埕北30太古宇裂缝性潜山油藏孔渗参数模型

为了建立裂缝性潜山油藏的孔渗参数模型，选取核磁共振测井、密度测井和声波测井资料约束Elanplus软件解释井剖面各点的总孔隙度和裂缝系统渗透率，利用井点孔渗物性与声波测井速度资料回归了声波测井速度、声波时差与孔隙度、渗透率的关系式。利用三维地震反演和相干分析得到的三维速度数据体，求取了埕北30太古宇潜山油藏孔渗物性的三维分布。在建立裂缝系统径向、主裂缝方向、次裂缝方向和垂向渗透率之间相关关系模型的基础上，结合应力场数值模拟求得的裂缝走向，预测了裂缝系统渗透率的三维空间各向异性分布，建立了裂缝性潜山油藏的孔渗参数模型。     

The Estimation of Formation Permeability in a Carbonate Reservoir Using an Artificial Neural Network

Abstract

Reservoir permeability is an important parameter that its reliable prediction is necessary for reservoir performance assessment and management. Although many empirical formulas are derived regarding permeability and porosity in sandstone reservoirs, these correlations cannot be accurately depicted in carbonate reservoir for the wells that are not cored and for which there are no welltest data. Therefore, having a framework for estimation of these parameters in reservoirs with neither coring samples nor welltest data is crucial. Rock properties are characterized by using different well logs. However, there is no specific petrophysical log for estimating rock permeability; thus, new methods need to be developed to predict permeability from well logs. One of the most powerful tools that we applied by the authors is artificial neural network (ANN), whose advantages and disadvantages have been discussed by several authors. In particular, 767 data sets were used from five wells of Bangestan reservoir in a southwestern field of Iran. Depth, Neutron (NPHI), Density (RHOB), Sonic (DT) logs, and evaluated total porosity (PHIT) from log data were used as the input data and horizontal permeability obtained by coring was as target data. Sixty percent of these data points were used for training and the remaining for predicting the permeability (i.e., validation and testing). An appropriate ANN was developed and a correlation coefficient (R) of 0.965 was obtained by comparing permeability predictions and the actual measurements. As a result, the neural science can be used effectively to estimate formation permeability from well log data.     

砂砾岩储层孔隙度和渗透率预测方法

垦西地区沙四段砂砾岩体岩块含量高,矿物多变,孔隙结构复杂,导致测井响应差异大,用传统的统计回归方法和测井解释方法计算储层孔隙度和渗透率精度很低.用基于测井相分析的参数回归法、多矿物模型测井最优化方法和BP神经网络法等方法分别计算砂砾岩孔隙度和渗透率,其目的是提高复杂岩性储层参数的解释精度,满足油藏描述和储量计算对参数精度的要求.通过与岩心分析结果对比,基于测井相分析的参数回归法较一般解释方法的解释精度高,而多矿物模型测井最优化法和BP神经网络法等非参数数学建模方法比前者的效果更好.该方法提高了现有测井信息的利用率,在垦西地区砂砾岩体应用中取得了良好的效果.     

DST测试资料在二连油田阿南油藏重复压裂设计中的研究与应用

由二连油田阿南油藏12口井的DST测试资料，应用模糊设计原理，研究了储层有效渗透率与电测渗透率、储层压力系数、电测孔隙度、含水率、上覆层压力以及最小水平主应力间的关系。该方法考虑的因素较为全面，并且在权重的确定上，巧妙地引用了灰色关联度法，克服了以往机重确定方法上的不足，使之更具量化标准。经实例验证，与油藏数值模拟得出的有效渗透率，基本吻合。     

Implementing a PSO-ANFIS model for prediction of viscosity of mixed oils

This work presents a reliable model named adaptive neuro-fuzzy inference system (ANFIS) optimized by coupled simulated annealing (PSO-ANFIS) for the prediction of viscosity of mixed oils. The model was developed based on various three and two oil sample mixture data gathered from literature covering wide range of influencing parameters. Different graphical and statistical approaches were used to evaluate the model performance in estimations of actual data. Predictions of the developed model were also compared with four well-known literature models for prediction of viscosity of mixed oils. Results show that the developed particle swarm optimization ANFIS model exhibits accurate predictions and presents reliable results compared to other literature models. The model exhibits an overall AARD% value of 2.59%.     

