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<p>The deep Huoshiling Formation of Chaganhua Sub-sag in Songnan Fault Depression has developed intermediate-basic volcanic rocks, with complex lithology, significant difference in reservoir physical properties, strong heterogeneity, and the influence of low-velocity tuffite. It is difficult to identify and predict the volcanic reservoir. In this paper, first, we calculated different mineral components of the volcanic rocks based on elemental capture spectroscopy logging and the normative mineral method. Taking the Xu-Panye rock physics model as the framework, the parameters of the physical model were optimized through error fusion and iteration, and a multi-mineral petrophysical model of volcanic rocks suitable for the study area was constructed. Sensitive elastic parameters for tuffite and reservoirs identification selected through petrophysical analysis. Then, based on pre-stack simultaneous inversion of wide-azimuth OVT gathers and Bayesian lithofacies probability analysis, different volcanic lithofacies bodies and reservoir probability bodies were obtained, thereby conducting quantitative prediction of volcanic reservoirs in the Huoshiling Formation of the study area. The reservoir results show a high degree of consistency with actual drilling data, achieving good practical application effects.</p>

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Study on prestack reservoir prediction of deep volcanic rock gas reservoirs in Chaganhua sub-sag of Songnan Fault Depression

  • 期刊论文

  • 发表日期：

    2025年12月8日

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  • Qin-lin Yang,
  • Xue-pei Fan,
  • Chen-chen Bi,
  • Lan-mei Ke,
  • Ye Yang,
  • Da Zhang,
  • Shu Wang

摘要

The deep Huoshiling Formation of Chaganhua Sub-sag in Songnan Fault Depression has developed intermediate-basic volcanic rocks, with complex lithology, significant difference in reservoir physical properties, strong heterogeneity, and the influence of low-velocity tuffite. It is difficult to identify and predict the volcanic reservoir. In this paper, first, we calculated different mineral components of the volcanic rocks based on elemental capture spectroscopy logging and the normative mineral method. Taking the Xu-Panye rock physics model as the framework, the parameters of the physical model were optimized through error fusion and iteration, and a multi-mineral petrophysical model of volcanic rocks suitable for the study area was constructed. Sensitive elastic parameters for tuffite and reservoirs identification selected through petrophysical analysis. Then, based on pre-stack simultaneous inversion of wide-azimuth OVT gathers and Bayesian lithofacies probability analysis, different volcanic lithofacies bodies and reservoir probability bodies were obtained, thereby conducting quantitative prediction of volcanic reservoirs in the Huoshiling Formation of the study area. The reservoir results show a high degree of consistency with actual drilling data, achieving good practical application effects.