蚀变中基性火山岩储层ABC-CM最优化测井解释方法研究

发布时间：2018-03-31 05:05

本文选题：中基性火山岩　切入点：人工蜂群算法　出处：《吉林大学》2017年硕士论文

【摘要】：近年来,由于勘探水平的陆续提高以及砂岩、碳酸盐岩等储层资源总量不断降低,使火山岩储层成为另一个重要勘探领域。作为对常规油气资源的补充,火山岩储层不仅备受石油地质学家们的关注,同时引起我国油田勘探界学者的重视。然而火山岩的岩性和储层类型繁杂、埋藏深度大、物性较差以及火山岩储层往往还存在着蚀变现象,所以,开展火山岩储层的测井评价研究是一项不仅具有明显理论价值,还具有重要现实意义的工作。常规解释方法存在着诸如测井资料应用不充分、不能灵活选择解释模型、对多矿物复杂地层难以有效评价等问题。常规测井解释方法已经不能完全满足复杂的火山岩储层测井评价。最优化测井解释方法与采用固定解释模型的常规测井解释方法不同,它可以将测井信息、误差及地区地质经验综合成多维信息复合体,通过选取数学中的最优化方法并采用合理的解释模型和测井响应方程,建立最优化测井解释响应目标函数,在误差允许范围内,计算出一个最能反映解释点地层地质因素的目的层参数的最优解。本文针对松辽盆地南部W断陷中基性火山岩储层,从微观参数层面出发,根据研究区的岩心、薄片以及压汞数据分析,共采用了五种方法进行孔隙度及渗透率的下限值求取,分别为经验统计法、孔隙度-渗透率交会法、0.1μm进汞饱和度法、以及最小孔喉半径法和中值压力法。并根据试气资料对计算出的下限值进行验证,结果表明本文所用方法可靠,为油气勘探开发和后期决策奠定了基础。由于研究区中基性火山储层发生蚀变现象,故需要在最优化体积解释模型中考虑次生的粘土矿物,建立了考虑蚀变的中基性火山岩储层模型为孔隙、石英、长石、暗色矿物及蚀变的粘土矿物,利用人工蜂群-复合形混合优化方法求取松辽盆地南部W断陷中基性火山岩储层某井段的五个组分体积含量。其中人工蜂群算法是一种新兴的优化算法,为蚀变中基性火山岩储层的最优化测井解释提供了一种新方法。并计算了考虑蚀变现象的饱和度值,在W断陷多口井进行了实际处理,结果与试气结论符合。本文主要创新点包括:从微观参数层面出发,针对研究区中基性火山岩储层,确定储层孔隙度及渗透率的下限值;考虑蚀变因素,建立中基性火山岩储层模型为孔隙、石英、长石、暗色矿物及蚀变的粘土矿物;将人工蜂群算法引入中基性火山岩储层的测井解释中,并与复合形算法结合来求解上述五个未知组分参数值。
[Abstract]:In recent years, volcanic reservoir has become another important exploration field because of the continuous improvement of exploration level and the decrease of sandstone, carbonate and other reservoir resources, as a supplement to conventional oil and gas resources. Volcanic reservoir has not only attracted the attention of petroleum geologists, but also attracted the attention of oil exploration scholars in China. However, the lithology and reservoir types of volcanic rocks are complicated, and the depth of burial is large. Because of the poor physical properties and the phenomenon of alteration in volcanic reservoir, it is not only of great theoretical value to carry out well logging evaluation of volcanic reservoir. There are also important work of practical significance. Conventional interpretation methods, such as inadequate application of logging data, are unable to flexibly select interpretation models, It is difficult to effectively evaluate the multi-mineral complex formation. The conventional logging interpretation method can not fully satisfy the complex volcanic reservoir logging evaluation. The optimization logging interpretation method is different from the conventional logging interpretation method using a fixed interpretation model. It can synthesize logging information, error and regional geological experience into multi-dimensional information complex. By selecting optimization method in mathematics and adopting reasonable interpretation model and logging response equation, the objective function of optimum logging interpretation response can be established. An optimal solution of the target layer parameters, which can best reflect the geological factors of the interpretation point, is calculated within the range of errors. In this paper, the microcosmic parameters of the basic volcanic reservoir in the W fault depression in the south of Songliao Basin are studied. Based on the analysis of core, thin slice and mercury injection data in the study area, five methods were used to calculate the lower limit of porosity and permeability, namely, empirical statistics method, porosity permeability intersection method and 0.1 渭 m mercury saturation method. The minimum pore throat radius method and the median pressure method are used to verify the calculated lower limit values according to the gas test data. The results show that the method used in this paper is reliable. It is necessary to consider the secondary clay minerals in the optimal volume interpretation model because of the alteration of the basic volcanic reservoir in the study area. In this paper, a model of meso-basic volcanic reservoir considering alteration is established, which consists of pore, quartz, feldspar, dark mineral and altered clay mineral. The volume content of five components in a well section of a basic volcanic rock reservoir in W fault depression in the south of Songliao Basin is obtained by using the hybrid optimization method of artificial bee colony and complex shape, among which artificial bee colony algorithm is a new optimization algorithm. This paper provides a new method for optimizing logging interpretation of basic volcanic rock reservoir in alteration, calculates saturation value considering alteration phenomenon, and carries out practical processing in many wells of W fault depression. The results are consistent with the conclusion of gas test. The main innovation of this paper is to determine the lower limit of reservoir porosity and permeability from the microscopic parameter level, considering the alteration factors, and to determine the lower limit of porosity and permeability of the middle and basic volcanic reservoir in the study area. The model of middle basic volcanic reservoir is established as pore, quartz, feldspar, dark mineral and altered clay mineral, and artificial bee colony algorithm is introduced into logging interpretation of middle basic volcanic reservoir. And combined with the complex algorithm to solve the above five unknown component parameters.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P618.13;P631.81

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