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Research on the Prediction Method of Shale Gas Production Capacity Using Stratigraphic Gas Index: Taking the Longmaxi Formation Marine Shale Gas Layer in Southern Sichuan as an Example

  • Qiang Shi,
  • Peng Chen,
  • XiangYang Pei

摘要

To address the challenges of significant production fluctuations and difficulties in productivity prediction for shale gas in the southern Sichuan Basin, this study proposes a methodology that comprehensively considers the differential contributions and temporal variations of shale gas in different occurrence states. By precisely differentiating the proportion of free gas and adsorbed gas in production output, an ideal production curve for shale gas was established based on actual production data analysis. Through detailed logging evaluation methods, key parameters including TOC (Total Organic Carbon), gas saturation, porosity, and brittle mineral content were obtained. This enabled the construction of gas-bearing index models for both free gas and adsorbed gas, along with a calculation model for total shale gas reservoir gas content. The weight of contributions from free gas and adsorbed gas to productivity was determined, ultimately forming a geological factor-based prediction method for initial production (test production, first-year average daily output) and cumulative production (EUR). Key findings include: (1) Productivity prediction prerequisites lie in defining and differentiating the contributions of free gas and adsorbed gas; (2) Free gas productivity is primarily controlled by gas saturation, porosity, and brittle mineral content, while adsorbed gas productivity mainly depends on TOC content; (3) Initial production is predominantly governed by free gas quantity, whereas EUR is jointly controlled by both free gas and adsorbed gas volumes, with reservoir thickness being a critical parameter. Application results in the southern Sichuan Basin demonstrate that high-precision shale gas productivity prediction during early development stages is achievable when key controlling factors are accurately identified and reservoir parameters are precisely calculated.