A log-based method for fine-scale evaluation of lithofacies and its applications to the Gulong shale in the Songliao Basin, Northeast China

Abstract

The Gulong shale demonstrates high clay content and pronounced thin laminations, with limited vertical variability in log curves, complicating lithofacies classification. To comprehend the distribution and compositional features of lithofacies in the Gulong shale for optimal sweet spot selection and reservoir stimulation, this study introduced a lithofacies classification scheme and a log-based lithofacies evaluation method. Specifically, the ΔlgR method was utilized for accurately determining the total organic carbon (TOC) content; a multi-mineral model based on element-to-mineral content conversion coefficients was developed to enhance mineral composition prediction accuracy, and the microresistivity curve variations derived from formation micro-image (FMI) log were used to compute lamination density, offering insights into sedimentary structures. Using this method, integrating TOC content, sedimentary structures, and mineral compositions, the Qingshankou Formation is classified into four lithofacies and 12 sublithofacies, displaying 90.6% accuracy compared to core description outcomes. The classification results reveal that the northern portion of the study area exhibits more prevalent fissile felsic shales, siltstone interlayers, shell limestones, and dolomites. Vertically, the upper section primarily exhibits organic-rich felsic shale and siltstone interlayers, the middle part is characterized by moderate organic quartz-feldspathic shale and siltstone/carbonate interlayers, and the lower section predominantly features organic-rich fissile felsic/clayey felsic shales. Analyzing various sublithofacies in relation to seven petrophysical parameters, oil test production, and fracturing operation conditions indicates that the organic-rich felsic shales in the upper section and the organic-rich/clayey felsic shales in the lower section possess superior physical properties and oil content, contributing to smoother fracturing operation and enhanced production, thus emerging as dominant sublithofacies. Conversely, thin interlayers such as siltstones and limestones, while producing oil, demonstrate higher brittleness and pose great fracturing operation challenges. The methodology and insights in this study will provide a valuable guide for sweet spot identification and horizontal well-based exploitation of the Gulong shale.

Keywords

• Lithofacies division
• Formation micro-image (FMI) log
• Lithoscanner logging
• Fine-scale log-based evaluation
• Gulong shale