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为了解决一些油田实际的多维参数的复杂问题,以筛选描述储层物性关键指标为目的,基于主成分分析法理论基础,对延长油田某区块储层物性指标进行筛选,结果表明得分系数值最大,最能够代表储层物性的两个关键指标,分别为渗透率和结构特征系数。 相似文献
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油田开发技术发展到目前,储层预测已成为油田开发中的重要参考依据,而预测的准确性和精度一直是储层预测研究中的难点。本次研究主要选择了MLQ油田双一段作为目的层,应用jason技术进行精确的预测。 相似文献
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油田开发技术发展到目前,储层预测已成为油田开发中的重要参考依据,而预测的准确性和精度一直是储层预测研究中的难点.本次研究主要选择了MLQ油田双一段作为目的层,应用jason技术进行精确的预测. 相似文献
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延长青平川油田长2储层最终采收率预测分析 总被引:1,自引:1,他引:0
结合延长青平川油田构造特征及区块储层物性和实际电测结果,采用容积法计算得到长2储层地质储量为517.14×10^4t;同时,选择6种不同水驱曲线预测该储层的可采储量,分析对比并结合油田开采结果,可以预测长2储层最终采收率:经济极限含水率为95%时,最终采收率在8.16%左右,经济极限含水率为98%时,最终采收率在9.17%左右。 相似文献
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杨林波 《中国石油和化工标准与质量》2012,33(Z1)
根据吉林油田增储上产的要求,需要对生产井的产油能力进行挖潜.本文在国内外文献调研的基础上,通过对储层堵塞的类型及特点的分析,初步研制了一种实用性较强的储层结垢堵塞油藏判断预测方法.根据新木油田储层特点,应用该预测方法,通过参数确定、选井拟合,效果分析及符合率分析,得到了一些规律性的认识,为生产井的产油能力挖潜提供了有效手段. 相似文献
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随着社会经济的发展,油田的开发也得到了很好的发展,低渗透油田的开发具有很大的潜力,低渗透油田也是主要的开发对象,但是低渗透油田的物性较差,在开发过程中很容易受到损害,在受到损害后的恢复能力也很差,储层受到损害对产能影响很大,所以研究低渗透油田储层损害机理以及相应的诊断预测具有十分重要的意义。本文就低渗透油田开发过程中的储层损害诊断及预测进行一些探讨,希望对油田开发有一定的帮助,对油田开发的发展起到一定的推动作用。 相似文献
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In this work, linear and exponential weighted principal component analysis techniques based on spectral similarity were employed for the prediction of dye concentration in coloured fabrics, which had been dyed with three component dye mixtures. The matching strategy was based on the equalisation of the first three principal component coordinates of the weighted reflectance curves of the predicted and target sample in a dynamic 3D eigenvector space. The performance of the proposed algorithm was evaluated by the root mean square differences of the reflectance curves and the relative error of the concentration prediction, as well as the metamerism index. The obtained results indicated that the developed exponential weighted principal component analysis method is more accurate than the spectrophotometric method and the simple principal component analysis matching strategy. 相似文献
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研究区位于准噶尔盆地腹部的昌吉凹陷,地质条件复杂,储层非均质性强,以低孔低渗储层为主,油水层识别困难,普通的油水层识别图版不能取得理想的效果;在分析了油水识别困难的成因机理的基础上,引入主成分分析方法,以SPSS软件为平台,充分利用已有钻井、完井、试油等资料,选取能反映含油性的深、中感应电阻率;反映储层物性的声波、补偿中子和反映泥质参数的自然电位、自然伽马等测井曲线,建立油水层判别分析模型进行测井解释,与试油结果比较,效果较好。 相似文献
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Evaluating the Performance of Detergent Powder Formulations Containing Nano Alumina Using Diffuse Reflectance Infrared Spectroscopy and Pattern Recognition Techniques 下载免费PDF全文
M. Khanmohammadi H. rezaee Rudmianeh A. bagheri Garmarudi K. Ghasemi 《Journal of surfactants and detergents》2015,18(2):251-258
An analytical method has been introduced based on diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) coupled with pattern recognition techniques to determine the efficiency of various detergent powder formulations containing nano alumina. In order to reach this aim, different multivariate classification methods such as principal component analysis, hierarchical cluster analysis and linear discriminate analysis (LDA) were utilized for diffuse reflectance spectra to evaluate the classification approach. The best model was predicted by LDA, with a correct classification rate (%CC) of 93.55 %. Furthermore, sensitivity and specificity for the test set were 0.90 and 0.95, respectively. These results confirm the capability of DRIFTS coupled with chemometric techniques for estimating the performance of detergent powder formulations containing nano alumina. 相似文献
