonance T2 cutoff values, high precision can be achieved. Additionally, high matching degrees between calculated and experimentally determined T2 cutoff values were observed using classification Gaussian distribution method. Furthermore, the dynamic extraction method based on petrogenesis classification was able to provide targeted block-by-block extraction within the reservoir section. This research provides robust support for dynamic calculation methods related to T2 cut off values and fully meets the requirements for evaluating pore structures within deep tight sandstone reservoirs using nuclear magnetic resonance logging.
%K Nuclear Magnetic Resonance Logging
%K T2 Cutoff Value
%K Multi-Fractal Analysis
%K High Bound Water Saturation
%K Gaussian Function
%K Multi-Parameter Fitting
%K Petrofacies Classification
%U http://www.oalib.com/paper/6874892