Nuclear magnetic resonance (NMR) log is a powerful tool to obtain porosity and oil saturation in reservoir evaluation. NMR echo inversion, however, may give poor information in the two parameters if the ratio of signal-to-noise is not so good. Combining NMR log and some conventional logs, such as GR log, sonic log, and density log, a novel inversion algorithm is developed in this research. First, normalize the logging response, then, insert both the logging response equations and the definition equations of volume model into the NMR echo equations. By conducting the data inversion for both NMR echo and conventional logging data, the porosity and oil saturation can be calculated. The condition number of the inversion matrix is decreased, so, the inversion parameters own better stability and the random weak noise is stifled. Furthermore, the T2 spectral distribution derived from the new inversion seems to be sensitive to the small pores in tight reservoir. Due to the weak noise removal and sensitiveness of small pore, the novel inversion may be utilized in reservoir evaluation in shale oil and gas, such as the identification of “sweet spot”.

中文翻译：

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一种结合核磁共振测井和常规测井的新型反演

核磁共振 (NMR) 测井是在储层评价中获取孔隙度和含油饱和度的有力工具。但是，如果信噪比不太好，则 NMR 回波反演可能会在两个参数中提供较差的信息。结合核磁共振测井和一些常规测井，如GR测井、声波测井和密度测井，本研究开发了一种新的反演算法。首先对测井响应进行归一化处理，然后将测井响应方程和体积模型定义方程都插入到核磁共振回波方程中。通过对核磁共振回波和常规测井数据进行数据反演，可以计算孔隙度和含油饱和度。反演矩阵的条件数减少，反演参数具有较好的稳定性，抑制了随机弱噪声。此外，新反演得到的 T2 谱分布似乎对致密储层中的小孔隙敏感。由于去噪能力弱，小孔隙灵敏度高，这种新型反演可用于页岩油气储层评价，如“甜点”识别。