应用三重孔隙模型评价火成岩储层

火成岩岩性特殊,储层非均质性非常严重,裂缝、孔洞发育,属于典型的多重孔隙介质储层,定量计算火成岩储层基质和裂缝的孔隙度和饱和度是评价火成岩油气层的关键。由基质、天然裂缝和非连通孔洞组成的储层可以模拟成基质和裂缝的并联导电网络,非连通孔洞和基质／裂缝的组合的串联导电网络。采用密度测井资料求取总孔隙度,用深浅双侧向电阻率计算裂缝孔隙度,采用密闭取心分析的孔隙度作为基质孔隙度。通过建立以基质、天然裂缝和非连通孔洞组成的储层的三重孔隙解释模型,找到适合于火成岩缝洞型复杂储层的饱和度方程。将三重孔隙解释模型应用于松辽盆地北部火成岩储层,计算的含水饱和度平均相对误差由16．85％降低至12．42％,精度明显提高,为火成岩储层评价、储量计算与地质建模提供了定量参数。     

基于球缝模型优化反演的裂缝储层评价新方法

裂缝型储层评价是复杂油气田评价的难题之一, 而且, 针对裂缝型储层的勘探需求也在日益增加.本文将裂缝型储层中的裂缝归纳为裂缝与孔隙两个基本类型, 然后, 叠加裂缝与孔隙, 在不同尺寸的配置关系下形成球缝模型.根据球缝模型提出孔隙结构参数的寻优方法, 结合现有的反演算法, 形成针对核磁测井回波的优化反演算法, 基于优化反演结果可获取裂缝均值宽度、孔隙半径、分选系数、峰态和其他孔隙结构参数.对比分析孔隙结构参数与储层品质因子及油气产量之间的关系, 可以发现孔隙结构参数与储层品质因子具有很好的相关性, 与储层测试产量也有良好的相关性.对比结果说明, 基于球缝模型反演的储层孔隙结构参数, 对于裂缝型储层的物性具有很好的刻画效果.因此, 本文的研究成果对于提高裂缝型储层的评价质量具有潜在的应用前景.

     

砂砾岩储层测井评价研究

砂砾岩储层岩性复杂、非均质性强,储层间非渗透性隔层类型多,储层基质孔隙度有时很低,从而使测井资料准确划分有效储层有很大的难度;砂砾岩体储层母岩类型变化大,岩石骨架参数很难确定,电阻率测量受岩石骨架、粘土含量和孔隙结构影响严重,反映储层孔隙流体性质的信息弱,使储层流体性质难以判断,油、气、干层界限的电性特征极不明显.通过核磁共振和井壁微电阻扫描成像测井,可以直观观察到岩石成分和粒径的变化,通过T2谱分布直观显示核磁测量井段的孔径分布,计算出各种类型孔隙度和渗透率参数,为砂砾岩有效划分储层和测井评价提供了可靠的依据.     

复杂岩性储层参数评价中神经网络技术的应用

在复杂岩性储层中，储层四性关系比较复杂，表现为非线性，用传统的方法已经难以解决这类问题，为此引入了目前比较流行的人工神经网络技术、在前人基础上，以SN油田9井区为例进行储层研究工作，该区非均质性比较强，经对该区364口井常规到井资料进行储层参数重新解释，并做平面展布，与实际资料吻合较好。由此表明，神经网络技术在解决非线性问题上表现出了较大的优越性，值得我们做进一步的研究工作。     

Evaluation of volcanic reservoirs with the “QAPM mineral model” using a genetic algorithm

Gas-bearing volcanic reservoirs have been found in the deep Songliao Basin, China. Choosing proper interpretation parameters for log evaluation is difficult due to complicated mineral compositions and variable mineral contents. Based on the QAPF classification scheme given by IUGS, we propose a method to determine the mineral contents of volcanic rocks using log data and a genetic algorithm. According to the QAPF scheme, minerals in volcanic rocks are divided into five groups： Q（quartz）, A （Alkaline feldspar）, P （plagioclase）, M （mafic） and F （feldspathoid）. We propose a model called QAPM including porosity for the volumetric analysis of reservoirs. The log response equations for density, apparent neutron porosity, transit time, gamma ray and volume photoelectrical cross section index were first established with the mineral parameters obtained from the Schlumberger handbook of log mineral parameters. Then the volumes of the four minerals in the matrix were calculated using the genetic algorithm （GA）. The calculated porosity, based on the interpretation parameters, can be compared with core porosity, and the rock names given in the paper based on QAPF classification according to the four mineral contents are compatible with those from the chemical analysis of the core samples.     

