松辽盆地南部油页岩地层的测井评价方法研究

发布时间：2018-03-11 08:47

本文选题：松辽盆地南部油页岩　切入点：油页岩物理性质的实验室测量与分析　出处：《吉林大学》2015年硕士论文　论文类型：学位论文

【摘要】：近年来，积极勘探开发油页岩等非常规新能源成为世界各国缓解能源紧张问题的有效途径。松辽盆地蕴含了丰富与油气共生的油页岩资源，青山口组和嫩江组油页岩构成了松辽盆地南部主要生油岩系。如何将油页岩与其他岩性区分出来，怎样能够实现含油率的准确计算等问题成为了油页岩勘探开发中的关键问题，因此利用测井方法进行油页岩的识别以及含油率的准确计算具有现实意义。目前国内外学者对松南地区油页岩的研究多集中于区域地质概况、成矿规律等方面，而没有对其进行过物理参数的实验室测量与分析，本文考虑到实验室现有仪器水平，从密度、孔隙度、声波速度、介电常数这几个参数的测量入手，对研究区油页岩的物理性质进行总结，为其他地区油页岩的物性参数提供参考，并为后续油页岩储层的测井评价提供参数支持。根据油页岩与其他岩性在测井响应上的区别，建立研究区不同岩性测井响应样本数据库。以支持向量机、朴素贝叶斯判别以及Fisher判别法为基础，综合考虑到三种方法在原理等方面的差异，建立多元综合法进行岩性识别。从该方法在研究区的应用效果来看，岩性识别结果与录井岩性基本吻合，油页岩平均识别准确率达86.3％，能够实现油页岩与其他岩性的有效区分。建立岩石物理体积模型是油页岩测井评价中的重要内容，本文首先对Dicman Alfred于2012年提出的基于密度测井曲线的有机页岩模型计算公式推广到符合体积模型的一般测井曲线，并将该模型应用到松南地区油页岩储层孔隙度的计算中；实现四组分模型在研究区油页岩储层各组分含量的计算；在四组分模型基础之上提出将孔隙中流体进一步细分的油页岩五组分体积模型，，即“非粘土矿物+有机质+粘土矿物+孔隙中游离油+孔隙中自由水”，通过建立起声波时差、自然伽马的响应方程，并结合泥质砂岩导电模型建立起响应方程组，利用模拟退火算法实现了对非线性响应方程组的求解，从而得到各组分含量，F1井计算出的孔隙度与实验室孔隙度之间平均绝对误差0.11。建立油页岩总含油率计算模型，即首先建立起松南地区有机质含油率的计算公式，再借助五组分模型计算出游离态含油率，最后将两部分含油率相加获得总含油率，研究区油页岩总含油率平均值约为10％。根据上述内容建立“松辽盆地南部油页岩地层的综合测井评价系统”，开发相应油页岩测井评价软件，并对松南地区油页岩的实际测井资料进行处理。
[Abstract]:In recent years, active exploration and development of oil shale and other unconventional new energy has become an effective way to alleviate the energy shortage problem all over the world. The Songliao basin contains abundant oil shale resources and oil-gas symbiosis, Qingshankou and Nenjiang oil shale constitute the main source rocks in the southern Songliao basin. How will the oil shale and other rocks how to distinguish, can realize the accurate calculation of oil content and other issues has become a key problem of oil shale exploration and development is of practical significance to accurately calculate so using well logging method for identification of oil shale and oil content.
The current research on oil shale in Songnan area of domestic and foreign scholars focus on regional geology, metallogenic regularity, and no laboratory measurement and analysis of the physical parameters, considering the existing laboratory instruments, from the density, porosity, acoustic velocity, measuring the dielectric constant of the parameters of study on the physical properties of oil shale were summarized, to provide reference for the physical parameters of oil shale and other areas, and to provide support for the subsequent evaluation logging parameters of oil shale reservoir.
According to the oil shale and other rocks in different logging response, a study of different logging response samples database. Based on the support vector machine, Naive Bayesian discriminant and Fisher discriminant method, considering the difference of the three methods in the aspects of principle, establish comprehensive method for lithology identification. From the result of applying the method in the study area, the lithology identification results and logging lithology with oil shale average recognition rate is 86.3%, can effectively distinguish oil shale and other rocks.
The establishment of rock physical volume model is an important part of the evaluation of oil shale in logging, this paper puts forward Dicman Alfred in 2012 organic shale density logging curve based on the model calculation formula is extended to meet the log volume model, and this model is applied to calculate oil shale reservoir porosity in Songnan area; the realization of the four group the model in the calculation of rock reservoir of the component content of oil shale in the region; four component model based on the pore fluid further subdivision of the oil shale five component volume model, namely "non clay mineral and organic clay mineral pore free + + oil + free water in pores, through setting up sonic, natural gamma ray response equation, and combining the shaly sand model established response equations, the equations of nonlinear response based on simulated annealing algorithm, The average absolute error between the porosity calculated by F1 well and the porosity of the laboratory is 0.11.
The establishment of oil shale oil content calculation model is first established calculation formula of organic matter content in Songnan area, and with the help of five component model to calculate the free state content, the two parts of oil yield obtained by adding the total oil content, oil shale of the total oil average rate is about 10%.
The establishment of comprehensive logging in southern Songliao Basin oil shale formation evaluation system based on the above contents, the corresponding development of oil shale logging evaluation software, and the actual logging data of oil shale in Songnan area for processing.

【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P618.12;P631.81

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