中国石油勘探 ›› 2018, Vol. 23 ›› Issue (4): 107-113.DOI: 10.3969/j.issn.1672-7703.2018.04.012

• 工程技术 • 上一篇    下一篇

不确定性致密气产能预测技术

白玉湖   

  1. 中海油研究总院有限责任公司
  • 收稿日期:2017-04-17 修回日期:2018-04-13 出版日期:2018-07-15 发布日期:2018-07-11
  • 基金资助:
    中海油综合科研项目“海外页岩油气产能评价技术与方法研究”(YXKY-2016-ZY-03);中海油研究总院有限责任公司创新项目:“煤层气—致密气联合开发层间干扰规律研究”(2017-JCJS-01)。

Uncertain productivity prediction technology for tight gas

Bai Yuhu   

  1. CNOOC Research Institute Co., Ltd
  • Received:2017-04-17 Revised:2018-04-13 Online:2018-07-15 Published:2018-07-11
  • Supported by:
     

摘要: 致密气产能预测涉及储层物性、压裂裂缝形态等参数,但由于致密储层渗透率很低,孔隙尺度小,储层非均质性强,孔喉分布差异大,采用压裂开发会导致预测储层及压裂裂缝参数具有一定的不确定性,因此仅给参数赋一个确定的值进行产能评价是不够全面的。研究认为致密储层绝对渗透率、有效渗透率、有效压裂裂缝半长等均有一定的不确定性,基于此,提出了不确定性致密气产能预测技术,以单井测试的无阻流量为基础,通过产能方程反算确定气相有效渗透率及有效裂缝半长等概率分布,在获取储层及流体物性参数基础上,计算区块无阻流量概率分布;然后,利用参数概率分布,采用解析模型方法预测产量剖面的概率分布。该方法既适用于区块也适用于单井概率产能预测,为降低致密气产能预测的不确定性提供了一种新的途径。

 

关键词: 致密气, 不确定性, 产能预测, 有效渗透率, 解析模型

Abstract: Tight gas productivity prediction involves parameters such as reservoir properties and fracture shape. However, with low permeability, small pore size, strong reservoir heterogeneity, and wide distribution of pore throats, there are uncertainties in predicting reservoir and fracture parameters. Therefore, such productivity prediction is not comprehensive as only by giving one definite value to a parameter. The study shows that there are uncertainties in absolute reservoir permeability, effective permeability, and half lengths of effective induced fractures. In such case, an uncertain productivity prediction technology for tight gas was proposed. First, based on the open flow potentials of single wells, the productivity equation was used to inversely determine the probabilistic distribution of effective gas permeability and the half lengths of effective induced fractures, and the probabilistic distribution of the open flow potential of a block was calculated based on available reservoir and fluid properties; second, the probabilistic distribution of production profiles was predicted based on the parameter probabilistic distribution and an analytical model. This method is applicable for both block and single-well probabilistic productivity prediction, and provides a new way to reduce the uncertainties in tight gas productivity prediction.

Key words: tight gas, uncertainties, productivity prediction, effective permeability, analytical model

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