玛湖凹陷风南地区百口泉组砂砾岩储集层测井评价方法研究

发布时间：2018-05-31 05:57

本文选题：风南地区 + 百口泉组　；参考：《西南石油大学》2017年硕士论文

【摘要】：准噶尔盆地风南地区百口泉组是新疆油田重点勘探层位,该区百口泉组砂砾岩储集层具有以下特点:①储集层岩性复杂,岩石粒径跨度大且类型多样;②储集层孔隙结构多样,不同粒径岩石的的储集空间类型、孔渗关系复杂;③储集层具有较强的非均质性;研究区岩性的复杂性、储集空间类型的多样性以及储集层的非均质性造成储集层测井响应规律性较差,准确识别岩性、分析储集层主控因素、参数建模以及储集层分类成为砂砾岩测井评价面临的难题。本论文在分析研究区砂砾岩储集层特征的基础上,综合运用常规测井、试油、录井资料,并结合砂砾岩配套岩石物理实验,从岩性识别、储集层主控因素分析、储集层参数建模、储集层分类四方面进行测井评价。研究认为:①首先要对砂砾岩岩性重新分类,根据各类岩性岩石学特征差异及测井响应特征,构建岩性敏感参数中子-密度孔隙度差并基于交会图法联合识别岩性;②储集层岩石类型主要包括:粗砂岩、细砾岩、小中砾岩、大中砾岩;优势岩性为粗砂岩与细砾岩,黏土含量低,孔隙性、渗透性较好,小中砾岩与大中砾岩次之;研究区岩性分布规律与扇三角洲地质沉积认识相吻合,.③砂砾岩储集层具有较强的非均质性,基于岩心刻度测井的思想,分岩性建立储集层特征参数计算模型;运用阿尔奇公式(岩石物理实验确定m、n值)计算含油饱和度;提取高压压汞敏感参数定量表征孔隙结构优劣。④多种理论方法与现场实际相结合,得出储集层孔隙度下限是6.93%,渗透率下限为0.155mD;以储集层单位厚度产量作为目标函数并结合孔隙度、渗透率、孔隙结构表征参数构建储集层品质因子,结合不同岩性特征参数值并在既定物性下限的基础上对储集层进行有效分类,最终得出各类储集层分类标准。本文的完成为百口泉组砂砾岩储集层岩性识别、主控因素分析、储集层参数建模以及储集层分类提供了一套行之有效的方法,对提高砂砾岩测井解释精度具有重要意义。
[Abstract]:Baikouquan formation in Fengnan area of Junggar Basin is the key exploration horizon in Xinjiang Oilfield. The sand gravel reservoir of Baikouquan formation in this area has the following characteristics: complex lithology, large span of rock diameter and diverse pore structure of reservoir No. 2. The reservoir space types of different size rocks have strong heterogeneity of complex porosity and permeability relationship, and the complexity of lithology in the study area. The diversity of reservoir space types and reservoir heterogeneity result in poor logging response regularity, accurate identification of lithology, analysis of reservoir control factors, Parameter modeling and reservoir classification are difficult problems in sand gravel logging evaluation. On the basis of analyzing the characteristics of sand gravel reservoir in the study area, this paper synthetically uses the conventional logging, oil test, logging data, and combined with the physical experiment of sand gravel matching rock, analyzes the lithology identification and reservoir main controlling factors. Reservoir parameter modeling, reservoir classification four aspects of logging evaluation. It is considered that the first step is to reclassify the lithology of sandy conglomerate, and according to the difference of lithologic petrology and logging response, to construct the lithology sensitive parameter, the difference of neutron density porosity, and to identify lithology jointly based on cross plot method. (2) the reservoir rock types mainly include: coarse sandstone, fine conglomerate, small and medium conglomerate, large and medium conglomerate, the dominant lithology is coarse sandstone and fine conglomerate, the clay content is low, porosity, permeability is better, small and medium conglomerate and large and medium conglomerate take second place; The distribution of lithology in the study area coincides with the understanding of fan delta geological deposition. The reservoir has strong heterogeneity. Based on the idea of core calibration logging, the calculation model of reservoir characteristic parameters is established. The oil saturation is calculated by using Archie formula (determination of mnn value by rock physics experiment), and the quantitative characterization of pore structure by extracting sensitive parameters of high pressure mercury pressure is combined with field practice. It is concluded that the lower limit of reservoir porosity is 6.93 and the lower limit of permeability is 0.155mD.The reservoir quality factor is constructed by taking unit thickness of reservoir as objective function and combining porosity, permeability and pore structure characterization parameters. Combined with the values of different lithologic parameters and on the basis of the established lower limit of physical properties, the reservoir is effectively classified, and finally, the classification criteria of various reservoirs are obtained. The completion of this paper provides a set of effective methods for lithology identification, main control factor analysis, reservoir parameter modeling and reservoir classification in Baikouquan formation. It is of great significance to improve the interpretation accuracy of sand gravel logging.
【学位授予单位】：西南石油大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P618.13;P631.81

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