地球物理学进展 ›› 2020, Vol. 35 ›› Issue (1): 272-280.doi: 10.6038/pg2020CC0542

• 应用地球物理学Ⅰ(油气及金属矿产地球物理勘探) • 上一篇    下一篇

煤层气储层物性影响因素和预测方法综述与展望

赵军龙1,2, 池佳玮1,2   

  1. 1. 西安石油大学地球科学与工程学院,西安 710065;
    2. 西安石油大学陕西省油气成藏地质学重点实验室,西安 710065
  • 收稿日期:2019-05-06 修回日期:2019-11-01 出版日期:2020-02-20 发布日期:2020-03-18
  • 作者简介:赵军龙,男,1970生,博士,教授,硕士生导师,主要从事测井资料处理与解释、复杂油气藏测井评价. E-mail:zjl1970@163.com
  • 基金资助:
    国土资源部煤炭资源勘查与综合利用重点实验室开放课题(KF2014-03)资助.

Review and prospect of influencing factors and prediction methods of coal bed gas reservoir physical properties

ZHAO Jun-long1,2, CHI Jia-wei1,2   

  1. 1. School of Earth Sciences and Engineering, Xi'an Shiyou University, Xi'an 710065, China;;
    2. Shaanxi Key Laboratory of Petroleum Accumulation Geology, Xi'an Shiyou University, Xi'an 710065, China;
  • Received:2019-05-06 Revised:2019-11-01 Online:2020-02-20 Published:2020-03-18

摘要: 为了解决煤储层物性的预测方法问题,本文基于大量的文献调研,梳理了煤储层孔隙性和渗透性的影响因素和预测方法,并进行了预测技术展望.研究表明,孔隙性影响因素主要有煤层埋深、压实作用、变质程度和显微组分等,孔隙度预测方法主要有双侧向迭代法、阿尔奇公式裂缝孔隙度估算法、双侧向数值模拟法、相关分析方法及支持向量机等方法;渗透性影响因素主要有煤层埋深、储层压力、煤的变质程度、煤体结构、煤岩组分、应力状态、基质收缩作用和裂隙系统发育程度等,渗透性预测方法主要有F-S计算方法、基于达西定律的计算方法、相关分析法及多层次模糊综合评判法等其他方法.本文认为遵循“地质约束测井、岩心刻度测井”的原则,加强煤层气储层岩石物理研究和物性影响因素分析是基础;常规测井信息与测井新技术信息结合,“多尺度信息融合”建立煤岩孔隙度和渗透率解释新模型,充分发挥多种非线性数学方法的优势构建煤岩物性非线性数学预测方法有一定的实际意义.

关键词: 煤储层, 孔隙度, 渗透率, 影响因素, 预测方法

Abstract: In order to solve the problem of predicting the physical properties of coal reservoirs. Based on a large number of literature investigations, this paper combs the influencing factors and prediction methods of coal reservoir porosity and permeability, and forecasting the prediction technology. The research indicates that the factors affecting the porosity are mainly the buried depth, compaction, metamorphism and microscopic composition of the coal seam. The porosity prediction methods mainly include the double lateral iteration method, the Archie formula crack porosity estimation method, and method of the dual laterolog numerical simulation, correlation analysis and support vector machine; the main factors of permeability include coal seam depth, reservoir pressure, coal metamorphism, coal structure, coal and rock composition, stress state, matrix shrinkage and the degree of development of the fracture system, etc., the permeability prediction methods mainly include FS calculation method, calculation method based on Darcy's law, correlation analysis method and multi-level fuzzy comprehensive evaluation method. This paper believes that following the principle of “geological constrained logging and core scale logging”, the basis is strengthening the petrophysical research and analyzing physical property influencing factors of coalbed methane reservoirs. On the basement of combining the conventional logging data and new logging technique data, the new interpretation models of porosity and permeability are built on Multi-scale information fusion. It is important that the nonlinear mathematical prediction method of coal petrophysical properties will be built by the advantages of many nonlinear mathematical methods.

Key words: Coal reservoir, Porosity, Permeability, Influencing factors, Prediction method

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