低孔渗可改造性储层测井产能预测方法研究

发布时间：2018-02-01 05:00

本文关键词： 低孔低渗储层测井解释水力压裂压裂施工参数产能级别　出处：《长江大学》2017年硕士论文　论文类型：学位论文

【摘要】：对储层油气产能进行合理地评价预测,一方面是对油气勘探成果的检验,同时又可以为油气田开发提供指导,对后期开发优势储层,提高油气产量和实际生产经济效益具有非常重要的意义。低孔渗油气藏作为油气资源的重要组成部分,在油气资源分布中占有重要地位。然而低孔渗储层一般需要对其进行酸化、压裂等措施才能达到工业开采价值,目前利用测井资料预测储层压裂后油气产能具有一定的难度,因此开展低孔渗储层油气产能预测研究工作,对指导低渗透储层的油气开发具有重要意义。本文研究区为XF区块和XG区块,XF区块目的层位为阜宁组一段,为典型的低孔低渗砂岩储层,储层基本无自然产能,几乎每口井都需要压裂,产能主要为压裂后产能。XG区块目的层位为阜宁组二段,储层物性优于XF区块,该区岩性相对于XF区块更为复杂,存在灰岩,部分砂岩灰质含量也较高。该区既有自然产能也有压裂后产能还有酸化酸压后产能,以自产和压裂为主。本文研究目的是针对区块开展低孔渗砂岩储层压后产能预测方法的实用性研究,建立一套适用于研究区块产能评价的方法。由于影响研究区产能的关键因素不明确,在储层评价的基础上,从储层参数以及压裂施工参数二个方面分析了其对产能的影响,分别建立了对应区块产能级别预测模型。研究区测井系列不全,基本的9条测井曲线中,只有部分取心井测量了中子和密度曲线。针对这一情况,利用所收集的资料,对XF区块、XG区块2个区块开展相关研究工作,取得的主要成果如下:1.建立了XF区块的孔隙度与声波时差的统计模型以及渗透率与孔隙度的统计模型;建立了XG区块基于灰质和泥质校正的孔隙度体积模型和与孔隙度单相关的渗透率统计模型。2.XF区块分别建立了阿尔奇模型、变参数(m)阿尔奇模型及等效岩石组分模型,并相互对比了三种饱和度模型评价的效果,认为等效岩石组分模型和变参数(m)阿尔奇模型的效果优于阿尔奇模型;XG区块建立了阿尔奇模型对饱和度进行评价。3.依据XF区块的测试资料,建立了基于Fisher判别的产能级别预测模型;依据XG区块的测试资料,首先建立了基于GR与AC测井资料的储层改造措施(自产、水力压裂和酸化)的判别,然后针对水力压裂测试层建立产能分级预测图版。
[Abstract]:Reasonable evaluation and prediction of reservoir oil and gas productivity, on the one hand, is to test the oil and gas exploration results, but also to provide guidance for the development of oil and gas fields, to the later development of the superior reservoir. It is very important to improve oil and gas production and actual economic benefit. Low porosity and permeability reservoir is an important part of oil and gas resources. It plays an important role in the distribution of oil and gas resources. However, the low porosity and permeability reservoirs generally need acidification, fracturing and other measures to achieve the value of industrial exploitation. At present, it is difficult to predict oil and gas productivity after reservoir fracturing by using logging data, so the research work of oil and gas productivity prediction in low porosity and permeability reservoir is carried out. This study area is XF block and XG block XF block, the target horizon of XF block is Funing formation, which is a typical low porosity and low permeability sandstone reservoir. The reservoir basically has no natural productivity, almost every well needs fracturing, the productivity is mainly after fracturing. The target horizon of XG block is the second stage of Funing formation, and the reservoir physical property is better than XF block. Compared with XF block, the lithology of this area is more complex, with limestone and high content of some sandstone lime-matter. The area has both natural productivity and production capacity after fracturing as well as acidizing acid-fracturing production. The purpose of this paper is to study the practicability of the prediction method of post-pressure productivity of low porosity and permeability sandstone reservoir. To establish a set of methods suitable for productivity evaluation of study blocks. Because the key factors affecting productivity in the study area are not clear, on the basis of reservoir evaluation. The influence of reservoir parameters and fracturing operation parameters on productivity is analyzed, and the prediction model of productivity level of corresponding blocks is established respectively. The logging series in the study area is incomplete and the basic logging curves are 9. Only a part of coring wells have measured neutron and density curves. In view of this situation, using the collected data, the relevant research work has been carried out on two blocks of XF block and XG block. The main results are as follows: 1. The statistical model of porosity and acoustic moveout of XF block and the statistical model of permeability and porosity are established. The porosity volume model of XG block based on gray and mud correction and the statistical model of permeability related to porosity single are established. 2. The Archie model of XG block is established respectively. The results of three saturation models are compared with each other. It is considered that the equivalent rock component model and the variable parameter (m) Archie model are better than the Archie model. According to the test data of XF block, the productivity level prediction model based on Fisher is established. Based on the test data of XG block, the measures of reservoir reconstruction (self-producing, hydraulic fracturing and acidizing) based on gr and AC logging data are established. Then, the productivity grade prediction chart is established for hydraulic fracturing test layer.
【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】：TE328;P631.81

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