人工神经网络技术在油田储层物性预测中的应用――以西峰油田为例

与传统的测井资料解释和信息处理技术相比较,在对非均质性较强、物性参数级差较大的储集层物性预测中,人工神经网络技术具有极强的自适应和自学习能力,其通过很强的非线性映射,能够精确地建立储集层参数与测井响应之间的非线性模型。在论述神经网络技术基本原理的基础上,对西峰油田延安组和延长组储层的物性参数(孔隙度和渗透率等)进行了预测,取得了较理想的结果。预测结果表明:渗透率参数级差不大(<102)时,预测精度高;渗透率的变化范围较大(>103)时,对具有高渗透率储层的预测精度高,而对具有低渗透率储层的预测值相对误差较大。     

利用测井曲线的校正进行低渗透砂岩油藏描述

通过对宝饶油田低渗透储层研究，结合测井曲线的校正，再利用自己研制的ＤＵＰＯＲ油藏描述软件，得到了剩余声阻抗，剩余声阻抗比值，纵波速度，地层密度，伪横波速度，泊松比，含油饱和度，地层孔隙度等一系列关于储层参数的三维数据体。     

Reservoir heterogeneity and fracture parameter determination using electrical image logs and petrophysical data(a case study,carbonate Asmari Formation,Zagros Basin,SW Iran)

Assessment of reservoir and fracture parameters is necessary to optimize oil production, especially in heterogeneous reservoirs.Core and image logs are regarded as two of the best methods for this aim. However, due to core limitations, using image log is considered as the best method. This study aims to use electrical image logs in the carbonate Asmari Formation reservoir in Zagros Basin, SW Iran, in order to evaluate natural fractures, porosity system, permeability profile and heterogeneity index and accordingly compare the results with core and well data. The results indicated that the electrical image logs are reliable for evaluating fracture and reservoir parameters, when there is no core available for a well. Based on the results from formation micro-imager(FMI) and electrical micro-imager(EMI), Asmari was recognized as a completely fractured reservoir in studied field and the reservoir parameters are mainly controlled by fractures. Furthermore, core and image logs indicated that the secondary porosity varies from 0% to 10%. The permeability indicator indicates that zones 3 and 5 have higher permeability index. Image log permeability index shows a very reasonable permeability profile after scaling against core and modular dynamics tester mobility, mud loss and production index which vary between 1 and 1000 md. In addition,no relationship was observed between core porosity and permeability, while the permeability relied heavily on fracture aperture. Therefore, fracture aperture was considered as the most important parameter for the determination of permeability.Sudden changes were also observed at zones 1-1 and 5 in the permeability trend, due to the high fracture aperture. It can be concluded that the electrical image logs(FMI and EMI) are usable for evaluating both reservoir and fracture parameters in wells with no core data in the Zagros Basin, SW Iran.     

A New Method for Building Porosity and Permeability Models of a Fractured Granite Basement Reservoir

This paper presents the procedure and results of building porosity and permeability models for a fractured basement reservoir in offshore Vietnam by using Artificial Neural Network (ANN) method. ANN may help solve problems that conventional computing has not been successful with. Thus, ANN is a method, which could provide an accurate model for fractured basement reservoirs. Moreover, well log data combine seismic attributes to establish the property model. Well log data were used as the indicator to test the accuracy of the models. This study shows the 3D models of porosity and the permeability models.     

