Evaluating what flows: a quantitative characterization of shale development sweet spots based on physical injection and NMR
Abstract
Accurate identification of sweet spots within shale reservoirs is critical for achieving economically efficient production. Effective evaluation methods can significantly enhance the development efficiency of shale oil while substantially reducing production costs. Addressing the prevalent mismatch between geologically and engineering-defined sweet spots and actual production performance, this study proposes, for the first time, a novel quantitative evaluation method for shale oil mobility. This method integrates Wood’s metal injection (WMI) experiments with centrifuge-based nuclear magnetic resonance (NMR) analysis, providing a comprehensive framework for assessing shale oil producibility. Using 18 representative shale samples, we introduce a new parameter, Es, which incorporates three key indicators—pore connectivity, lower limit of injection, and the proportion of free oil—to identify development sweet spots. Based on the Es parameter, the Q1–Q9 layers of the Qingshankou Formation's first and second members were classified into three categories: Type I (high-quality oil-bearing layers, Q1 and Q9), Type II (moderate-quality oil-bearing layers, Q2–Q4 and Q8), and Type III (Q5–Q7). The results demonstrate that the Es parameter effectively differentiates between samples with “high storage but low flowability” and those with “high mobility,” showing strong discriminatory power and engineering applicability. This approach not only extends the conceptual framework of traditional sweet spot evaluation but also provides a quantifiable basis for preferential zone selection and production forecasting in shale oil development. As such, it holds significant potential for broader application in unconventional reservoir evaluation and development strategies.
Fields of Study & Subjects
Hydrocarbon exploration and reservoir analysis
Hydraulic Fracturing and Reservoir Analysis
Enhanced Oil Recovery Techniques
Publication details
- Journal / source
- Results in Engineering
- Volume
- 29
- Pages
- 109339–109339
- Publication date
- 29 January 2026
- Language
- EN