A New Protocol for Borehole NMR Simulation

Nuclear magnetic resonance (NMR) logging for formation evaluation can be challenged by heterogeneity and mud filtrate invasion, leading to increased modeling errors in complex formations. Understanding the response characteristics of NMR tools at formation interfaces and their influencing factors is critical for accurate evaluation. The response of NMR logging under varying formations and instruments parameters remains unclear. This study calculates the NMR porosity decay using the Bloch equations and incorporating the spatial sensitivity distribution of the instruments.First, the formation and borehole models were established, considering factors such as formation thickness, different formation types, mud properties, and invasion depth. The NMR measurement model was established, consisting of a permanent magnet generating a static gradient magnetic field(B0) and an RF antenna generating a radio frequency magnetic field(B1). The instrument simulated NMR responses at depths of 50 mm, 60 mm, and 70 mm. The magnetization vector decay was estimated using a recursive method based on Bloch equations. Considering the presence of non-uniform static magnetic fields or applied gradient fields, the magnetization process around the effective magnetic field. An instrument signal sensitivity calculation formula was introduced to compute the sensitivity map of the NMR signal distribution in the borehole. The total response during measurement was the combined signal contribution from different formations within the sensitive area at the time of acquisition.This study simulated the NMR logging response under varying formation conditions, including different layer thicknesses and rock properties, while also analyzing the effects of instrument factors such as motion speed and signal-to-noise ratio (SNR). Model validation shows that the root mean square error (RMSE) of the simulation results remains below 1%. The NMR logging response is influenced by formation thickness, well deviation angle, tool motion speed, and SNR. Excessive motion speed causes incomplete polarization and echo acquisition, leading to T2 spectrum shifts proportional to antenna length. Furthermore, logging speed has a significant impact on the resolution of NMR logging; higher speeds result in reduced signal resolution. Lower SNR further degrades signal clarity, limiting the ability to distinguish pore size components during inversion and causing multiple peaks in the T2 spectrum. To optimize NMR logging, selecting appropriate logging speeds and enhancing SNR is critical for accurate lithology and porosity characterization. This research contributes to improving NMR tool performance and pre-logging planning.