Selective methods of TOC content estimation for organic-rich interbedded mudstone source rocks

Abstract

The total organic carbon content (TOC) is one of the key parameters for evaluating the hydrocarbon generation potential of source rocks. Petroleum geochemists and geologists usually use conventional logging curves to predict TOC content in order to reduce the errors caused by limited TOC content data. The ΔlogR method is the most widely used TOC prediction method. However, it is not applicable to organic-rich mudstone interlayers, due to the rapidly changing lithology and the difficulty in determining a baseline. Some improved ΔlogR methods and artificial neural network techniques have also been proposed by previous authors. In this paper, a 3D surface fitting technique based on biharmonic interpolation is proposed to optimize an improved ΔlogR method. A total of 76 samples were divided into pure mudstone and mudstone interlayers. The correlation coefficient (R) and the root mean square error (RMSE) between the measured TOC and the predicted TOC obtained using the improved ΔlogR method, the artificial neural network method, and the 3D surface fitting method were calculated. These methods were applied to assess the source rocks of the Eocene Liushagang Formation in the Fushan Depression, South China Sea. The results show that the 3D surface fitting method can effectively distinguish source rocks from non-source rocks and has a higher accuracy, which makes it the most suitable method for assessing the TOC content of organic-rich source rocks with alternating mudstone layers.