An evolutionary approach is applied to solve the nonlinear well logging inverse problem. In the framework of the proposed interval inversion method, nuclear, sonic, and laterolog resistivity data measured at an arbitrary depth interval are jointly inverted, where the depth variation of porosity, water saturation, and shale volume is expanded into series using Legendre polynomials as basis functions. In the interval inversion procedure, the series expansion coefficients are estimated by using an adaptive float-encoded genetic algorithm. Since the solution of the inverse problem using traditional linear optimization tools highly depends on the selection of the initial model, a heuristic search is necessary to reduce the initial model dependence of the interval inversion procedure. The genetic inversion strategy used in interval inversion seeks the global extreme of the objective function and provides an estimate of the vertical distribution of petrophysical parameters, even starting the inversion procedure from extremely high distances from the optimum. For a faster computational process, after a couple of thousand generations, the genetic algorithm is replaced by some linear optimization steps. The added advantage of using the Marquardt algorithm is the possibility to characterize the accuracy of the series expansion coefficients and derived petrophysical properties. A Hungarian oil field example demonstrates the feasibility and stability of the improved interval inversion method. As a significance, the genetic inversion method does not require prior knowledge or strong restrictions on the values of petrophysical properties and gives highly reliable estimation results practically independent of the initial model and core information.
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共查询到17条相似文献，搜索用时 390 毫秒
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利用巴克斯—吉尔伯特反演理论实现了二度磁异常的下界面反演,针对重磁异常问题,讨论了获得稳定解的两种途径:奇异值截断法和加阻尼因子法,并以模型加以证实。 相似文献
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从目标函数的线性化出发,采用奇异值分解法求广义逆矩阵并适当加阻尼,用迭代法直接解超定方程实现改进广义逆矩阵反演。进一步从理论与实际结合上阐明改进广义逆矩阵反演法的灵活、稳定,它涵盖了多种反演方法的优点,又具有自身特点,在实际应中适应性强,并能提供一些辅助信息,可更好地评价解释结果。 相似文献
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为了进一步改进完善核磁共振T2谱反演算法,利用核磁共振正演模拟信号,研究回波间隔、原始回波采集数量、信噪比等因素对反演结果的影响,同时在不同信噪比下对最优化T2谱反演算法、奇异值分解反演算法进行比较分析。研究表明:采集弛豫信号时,回波间隔大小的设置与回波数量、组分大小相匹配,才能得到最佳的反演效果;信噪比越高反演效果越好,当信噪比大于25时反演谱与构造谱基本吻合;在反演不同信噪比理论回波数据时,最优化反演方法对信噪比要求不高,奇异值分解反演方法对信噪比要求高,而奇异值分解反演速度较快。 相似文献
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激发极化衰减谱是一系列单指数衰减的线性叠加,因此可以对衰减谱进行多指数反演,得到的弛豫时间谱可用于储层孔隙结构和渗透性评价,是一种非常有前途的技术。由于实际测井的信噪比相对较低,常规的奇异值分解方法难以获得合理的弛豫时间谱,为此,采用正则化约束,结合奇异值分解,对合成数据和实际测量的衰减谱进行反演,得到连续的弛豫时间谱;同时,讨论了弛豫时间谱的时间常数分布、正则化因子以及信噪比对反演结果的影响。研究结果表明:该方法适用于信噪比较低的实际测量结果的反演,弛豫时间常数的分布点数为32~64较为合适;随着正则化因子的增加,反演结果逐渐变得平滑,存在一个最优的正则化因子,用于获得最为合理的弛豫时间谱;在双对数图中,最优正则化因子随着信噪比的增加而线性降低,因此通过测量结果的信噪比,可以求取最优正则化因子,进而将该技术应用于实际。 相似文献
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地震波在粘弹性介质中传播的一个基本特征是能量的衰减及地震波的瞬时波形变化。从广义上说,衰减可分为两类：一类是与地震波传播特性有关的衰减|另一类是反映介质内在属性的地层本征衰减,地层的本征衰减通常用品质因子来度量。反演品质因子的方法有多种,常用的是谱模拟频谱比法。笔者的主要目的是通过模型试算来分析评价该方法在反演品质因子时对干涉和噪声的稳定性,得出有益的结论,用于指导反演计算。 相似文献
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《物探化探计算技术》2021,(1)
为提高电测深曲线反演过程的稳定性和自动性,基于广义交叉验证自适应正则化方法,给出了电测深曲线反演的全自动迭代方法。首先介绍了引入光滑约束的线性反演方程的构建方法,综合奇异值分解法与广义交叉验证自适应正则化方法求解线性反演方程,接着给出了反演过程中初始模型的构建方法和反演偏导数矩阵的差分计算方法,并采用C++语言实现了电测深一维反演算法,最后通过对模拟数据和实测数据进行反演试算,验证了反演算法的有效性 相似文献
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通过分析最佳奇异值保留个数与信噪比的关系,改进了传统的SVc反演算法,提出了一种新的实现非负约束的迭代方案.数值模拟实验和实际应用表明,改进的奇异值分解算法可以适用于低信噪比(5
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OCCAM算法在大地电磁测深资料反演中已获得了成功应用。将其引入到瑞雷波频散曲线反演中,应用权重矩阵,提高了解的纵向分辨率;应用拉格朗日乘子光滑参数改善了迭代效果并提高了解的稳定性,使其可以在解的精度和模型分辨率中取最佳折中解。实测资料试算结果表明:用OCCAM算法对低速软弱夹层瞬态瑞雷波频散曲线进行反演,不但具有稳定性好、精度高、分辨能力强的特点,而且能自动分层和反演地层参数。 相似文献