基于非饱和多孔隙介质BISQ模型的储层参数反演

Biot流动和喷射流动是含流体多孔隙介质中流体流动的两种重要力学机制．文中基于同时包含这两种力学机制的非饱和多孔隙BISQ模型,利用小生境遗传算法实现了储层参数(孔隙度、渗透率、含流体饱和度等)的反演．结果表明,本文方法在储层参数的反演过程中目标函数收敛快、且具有较强的抗“噪声”干扰性能,当观测噪声ε≤5%时,储层参数的反演精度很高．最后,通过实测数据的反演应用验证了该方法处理储层参数反演问题的有效性和非饱和BISQ模型的准确性．     

火成岩气藏储层预测及勘探技术——以松辽盆地长岭断陷为例

本文以松辽盆地长岭断陷达尔罕断凸带火成岩气藏预测为例,从已钻遇火成岩的钻井资料出发,结合钻井地质信息与地震资料,利用地震特殊处理技术识别火成岩.通过分析结果,研究该区的火成岩分布特征及油气成藏规律,建立判断火成岩的地球物理模式.结合本区域地质资料,预测了本区的火成岩分布,总结出适合本区火成岩构造特征的火成岩气藏识别技术,包括火成岩测井识别技术、火成岩地震剖面反射特征识别技术、火成岩地震相识别技术和地震反演技术等来预测火成岩的空间展布规律,了解火成岩与构造的关系.进而识别火成岩圈闭,总结断陷层系油气成藏组合,为在本区寻找火成岩气藏提供系统分析方法.     

基于机器学习的储层测井评价研究进展

储层测井评价的核心是数据分析和模型驱动方法的数学建模问题,将测井评价过程转化为机器学习过程,是提高储层测井评价自动化程度和评价精度的有效手段.大量实践证明,机器学习技术能够有效解决测井评价中复杂的非线性问题,目前在测井处理质量和评价精度方面均已取得了一定的突破.但如何更有效利用海量多源测井数据,在繁多的机器学习算法中找...     

致密油储层核磁共振测井响应机理研究

中国西部某盆地致密油储层孔隙结构差,而核磁共振测井T2谱宽,其复杂的核磁测井响应认识不清,且响应机理也不明确.本文基于致密油储层的特性,通过对三组岩样不同系列的实验测量,包括核磁共振、毛管压力曲线、X衍射矿物分析和润湿性实验,主要研究了碳酸盐岩矿物含量对T2谱的影响和由润湿性引起的T2弛豫机制.根据实验结果分析和讨论,明确了致密油岩石核磁共振响应的影响因素及孔隙流体的弛豫机制.综合分析认为,所述的核磁测井响应特征是由两方面因素综合作用的结果,一是水的T2信号主要取决于表面弛豫,低表面弛豫率的碳酸盐岩矿物导致水的T2信号的长弛豫分量增多;二是由于岩石亲油孔隙表面的存在且其弛豫率低于亲水孔隙表面的弛豫率,使得油的T2信号由表面弛豫和体弛豫贡献.     

一种基于遗传算法的测井曲线高分辨率处理方法

测井曲线高分辨率处理是提高薄层测井解释精度的一条重要途径.在纵向分辨率匹配技术基础上,利用遗传算法进行测井曲线分辨率处理：先由遗传算法在频率域确定滤波器,然后使用分辨率匹配技术提高测井曲线分辨率.利用该方法对中原油田和新疆塔河油田多口井的八侧向、深感应、自然伽马等多种方法的测井数据进行处理,测井曲线的分辨率得到明显提高,使得其更加适合薄层高分辨率处理解释的需要.     

Predicting rainfall intensity using a genetic algorithm approach

A genetic algorithm rainfall intensity (GARI) model has been developed and used to predict the intensities for given return period. It is a one‐step solution procedure that may not require any mathematical transformation. The problem formulation is given and the genetic algorithm solution of the problem is presented. The results show that the proposed GARI model can be used to solve the rainfall intensity–duration–frequency relations with lowest mean‐squared error between measured and predicted intensities. Predicted intensities are in good agreement between measured and predicted values for given return periods. Copyright © 2006 John Wiley & Sons, Ltd.     

Estimation of water cloud model vegetation parameters using a genetic algorithm

Abstract

The water cloud model is used to account for the effect of vegetation water content on radar backscatter data. The model generally comprises two parameters that characterize the vegetated terrain, A and B, and two bare soil parameters, C and D. In the present study, parameters A and B were estimated using a genetic algorithm (GA) optimization technique and compared with estimates obtained by the sequential unconstrained minimization technique (SUMT) from measured backscatter data. The parameter estimation was formulated as a least squares optimization problem by minimizing the deviations between the backscatter coefficients retrieved from the ENVISAT ASAR image and those predicted by the water cloud model. The bias induced by three different objective functions was statistically analysed by generating synthetic backscatter data. It was observed that, when the backscatter coefficient data contain no errors, the objective functions do not induce any bias in the parameter estimation and the true parameters are uniquely identified. However, in the presence of noise, these objective functions induce bias in the parameter estimates. For the cases considered, the objective function based on the sum of squares of normalized deviations with respect to the computed backscatter coefficient resulted in the best possible estimates. A comparison of the GA technique with the SUMT was undertaken in estimating the water cloud model parameters. For the case considered, the GA technique performed better than the SUMT in parameter estimation, where the root mean squared error obtained from the GA was about half of that obtained by the SUMT.

