Spectral data of 193 shale samples collected from Cleveland and Wessex Basins in the United Kingdom were generated from the mid-infrared (MIR) region of the electromagnetic spectrum using two types of Fourier transform infrared (FTIR) spectroscopic techniques, attenuated total reflectance (ATR) and diffuse reflectance infrared fourier transform (DRIFT). Spectral data acquired using these techniques were combined with partial least square regression (PLSR) to calibrate models capable of rapid, routine, and accurate quantification of total organic carbon (TOC) concentration in sediment. At the validation stage, DRIFT presented high correlation coefficient (R² = 0.96) between LECO measured and model-predicted TOC concentration relative to ATR (R² = 0.89). Further optimisation of the DRIFT model with a balanced data set offered an improved correlation coefficient (R² = 0.99) at the calibration and validation stages. Prediction of TOC content of shale samples with unknown values using the optimised model presented good correlation and low modelling error (R² = 0.93; RMSE = 1.5 wt %): an indication that MIR-DRIFT-PLSR has the potential for accurate and precise quantification of sediment TOC concentration. The presence of organic functional groups and mineral absorption bands observed on the MIR spectra renders the technique indispensable for real-time simultaneous characterisation of TOC and minerals in Gas Shales and other formations during exploration.

从英国克利夫兰和威塞克斯盆地采集的 193 个页岩样品的光谱数据是使用两种类型的傅里叶变换红外 (FTIR) 光谱技术，衰减全反射 (ATR)和漫反射红外傅里叶变换 (DRIFT)。使用这些技术获得的光谱数据与偏最小二乘回归 (PLSR) 相结合，以校准能够快速、常规和准确量化沉积物中总有机碳 (TOC) 浓度的模型。在验证阶段，DRIFT^在LECO 测量和模型预测的 TOC 浓度相对于ATR  ( R ² = 0.89)。使用平衡数据集进一步优化 DRIFT 模型在校准和验证阶段提供了改进的相关系数 ( R ²  = 0.99)。使用优化模型预测未知值页岩样品的 TOC 含量表现出良好的相关性和低建模误差（R ²  = 0.93；RMSE  = 1.5 wt %）：表明 MIR-DRIFT-PLSR 具有准确和精确量化的潜力沉积物 TOC 浓度。在 MIR 光谱上观察到的有机官能团和矿物吸收带的存在使得该技术对于在勘探过程中对气页岩和其他地层中的 TOC 和矿物进行实时同时表征是必不可少的。