基于核主成分_小波能谱分析的复杂储层油水界面预测_葛新民

6.研究了西北地区某油田地表沙样的光学响应，利用单位厚度太赫兹幅值衰减系数得到了采样区域内油藏和气藏的太赫兹响应分布，以此作为该区域内有机质分布预测的依据，获得了钻井位置的分布。

该结果与已钻井位置基本符合，具有很高的准确率。

关键词：油气储层；光学新方法；光谱分析技术；油气光学Potential evaluation of oil-gas reservoir based on new opticalmethodsABSTRACTWith the development of economic soial and energy industrial, traditional oil and gas resources are becoming increasingly missing. On one hand, the potential evaluation is necessary for the petroleum that has been found, thus scientific measures will be taken to exploit the oil-gas. On the other hand, the potential evaluation is also necessary for the unknown block so that the correct theory will be used to guide exploration practice. Consequently, both practical and economic methods should be developed by the researchers to enrich the theoretical system of oil-gas exploration. Optical techniques have the characteristics of non-contact, low-cost and insensitivity to the geomagnetic and geoelectric fields. In this report, new optical methods including terahertz (THz) spectroscopy and oblique-incidence reflectivity difference (OIRD), which are rapidly developed in recent years, are employed to evaluate the oil-gas reservoir especially the unconventional reservoirs. Meanwhile, spectrum analysis methods are also developed for the sake of the optical application. The theoretical system is preliminarily formed for the optical characterization and evaluation of oil and gas.1.According to the response characteristics of oil-gas in optics, a series of spectrum methods are developed and gradually optimized which include linear regression, principal component analysis, cluster analysis, artificial neural networks, support vector machine and two-dimensional correlation spectroscopy. These methods are then applied in oil-gas detection, atmospheric pollution monitoring and urban livelihood areas. The related program and software are also finished. The basic principles and practical applications of these methods are written in a book called “The Spectrum Analysis Method of Terahertz spectroscopy” pressed by Sc ience Press.2.Carbonates and carbonate rocks are investigated by using THz spectroscopy. Results show that carbonates have different absorption features in THz range, which isthe base of reservoir evaluation. Meanwhile, for a general chemical reaction in geological evolution, the refractive indes spectra validate a common conservation relation that the average index of the reactants equal those of the products in the whole range. The results prove that atomic rearrangement process has different influence on the absorption and refractive response in THz range.3.The shape effect of micro-pore is investigated by using THz spectroscopy and relative spectrum analysis methods. The utilization of spectrum analysis methods can improve the imaging resolution from 150 μm to 20 μm. Therefore, spectrum analysis methods can extract the hidden information in the spectroscopy of optical parameters.4.THz spectroscopy is employed to investigate the absorption dynamics of water in porous active carbon. In the early diffusion stage, the optica parameters do not change; when absorption begins, THz parameters dramatically change until the end of adsorption. Consequently, THz spectroscopy can not only monitor the absorption dynamics, but also accurately determine the starting point, inflection and absorption rate in whole process.5.The surface properties of dense cores are investigated by using the OIRD technique. We discuss the dielectric distribution and observe that the shale has distinct texture or anisotropic characteristics and sandstone has isotropic properties. By the combination of optical microscope and scanning electron microscope, the micro-cracks and mineral distribution can be detected within the rocks. Therefore, OIRD is a very promising and practical technology for detecting the isotropy and anisotropy in rock and is a convenient supplementary technique for conventional methods.6.The optical response of surface sediment samples in an oil field in northwest China are studied by using THz spectroscopy. The amplitude attenuation coefficients per thickness are calculated and used for the distribution of THz resonse of oil and gas reservoirs in sampling areas. The above parameter is used as a basis to predict the distribution of organic matter, and the disbution of drilling locations is then obtained. The results are in agreement with the actual drilling and reflect high accuracy.Key Words：Oil-gas reservoir；Optical methods；Spectral analysis techniques；Oil-gas optics创新点1．油气储层的光学表征原理有别于常规测试分析方法。

