变流量凝析气试井
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摘要
变流量凝析气试井方法可以得到更准确的地层信息,但永久压力计数据量大且含有大量噪音;凝析气藏存在反凝析现象,渗流规律复杂;需要拟合的参数多难度大。本文采用db4,sym4,coi2和bior1.5小波函数对实际PDG压力信号进行压缩去噪处理,对各小波函数和阀值处理方法进行比较,确定使用无偏似然估计阀值的db4小波基为最优方案;通过分析不同小波基和不同分解层数对PDG历史数据的压缩效果,认为小波基的分解层数是影响PDG数据压缩程度的主要因素,层数相同的情况下,各种小波基表现基本一致。通过反褶积方法可以从PDG数据中得到更多更准确的油藏信息,但现有的反褶积算法不适应于存在复杂形态的压力导数曲线,本文提出了基于NUAT B样条的反褶积算法,通过实例验证了NUAT B样条反褶积算法处理复杂试井曲线的优越性;围绕NUAT B样条反褶积算法,研究了数值反演和产量历史的处理方法,通过对不同油藏试井数据的应用研究,分析讨论了反褶积方法的优点和适用性条件。凝析气藏在压力降低到露点以下时会出现反凝析现象,使得凝析气藏的流体渗流特征复杂化,本文构建了非结构化混合网格进行数值模拟分析,研究了反凝析和毛细管数效应对凝析油饱和度分布的影响,并以此为基础分别建立和求解单井、干扰试井和多层数值组分试井模型,研究了各参数对井底压力动态的影响和存在多层窜流情况下井底压力动态特征,并通过实例详细分析了针对单井、干扰试井和多层凝析气试井分析解释方法。在对试井自动拟合特点、遗传算法和模拟退火算法的优缺点进行分析的基础上,提出了试井自动拟合的遗传模拟退火算法,该算法对以遗传算法为核心,使用Metropolis准则对遗传算法每一步生成的新种群进行处理,在保证种群多样性的同时提高了效率,经过实例分析证明了遗传模拟退火算法具有更强的全局和局部搜索能力,可以得到更优的平均值和标准差,并且在取得最优值所用的时间上具有很大优势。本文通过小波变换对永久压力计数据进行预处理,改进了PDG的数据预处理效果,运用反褶积方法将变流量数据转化为定流量数据,提高了反褶积的适用能力,并对单井、干扰试井和多层组分试井分析方法进行详细研究,完善了凝析气试井的分析方法,研究具有重要的学术价值和广阔的应用前景。
Condensate gas well test method of variable flow can obtain more accurate stratigraphic information; however, PDG data is large and contains lots of noise; condensate gas reservoir shows retrograde condensation phenomenon; PDG data is difficult to fit and need more data. The paper carried out denoising processing on actual PDG data using db4, sym4, coi2, bior1.5 wavelet functions, certained db4 wavelet with unbiased likelihood threshold is the best plan though comparison of each wavelet functions and threshold.methods. The paper found that decomposition levels of wavelet function is the main factor affects the compress level of PDG data though analyzing of different wavelet functions and different decomposition levels on compress PDG history data. Although deconvolution method can obtain more information from PDG data, the existed deconvolution algorithms aren’t adapted to pressure derivative curves with complex shape. To cure this problem, the paper proposed deconvolution algorithm based on NUAT B-spline, and experiments demonstrate the advantages of NUAT B-spline deconvolution algorithm adapted to complex well test curves; around NUAT B-spline deconvolution algorithm, the paper studied numerical inversion methods and methods to deal with production history, analyzed and discussed advantages and applicability conditions of deconvolution algorithm though application research of different reservoir data. When the bottomhole pressure reduced to below the dew point condensate gas well will appear condensate clogging phenomenon, which makes fluid flow characteristics of condensate gas reservoir occurs complex changes. The paper constructed unstructured hybrid grid for numerical simulation, and studied the influence of condensate plug and capillary number effect on condensate saturation distribution. As a basis, the paper further built and solved single well, interference well testing and multi-layer numerical component models, studied the influence of various parameters on the bottom hole pressure dynamic and bottom hole pressure dynamic characteristics under multi-channeling case, analyzed well test interpretation methods focused on single layer and multi-layer condensate gas models. The paper analyzed advantages and disadvantages of well test automatic matching features, genetic algorithms and simulated annealing algorithm. On this basis the paper proposed genetic simulated annealing algorithm for well test automatic matching. This algorithm makes up for the disadvantages of using genetic algorithms and simulated annealing algorithm been used separately. And many examples proved that genetic simulated annealing algorithm has greater global and local search abilities, and can obtain better average value and standard deviation, and has great advantage at the time consuming to obtain the optimal value. The study of condensate gas well test of variable flow improved pre-processing effect of PDG data, enhanced the application ability of deconvolution algorithm, completed analysis methods of condensate gas well test. This research has significant scientific and academic values and has a broad application prospect.
Condensate gas well test method of variable flow can obtain more accurate stratigraphic information; however, PDG data is large and contains lots of noise; condensate gas reservoir shows retrograde condensation phenomenon; PDG data is difficult to fit and need more data. The paper carried out denoising processing on actual PDG data using db4, sym4, coi2, bior1.5 wavelet functions, certained db4 wavelet with unbiased likelihood threshold is the best plan though comparison of each wavelet functions and threshold.methods. The paper found that decomposition levels of wavelet function is the main factor affects the compress level of PDG data though analyzing of different wavelet functions and different decomposition levels on compress PDG history data. Although deconvolution method can obtain more information from PDG data, the existed deconvolution algorithms aren’t adapted to pressure derivative curves with complex shape. To cure this problem, the paper proposed deconvolution algorithm based on NUAT B-spline, and experiments demonstrate the advantages of NUAT B-spline deconvolution algorithm adapted to complex well test curves; around NUAT B-spline deconvolution algorithm, the paper studied numerical inversion methods and methods to deal with production history, analyzed and discussed advantages and applicability conditions of deconvolution algorithm though application research of different reservoir data. When the bottomhole pressure reduced to below the dew point condensate gas well will appear condensate clogging phenomenon, which makes fluid flow characteristics of condensate gas reservoir occurs complex changes. The paper constructed unstructured hybrid grid for numerical simulation, and studied the influence of condensate plug and capillary number effect on condensate saturation distribution. As a basis, the paper further built and solved single well, interference well testing and multi-layer numerical component models, studied the influence of various parameters on the bottom hole pressure dynamic and bottom hole pressure dynamic characteristics under multi-channeling case, analyzed well test interpretation methods focused on single layer and multi-layer condensate gas models. The paper analyzed advantages and disadvantages of well test automatic matching features, genetic algorithms and simulated annealing algorithm. On this basis the paper proposed genetic simulated annealing algorithm for well test automatic matching. This algorithm makes up for the disadvantages of using genetic algorithms and simulated annealing algorithm been used separately. And many examples proved that genetic simulated annealing algorithm has greater global and local search abilities, and can obtain better average value and standard deviation, and has great advantage at the time consuming to obtain the optimal value. The study of condensate gas well test of variable flow improved pre-processing effect of PDG data, enhanced the application ability of deconvolution algorithm, completed analysis methods of condensate gas well test. This research has significant scientific and academic values and has a broad application prospect.
引文
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