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核磁测井资料的处理与解释是核磁测井技术的关键,也是其应用的难点所在。介绍了利用奇异值分解法对回波串进行处理,求得最小二乘意义下的最优解,进一步得到关于孔隙度分布的T2谱。并利用T2分布谱对实际地层进行分析,区分油、气、水层。 相似文献
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激发极化衰减谱比极化率具有更为丰富的储层信息,与地层的孔隙结构、渗透率、地层水电阻率以及泥质含量密切相关。衰减谱是一系列单指数衰减的线性叠加,因此,可以对衰减谱进行多指数反演,得到弛豫时间谱,从而可以更好地利用激发极化衰减谱来进行储层评价。一般的非负最小二乘反演的结果振荡剧烈,与实际情况不相符。这里采用阻尼最小二乘方法,结合奇异值分解技术对泥质砂岩的激发极化衰减谱进行了多指数反演,得到了光滑连续的弛豫时间谱,弛豫时间分布点数为32点~64点较合适,算法和软件对实际的岩心具有较好的效果。 相似文献
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A Bayesian linear inversion methodology based on Gaussian mixture models and its application to geophysical inverse problems are presented in this paper. The proposed inverse method is based on a Bayesian approach under the assumptions of a Gaussian mixture random field for the prior model and a Gaussian linear likelihood function. The model for the latent discrete variable is defined to be a stationary first-order Markov chain. In this approach, a recursive exact solution to an approximation of the posterior distribution of the inverse problem is proposed. A Markov chain Monte Carlo algorithm can be used to efficiently simulate realizations from the correct posterior model. Two inversion studies based on real well log data are presented, and the main results are the posterior distributions of the reservoir properties of interest, the corresponding predictions and prediction intervals, and a set of conditional realizations. The first application is a seismic inversion study for the prediction of lithological facies, P- and S-impedance, where an improvement of 30% in the root-mean-square error of the predictions compared to the traditional Gaussian inversion is obtained. The second application is a rock physics inversion study for the prediction of lithological facies, porosity, and clay volume, where predictions slightly improve compared to the Gaussian inversion approach. 相似文献
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Zehra Yenihayat 《Mathematical Geology》1996,28(2):203-228
An iterative method for calculating the transmissivity and storage coefficient from pumping test data for a confined aquifer is presented. The method optimizes the fit between the measured and the theoretical data (computed using the Theis equation) in the leastsquare sense. Unlike the existing schemes, this method employs the Levenberg-Marquardt method and the singular value decomposition technique resulting in a stable and rapidly convergent data inversion algorithm. The inverse procedure is initialized by an automatically created starting model derived using a novel technique that operates on the timederivative of the drawdown curve. An important feature of the algorithm is that all the computations are done in logarithmic space which effectively linearizes the pmblem. The proposed method has several advantages over the conventional iterative inversion algorithms because of the linearizing parameterizations at both the forward and inverse stages of the problem. Detailed derivations of the basic equations are provided to guide the potential users as well as applications to field data to demonstrate the usefulness of the proposed algorithm. 相似文献
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广义共轭梯度算法 总被引：11，自引：1，他引：11
在地球物理反问题的求解过程中,共轭梯度(CG)法是一种经典的、很有价值的主要算法之一。本文在经典的共轭梯度标准基础上,将进一步发展,推导出了求解阻尼最小二乘(LS)解和最小绝对值偏差(LAD)意义下的迭代再加权最小平方(IRLS)解的标准算法形式,从而使得CG法的应用更具一般性。为了更好地理解GCG法的性能,文中还给出了两个例子,并将计算结果与公认的、好的求解病态问题的奇异值分解(SVD)算法的计算结果进行了比较,结果表明:GCG法亦具有很强的求解病态问题的能力,精度高,且运算速度快。此外,GCG法还具有两个显着的特点:①算法简单、编程灵活;②可以保持系数矩阵的稀疏特征。 相似文献
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BP神经网络方法在二维密度界面的反演中取得了较好的效果,但在反演三维界面时,由于模型更复杂、参数更多,BP神经网络的收敛速度和反演精度都有一定程度的下降。为了改善反演效果,本文利用遗传算法对BP神经网络的权值、阈值选择过程进行优化,获得了更好的网络模型;并将此模型应用于密度界面模型的反演中,预测误差从上百米减小到数十米,同时迭代计算步数减少了近2/3,有效减少了计算时间,反演结果更准确。利用基于遗传算法优化的BP神经网络反演了法国某地区莫霍面深度,预测相对误差仅为1.8%,取得了较好的应用效果。基于遗传算法优化的BP神经网络在密度界面的反演中具有良好的应用价值和研究前景。 相似文献
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