基于小波包变换与近似熵的储集层识别裴小刚;陈学华;侯磊;邓吉刚【摘要】通常不同地层特征对应的地震波复杂程度均有差异.近似熵是一种反映信号复杂程度的特征量,对储层特征有一定反映.但是,地震波是有一定带宽的信号,在此带宽内,可能某一部分频段对油气层较为敏感,而其他频段的信号则对油气层的反应不够敏感,如果直接进行近似熵的计算,其结果往往不能很好地反映储层特征.鉴于这种情况,对小波包变换和近似熵结合进行储集层预测的方法进行研究,即对小波包分解的结果进行近似熵计算.实际资料计算结果表明,结合小波包分解和近似熵的储层识别方法,能够精确刻画储层形态.【期刊名称】《重庆科技学院学报（自然科学版）》【年(卷),期】2013(015)006【总页数】4页(P62-65)【关键词】小波包变换;近似熵;高频;储集层识别【作者】裴小刚;陈学华;侯磊;邓吉刚【作者单位】成都理工大学地球物理学院,成都610059;成都理工大学地球物理学院,成都610059;成都理工大学地球物理学院,成都610059;川庆地球物理勘探公司物探研究中心,成都610213【正文语种】中文【中图分类】TE19;P628地面接收到的地震波波形包含丰富的地下地质信息，通常储集层内部的非均匀性越强时，地震波就会越复杂。

因此，近年来有地球物理研究者［1－3］通过分析地震波波形的复杂性以达到储集层检测的目的，并且取得了良好的效果。

然而地震波是频带有限的信号［4］，在这个有限的频带内，部分频段信号对储层特征反映较为敏感，其他频段的信号则对储层特征的反应不够敏感［5－6］，甚至会造成干扰。

因此直接用地震道数据进行近似熵的计算，其结果可能达不到理想的储层检测效果。

对此本文对利用小波包分频的方法对地震道数据进行分解［7－8］，然后利用分解后的分量的近似熵［9］开展储集层特性检测的方法进行了研究。

考虑到小波变换只分解地震信号的低频部分，对地震信号的高频成分即细节部分不做进一步分解，因此小波变换对以低频信息为主要成分的信号能较好地描述，而不能较好地描述信号的细节信息(如较小的边缘、纹理等)。

现代电子技术Modern Electronics Technique2024年3月1日第47卷第5期Mar. 2024Vol. 47 No. 5基于改进支持向量机的致密砂岩储层参数预测研究徐颖晋1， 庞振宇2（1.东华理工大学 信息工程学院， 江西 南昌 330013；2.东华理工大学 江西省核地学数据科学与系统工程技术研究中心， 江西 南昌 330013）摘 要： 致密砂岩储层的评价技术既是油气勘探开发的重点，也是难点。

目前对致密砂岩储层的储层参数的预测与评价，依然采用传统的储层参数预测方法，结合测井曲线进行建模，用以对渗透率、孔隙度等参数进行拟合，主要运用的方法有经验公式、回归分析等，其中大部分方法都是基于线性的，无法反映致密储层特有的沉积和成岩作用所导致的非均质性强的特点，无法揭示致密储层中测井曲线与储层参数之间的复杂非线性关系。

针对此问题，提出在传统储层参数预测模型的基础上，对测井曲线与储层参数的非线性关系进行分析，挖掘更多现有测井信息，进行支持向量机储层参数预测模型的建构，并采用粒子群算法、头脑风暴算法、布谷鸟算法等三种支持向量机的改进优化算法对模型参数进行测试，筛选出最优的储层参数预测模型。