Editor D. Koutsoyiannis; Associate editor L. See

Citation Kumar, K., Hari Prasad, K.S. and Arora, M.K., 2012. Estimation of water cloud model vegetation parameters using a genetic algorithm. Hydrological Sciences Journal, 57 (4), 776–789.     

Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments

ABSTRACT

Climate patterns, including rainfall prediction, is one of the most complex problems for hydrologist. It is inherited by its natural and stochastic phenomena. In this study, a new approach for rainfall time series forecasting is introduced based on the integration of three stochastic modelling methods, including the seasonal differencing, seasonal standardization and spectral analysis, associated with the genetic algorithm (GA). This approach is specially tailored to eradicate the periodic pattern effects notable on the rainfall time series stationarity behaviour. Two different climates are selected to evaluate the proposed methodology, in tropical and semi-arid regions (Malaysia and Iraq). The results show that the predictive model registered an acceptable result for the forecasting of rainfall for both the investigated regions. The attained determination coefficient (R²) for the investigated stations was approx. 0.91, 0.90 and 0.089 for Mosul, Baghdad and Basrah (Iraq), and 0.80, 0.87 and 0.94 for Selangor, Negeri Sembilan and Johor (Malaysia).     

基于VSP直达波资料的粘弹介质参数遗传算法反演

粘弹性参数变得越来越重要,其反演算法也逐渐成为众多研究者的研究热点。而遗传算法是一种随机、自适应、启发式的算法, 具有很好的鲁棒性和全局收敛性, 本文基于VSP直达波方程,引入了遗传算法来进行粘弹参数反演, 首先将频率域直达波方程表示为复速度的函数,然后通过遗传算法反演出复速度。而复速度和品质因子又是复速度的函数,从而便可很容易的得出。但若直接反演复速度, 反演参数太多, 不容易实现, 所以又将复速度表示成参数C0和C∞的函数,以减少反演参数数量。最后给出了理论模型实验,以证明该算法的有效性。     

Multi‐level design model and genetic algorithm for structural control system optimization

The integrated optimum problem of structures subjected to strong earthquakes and wind excitations, optimizing the number of actuators, the configuration of actuators and the control algorithms simultaneously, is studied. Two control algorithms, optimal control and acceleration feedback control, are used as the control algorithms. A multi‐level optimization model is proposed with respect to the solution procedure of the optimum problem. The characteristics of the model are analysed, and the formulation of each suboptimization problem at each level is presented. To solve the multi‐level optimization problem, a multi‐level genetic algorithm (MLGA) is proposed. The proposed model and MLGA are used to solve two multi‐level optimization problems in which the optimization of the number of actuators, the positions of actuators and the control algorithm are considered in different levels. In problem 1, an example structure is excited by strong wind, and in problem 2, an example structure is subjected to strong earthquake excitation. Copyright © 2001 John Wiley & Sons, Ltd.     

长岭地区火山岩储层流体性质测井预测

火山岩储层非均质性强,其岩石的矿物成分复杂,裂缝、溶蚀孔的类型、组合分布有极强的各向异性,这给火山岩储层流体性质预测造成很大困难.本文通过运用偶极横波资料和三重孔隙解释模型对长岭地区火山岩储层流体性质进行了预测,并取得了较好的效果.说明可以应用这些方法对火山岩储层流体性质进行预测.     

松辽盆地白垩系营城组隐伏火山机构物理模型和地震识别

将火山机构分为火山口-近火山口相 (CNCF)、近源相 (PF)和远源相 (DF)三个相带.露头揭示这三个相带的倾角范围为：CNCF-40～70°,PF-25～45°,DF-20～35°.这三个相带的裂缝线密度为：CNCF-10～30条/m,PF-3～25条/m,DF-2～11条/m.这三个相带的相干值的关系为：CNCF相似文献   

加速遗传算法在预应力连续箱梁桥有限元模型修正中的应用

针对预应力混凝土连续箱梁桥的通扬运河大桥,建立其有限元模型.基于评价模型修正效果的频率指标与振型相关系数指标、柔度矩阵指标和挠度指标,定义三个目标函数,利用环境激励的试验模态参数,通过实数编码加速遗传算法对有限元模型进行了修正.相对于基于频率指标与振型相关系数指标定义的目标函数,基于柔度矩阵指标或挠度指标定义的目标函数修正的有限元模型,能同时较准确地反映其动态和静态特性,也能实现其试验模态振型较精确的质量归一化.