致密油储层常规测井系列适应性评价研究

致密油储层岩性细、物性差和非均质性强等特点,使有效储层与非储层、油层与水层、工业产层与低产层的测井响应特征差异非常小,测井对比度低。通过孔隙度测井和电阻率测井系列的适应性分析,提出了适应致密油储层的测井仪器精度要求,并在现有测井仪器精度条件下,发展了满足非均质和非线性要求的解释模型:选取自然伽马(GR)、声波时差(AC)、密度(DEN)和电阻率(Rt)四条测井曲线,采用模糊综合聚类方法建立了高精度的孔隙度和渗透率解释模型,结合核磁共振测井资料,建立了可变岩电参数饱和度修正模型,提高了储层参数解释精度。     

库车地区砂岩裂缝测井定量评价方法及应用

库车地区致密砂砾岩中普遍发育裂缝,可以利用测井资料计算裂缝宽度、裂缝孔隙度和渗透率等参数,以加深对该类储层的认识与评价。对高分辨率井壁成像测井资料进行处理和解释,确定裂缝宽度、裂缝孔隙度等参数,并采用模拟实验手段对其可靠性进行验证,以此为基础对双侧向测井响应进行校正和刻度,提出基于双侧向测井资料的裂缝宽度、裂缝孔隙度计算方法和模型,实现了在没有井壁成像测井资料的条件下定量计算与评价裂缝参数的目的。斯通利波传播特性与地层渗透性有关,从斯通利波中提取流动指数,建立渗透率模型,从而计算裂缝性砂砾岩储层总渗透率。实践表明,该方法在库车地区低孔低渗复杂储层评价中发挥了重要作用,取得良好效果。     

标准测井在砾岩储层评价中的应用——以克拉玛依油田七区砾岩储层为例

克拉玛依油田七区综合测井资料有限，在砾岩储层精细描述中，利用标准测井资料分析计算了砾岩储层物性的参数变化，利用标准测井视电阻率和岩心分析资料建立了储层岩性图版及电性标准，利用孔隙度分析资料和综合测井资料标定了标准测井自然电位减小系数及视电阻率值刻度，建立了区块标准测井储层评价及孔隙度、含油饱和度分析模型。而且标准测井分析模型孔隙度、含油饱和度平均绝对误差和相对误差均在储层描述工作允许范围内，从而解决了在缺乏综合测井资料时无法进行储层精细描述及参数标定的问题。     

陆相断陷湖盆油藏流场宏观参数变化规律及动态模型

以胜利油田河流三角洲储层为例,综合应用多学科理论以及岩心分析、测井储层评价、物理模拟和油藏数模等多种方法,研究了陆相断陷湖盆高渗透储层和中、低渗透储层在长期注水开发过程中油藏流场宏观参数变化规律,建立了特高含水期宏观参数变化规律的数学模型和预测模型,探讨了油藏流场宏观参数的变化机理。研究结果表明,油藏开发流体对储层渗透率的改造作用最大,对孔隙度的影响较小,油藏开发流体的动力地质作用是导致储层宏观参数变化的主因。     

ESTABLISHMENT OF THE GEOLOGICAL MODEL OF FRACTURED RESERVOIRS

ＥＳＴＡＢＬＩＳＨＭＥＮＴＯＦＴＨＥＧＥＯＬＯＧＩＣＡＬＭＯＤＥＬＯＦＦＲＡＣＴＵＲＥＤＲＥＳＥＲＶＯＩＲＳ￥ＭｕＬｏｎｇ－ｘｉｎ（ＲｅｓｅａｒｃｈＩｎｓｔｉｔｕｔｅｏｆＰｅｔｒｏｌｅｕｍＥｘｐｌｏｒａｔｉｏｎａｎｄＤｅｖｅｌｏｐｍｅｎｔ，ＣＮＰＣ）...     

利用测井资料研究稠油油藏注汽前后物性变化规律--以河南油田为例

针对稠油注汽前后物性参数变化的问题，主要依据大量的录井资料、岩心分析资料、各类测井资料和动态监测等资料，从测井角度开展了物性变化规律研究，建立了孔、渗地质模型及多种参数计算方法。可为稠油开采、调整方案编制、增产挖潜提供可靠的参数资料及测井依据。     

按流动单元建立测井储集层解释模型

常规测井解释以砂层组或单砂层为解释单元，忽视砂层内部不同流动单元渗流特征的差异，因此储层解释模型可靠性不高。考虑影响流体流动的微观孔隙结构特征，从修正的Kozeny-Carman方程和平均流动半径入手，利用4个储集物性参数，首先通过聚类分析，定量划分和表征大庆油田某油层的流动单元；然后通过确定流动单元内部孔隙度与渗透率的相关性，建立各流动单元孔隙度，渗透率解释模型，进而根据实验室分析结果确定岩电关系，来确定含水饱和度解释模型。将流动单元模型计算结果与岩心分析结果进行对比，证明所建立的模型准确度高。图2表3参3（王月莲摘）。     