将该模型应用于研究区储层参数预测评价中，有效提高了预测评价精度，为致密储层精细预测评价和非常规油气田的高效开发提供了有力的技术保障。

关键词： 储层参数； 致密砂岩； 测井曲线； 机器学习； 支持向量机； 粒子群算法中图分类号： TN911.1⁃34 文献标识码： A 文章编号： 1004⁃373X （2024）05⁃0132⁃07Research on tight sandstone reservoir parameter predictionbased on improved support vector machineXU Yingjin 1, PANG Zhenyu 2(1. School of Information Engineering, East China University of Technology, Nanchang 330013, China;2. Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System, East China University of Technology, Nanchang 330013, China)Abstract ： The evaluation technology of tight sandstone reservoir is not only the focus but also the difficulty of oil and gas exploration and development. At present, the traditional methods are still adopted in the prediction and evaluation of reservoir parameters of tight sandstone reservoir. In these methods, the modeling is carried out in combination with the well logging curves, so as to fit parameters such as permeability and porosity. The main methods used are empirical formulas and regression analysis.Most of these methods are based on linearity, which fails to reflect the strong heterogeneity caused by the unique sedimentation and diagenesis of tight reservoirs and fails to reveal the complex nonlinear relationship between well logging curves and reservoirparameters in tight reservoirs. In view of the above, on the basis of the traditional reservoir parameter prediction model, the nonlinear relationship between well logging curves and reservoir parameters is analyzed and the existing well logging information is more fully explored to construct a reservoir parameter prediction model based on support vector machine (SVM). The modelparameters are tested with three improved optimization algorithms of SVM, including particle swarm optimization (PSO), brainstorming algorithm and cuckoo search (CS) algorithm, so as to select the optimal reservoir parameter prediction model. The model improves the accuracy of prediction and evaluation effectively when it is applied to the prediction and evaluation of the parameters of the reservoir in the study area. Therefore, the proposed model can provide strong technical support for fineprediction and evaluation of tight reservoirs and efficient development of unconventional oil and gas fields.Keyword ： reservoir parameter; tight sandstone; well logging curve; machine learning; SVM; PSO algorithmDOI ：10.16652/j.issn.1004⁃373x.2024.05.023引用格式：徐颖晋，庞振宇.基于改进支持向量机的致密砂岩储层参数预测研究[J].现代电子技术，2024，47（5）：132⁃138.收稿日期：2023⁃09⁃06 修回日期：2023⁃09⁃27基金项目：江西省核地学数据科学与系统工程技术研究中心开放基金（JETRCNGDSS202003）0 引 言近年来，随着能源需求的增长，石油勘探开发进入了一个新的高峰期，致密砂岩油气资源逐渐成为勘探开发的主战场。

基于模糊聚类分析方法的高含水期油藏层系优化作者：李小波刘威李健来源：《当代化工》2019年第11期Optimization of Reservoir System in High Water CutPeriod Based on Fuzzy Clustering AnalysisLI Xiao-bo， LIU Wei， LI Jian（China Petroleum Exploration and Development Research Institute，Beijing;100083，;China）对于我国油田而言，由于地层压力不足，因此必须采取加压采油方案，一般来说，我国大多数油田都是采用注水的方式增加地层压力[1]。

随着油田注水时间的不断增加，大多数油田已进入高含水期阶段。

高含水油田普遍具有层间干扰严重、地层剩余原油较为分散等问题，直接造成油田单位的采收率下降，原有的层系组合方式不能满足采油的需求[2，3]。

因此，十分有必要对高含水期油田进行层系优化，为提高采油效率奠定基础。

目前，国内外众多学者对层系优化问题进行了深入研究，并取得了一定的成果。

2011年，曾雪梅等[4]根据原油开发中面临的众多问题，结合影响原油采收率的相关因素和地层的层系特征，对层系进行了重新优化，使得层系与井网之间紧密结合，具有提高采收率的效果，但是该研究所考虑的地层因素不足，因此，提高采收率的效果十分有限;2012年，代兴斌等[5]对萨中油田地层内剩余油的分布情况进行了调研，根据油田井网的分布情况，提出了二次开发的层系优化方案，该研究为萨中油田的二次开发奠定了良好基础，但是该研究具有很强的针对性，所提方案对于其它油田并不适用;2014年，周羽佳等[6]对杏一区油田的地层特征进行了调研，并对层系进行了细分和优化，层间干扰得到了降低，使得开发效果得到了提高，在该研究中，所考虑的因素相对较小，同时所提方案也具有很强针对性。