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现有的多尺度主元分析方法为监测具有多尺度特性的工业过程提供了一种有效途径,但该方法还存在以下两个问题:一是采用了重构步骤使得需要建立的监测模型数大大增加;二是采用Haar小波进行小波变换,而Haar小波不连续从而对信号特征的刻画能力比较弱,为此,本文提出了根据故障尺度特征的分布特点修改原有的多尺度主元分析的框架,去除了重构步骤并具体给出了突变故障和振荡故障的定位和跟踪方法,还提出了采用sym小波进行多尺度分析并解决了边界效应的处理和信号对齐的计算等问题,在一个标准的CSTR仿真过程中验证了所提方法的有效性。 相似文献
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底水气藏气井见水时间预测方法 总被引:1,自引:0,他引:1
基于Sobocinaki-Cornelius方法对底水油藏水锥突破时间的计算公式,通过数值模拟计算,得到了底水气藏的无因次锥高与无因次时间的相关关系式,利用该方法可以较为准确的预测底水气藏水锥突破的时间。胜利油田某气藏的计算结果表明,该方法合理可靠,对指导底水气藏的开发具有重要意义。 相似文献
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燃料乙醇行业是可再生能源的重要组成部分,但是燃料乙醇行业具有高能耗、高污染等特点,环保压力巨大。文章基于主成分分析法对调研的8家燃料乙醇企业9条生产线进行清洁生产综合评价,找到了不同指标之间的相关性和信息重叠之处,提炼出了不同燃料乙醇企业清洁生产评价中的主要控制指标,得到了主成分表达式及主成分综合评价模型,评价结果与百分制法评价结果基本一致,表明主成分分析法在燃料乙醇清洁生产中的综合评价中是一种客观科学的方法。 相似文献
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注水开发是各油田采取的主要开发方式之一,注水开发效果影响因素众多。本文主要从青海油田注水开发油田实际出发,建立了包含油藏因素、采油因素等14个方面指标的评价体系,采用专家确定权重的方法与主成分分析法相结合,建立了注水油田开发效果综合评价方法。通过实例验证,该评价方法的评价结果与实际生产状态吻合。本文所建立的注水油田开发效果综合评价方法对指导注水开发油田的生产具有实际意义。 相似文献
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《Fuel》2005,84(14-15):1986-1991
Multivariate analysis techniques, principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLSR), were employed to develop calibration and prediction models for the determination of oil yield from oil shale samples using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). Data pre-processing included the use of second-derivative spectral data. Multi-component models were constructed and were effective in predicting oil yield with accurate predictions achieved using oil shale samples other than those used in the calibration set. DRIFTS with multivariate calibration modelling is demonstrated to provide a simple and rapid method of evaluating oil yield from oil shales compared with, and potentially replacing, the traditional modified Fisher assay (MFA) method. 相似文献
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In this paper, the multivariate Laplace distribution (also called L1 distribution) is adopted to construct a robust probabilistic principal component regression model (MRPPCR-L1) under multiple operating modes. In the practical industrial chemistry process, outliers exist due to incorrect recording, disturbances, and process noises and might result in modelling distortion. To address this problem, Laplace distribution, instead of the Gaussian distribution in traditional methods, is introduced to reduce the negative influence of outliers. Moreover, probabilistic principal component regression is employed for dealing with the mixture modelling problem owing to its probabilistic property to determine the operating modes. The formulation of this approach is derived with the expectation maximum algorithm and the soft sensing model is also developed for prediction. Compared to the conventional method, a numerical example and the Tennessee Eastman process are used to demonstrate the robust modelling performance of the proposed method. 相似文献