S区块低渗—致密砂砾岩储层流体性质识别方法研究

发布时间：2018-05-07 20:35

本文选题：致密砂砾岩 + 四性关系　；参考：《长江大学》2017年硕士论文

【摘要】：随着油气资源需求持续增长,常规储层油气的勘探开发到达一个瓶颈期,世界关注的焦点逐步投入到非常规储层,其中非常规储层的致密砂砾岩储层受到越来越多的关注。致密砂砾岩储层流体性质识别遇到储层岩性、物性复杂、非均质性强、孔隙结构复杂及储层控制因素复杂等难题。本文针对致密砂砾岩储层流体性质识别方法进行研究,不仅有重要的理论意义,还可以为致密砂砾岩储层的勘探开发提供方法补充。本文以某油田低孔、低渗致密砂砾岩储层为主要研究对象,以研究区提供的岩心数据、物性分析资料、试油数据、测井资料以及地质录井信息为基础,主要针对研究区内30多口井对储层进行研究,形成了一套相对系统的致密砂砾岩储层流体性质识别的测井资料解释方法,建立了符合S区块流体识别的评价标准。储层的物理性质方面,研究区“四性”关系研究。发现研究区整体岩性复杂,较常规储层砂砾岩含量较高,孔渗关系复杂,且层控作用强于岩性,因此,后面建立储层参数解释模型应考虑分层位进行研究,并进一步建立储层“四性”关系图版。储层的典型储层的测井响应特征及影响因素:从测井响应角度出发,判断储层流体识别方法的基础就在于不同流体的岩石物理特征对测井响应的贡献大小。研究区最明显的影响因素是岩性,尤其是砾石含量较高的电阻率曲线呈异常高值。建立储层参数精细解释模型:利用自然伽马、声波、密度和粒度中值等参数建立了孔隙度、渗透率和饱和度的模型。其中,对传统的阿尔奇公式计算饱和度的模型进行改进,利用变岩电参数和等效岩石组分理论建立了EREM模型,提高了饱和度的计算精度。储层流体性质识别方法研究:利用试油资料及测井资料,分别采用三孔隙度差、比值法、电阻率差、比值法、中子-密度相关系数法、等效岩石弹性模型法及电阻率-孔隙度交会图版法判别S地区目标层组的气、水层,并给出了各种方法的判别标准。在实际应用中,对目的层段的流体性质进行识别,建议结合试油资料,选用多种方法进行综合流体性质判别,以期达到最为准确、可靠的识别效果。
[Abstract]:With the continuous increase of oil and gas resource demand, the exploration and development of conventional reservoir oil and gas reach a bottleneck period, and the focus of world attention is gradually put into unconventional reservoir, among which the dense sand and gravel reservoir of unconventional reservoir is paid more and more attention. The identification of fluid properties of tight sandstone and gravel reservoir is confronted with the problems of reservoir lithology, complex physical properties, strong heterogeneity, complex pore structure and complex reservoir control factors. In this paper, the method of identifying the fluid properties of dense gravel reservoir is studied, which is not only of great theoretical significance, but also can be used as a supplement to the exploration and development of dense sandstone and gravel reservoir. In this paper, the core data, physical property analysis data, oil test data, logging data and geological logging information provided by the study area are taken as the main research object of a low porosity and low permeability sand gravel reservoir in an oil field, which is based on the core data, physical property analysis data, oil test data, logging data and geological logging information provided by the study area. In this paper, more than 30 wells in the study area are studied, and a set of relatively systematic logging data interpretation method for identifying the fluid properties of dense sandy gravel reservoir is formed, and the evaluation criteria for fluid identification in S block are established. In terms of the physical properties of the reservoir, the relationship between the "four properties" of the study area is studied. It is found that the whole lithology of the study area is complex, the content of sandy gravel is higher than that of the conventional reservoir, the relationship between pore and permeability is complex, and the formation control action is stronger than that of lithology. Therefore, the stratification location should be considered in the later reservoir parameter interpretation model. And further establish the reservoir "four properties" relationship chart. Logging response characteristics and influencing factors of typical reservoirs: from the point of view of log response, the basis of identifying reservoir fluid is the contribution of petrophysical characteristics of different fluids to log response. The most obvious influencing factor in the study area is lithology, especially the abnormal high value of resistivity curve with high gravel content. The fine interpretation model of reservoir parameters is established: the porosity, permeability and saturation model are established by using natural gamma ray, acoustic wave, density and particle size median. Among them, the traditional Archie formula model for saturation calculation is improved, and the EREM model is established by using the variable rock electrical parameters and the equivalent rock component theory, which improves the accuracy of saturation calculation. Research on the identification method of reservoir fluid properties: using oil test data and logging data, adopting three porosity difference, ratio method, resistivity difference, ratio method, neutron-density correlation coefficient method, respectively. The equivalent rock elastic model method and the resistivity-porosity cross chart method are used to judge the gas and water layers of the target formation in S area and the criteria of these methods are given. In the practical application, the fluid properties of the target layer are identified, and it is suggested that combined with the oil test data, various methods should be used to judge the comprehensive fluid properties in order to achieve the most accurate and reliable recognition effect.
【学位授予单位】：长江大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P618.13

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