On the value of 3D seismic amplitude data to reduce uncertainty in the forecast of reservoir production

Three-dimensional (3D) seismic data are commonly used to identify the size and shape of putative flow barriers in hydrocarbon reservoirs. It is less clear to what extent determining the spatial distribution of engineering properties (e.g., porosity, permeability, pressures, and fluid saturations) can improve predictions (i.e., improve accuracy and reduce uncertainty) of hydrocarbon recovery, given the multiple non-linear and often noisy transformations required to make a prediction. Determining the worth of seismic data in predicting dynamic fluid production is one of the goals of this paper.We have approached the problem of assessing uncertainty in production forecasts by constructing a synthetic reservoir model that exhibits much of the geometrical and petrophysical complexity encountered in clastic hydrocarbon reservoirs. This benchmark model was constructed using space-dependent, statistical relationships between petrophysical variables and seismic parameters. We numerically simulated a waterflood in the model to reproduce time-varying reservoir conditions. Subsequently, a rock physics/fluid substitution model that accounts for compaction and pressure was used to calculate elastic parameters. Pre-stack and post-stack 3D seismic amplitude data (i.e., time-domain amplitude variations of elastic responses) were simulated using local one-dimensional approximations. The seismic data were also contaminated with additive noise to replicate actual data acquisition and processing errors. We then attempted to estimate the original distribution of petrophysical properties and to forecast oil production based on limited and inaccurate spatial knowledge of the reservoir acquired from wells and 3D seismic amplitude data.We compared the multiple realizations of the various predictions against predictions with a reference model. The use of seismic amplitude data to construct static reservoir models affected production performance variables in different ways. For example, seismic amplitude data did not uniformly improve the variability of the predictions of water breakthrough time; other quantities, such as cumulative recovery after the onset of production, did exhibit an uncertainty reduction as did a global measure of recovery. We evaluate how different degrees of spatial correlation strength between seismic and petrophysical parameters may ultimately affect the ensuing uncertainty in production forecasts.Most of the predictions exhibited a bias in that there was a significant deviation between the medians of the realizations and that the value from the reference case. This bias was evidently caused by noise in the various transforms (some of which we introduced deliberately) coupled with nonlinearity. The key nonlinearities seem to be in the numerical simulation itself, specifically in the transformation from porosity to permeability, in the relative permeability relationships, and in the conservation equations themselves.     

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在油田开发中后期，利用储层的成岩和储集参数资料来划分储层的有利部位，指导油田的开发。研究中，根据岩心实验分析资料和测井资料，计算主要反映储层性能的成岩和储集参数：视压实率，视胶结率，成岩综合系数，孔隙度，渗透率，孔喉半径平均值。按照这些参数分类标准，通过计算机编程，运用模糊聚类方法将各口井的各小层共n个样本的m个参数看作m×n维空间的点，直接用样品隶属度将其分类，从而划分了成岩—储集相。模糊聚类方法很好地解决了多参数综合分类困难，快速准确地将枣南油田孔一段V油组划分了Ⅰ、Ⅱ、Ⅲ、Ⅳ、Ⅴ类成岩—储集相，其中Ⅰ类成岩—储集相为储层性能最好部位，Ⅴ类为最差部位。根据划分结果调整了油田注采井关系，解决了注不进、采不出的问题。     

S_(wi)与Φ关系及其油气层识别作用

束缚水饱和度是描述地层特性的一个重要参数。它的求取对于确定地层流体性质、分析水淹状况、估算油气田的地质储量、渗透率、含水率都有着十分重要的意义。本文以岩石导电的电阻车模型为基础,导出了利用岩石孔隙度计算束缚水饱和度的关系式,即对于给定的岩性Swi与Φ在双对数坐标下呈抛物线关系,并用实验资料进行了验证。由该关系式建立的测井解释交会图版能有效地识别低阻油层。