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    利用弹性参数反演预测潮汕坳陷目标构造的含油气性

    Hydrocarbon prediction of Mesozoic target structure in Chaoshan Depression based on pre−stack elastic parameter inversion

    • 摘要:
      研究目的 潮汕坳陷构造隆起部位受砂岩储层发育程度和构造条件的双重控制,其侧翼洼陷为其提供烃源,是油气聚集最有利区。利用地震反演的弹性参数进行含油气性预测的潮汕坳陷中生界砂岩储层具有明显的低密度特征,而其他岩性的密度偏高。
      研究方法 利用叠前地震全道集资料直接反演密度、泊松比等弹性参数,通过密度反演成果预测砂岩储层发育情况和烃类分布,实现对中生界含油气性的预测。
      研究结果 泊松比对烃类比较敏感,储层含烃后具有明显的低泊松比特征。
      结论 利用地震反演的弹性参数进行含油气性预测表明,烃类异常特征明显,预测构造隆起部位具有较好的含油气性。叠前弹性参数反演技术使无井区域储层预测的多解性与不确定性大大降低,提高了反演结果的准确性和可靠性,这项技术的应用对于类似研究新区的储层预测和烃类检测工作,具有很好的应用推广价值。

       

      Abstract:
      This paper is the result of oil and gas exploration engineering.
      Objective The structural uplift of Chaoshan depression is controlled by the development degree of sandstone reservoir and tectonic conditions. It’s flank depression provides a source of hydrocarbon, which is the most favorable area for zones of hydrocarbon accumulation. The Mesozoic sandstone reservoirs in the Chaoshan Depression have obvious low−density characteristics based on the elastic parameters of seismic inversion to predict the oil and gas properties, while the density of other lithologies is high.
      Methods The elastic parameters such as density and Poisson's ratio were directly inverted from the pre−stack seismic data, and the development of sandstone reservoirs and the distribution of hydrocarbons were predicted through the density inversion results, so as to realize the prediction of the Mesozoic oil and gas content.
      Results The Poisson's ratio is sensitive to hydrocarbons, and the reservoir has obvious characteristics of low Poisson's ratio after hydrocarbons.
      Conclusions The elastic parameters of seismic inversion are used to predict the oil and gas properties, and the hydrocarbon anomalies are obvious, and the predicted structural uplift has good oil and gas properties. The pre−stack elastic parameter inversion technology greatly reduces the multi−solution and uncertainty of reservoir prediction in well−free areas, and improves the accuracy and reliability of inversion results.

       

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