核磁测井资料在大庆油田储层评价中的应用

核磁共振测井可以提供与矿物成分无关的孔隙度、孔隙度分布、泥质束缚水体积、毛管束缚水体积、自由流体体积和渗透率等十分丰富的地层信息。通过深入研究P 型核磁测井数据处理方法,在此基础上编制了核磁测井数据处理软件,结合相应的常规测井资料,对大庆油田实际的核磁测井资料进行了综合解释。结果表明,核磁测井数据的应用可以增强大庆油田储层流体性质评价的可靠性,修正常规测井方法在复杂储层的评价问题中的一些解释失误。     

Assessment of natural gas hydrate reservoirs at Site GMGS3-W19 in the Shenhu area,South China Sea based on various well logs

To obtain the characteristics of the gas hydrate reservoirs at GMGS3-W19, extensive geophysical logging data and cores were analyzed to assess the reservoir properties. Sediment porosities were estimated from density, neutron, and nuclear magnetic resonance (NMR) logs. Both the resistivity and NMR logs were used to calculate gas hydrate saturations, the Simandoux model was employed to eliminate the effects of high clay content determined based on the ECS and core data. The density porosity was closely in agreement with the core-derived porosity, and the neutron porosity was higher while the NMR porosity was lower than the density porosity of sediments without hydrates. The resistivity log has higher vertical resolution than the NMR log and thus is more favorable for assessing gas hydrate saturation with strong heterogeneity. For the gas hydrate reservoirs at GMGS3-W19, the porosity, gas hydrate saturation and free gas saturation was 52.7%, 42.7% and 10%, on average, respectively. The various logs provide different methods for the comprehensive evaluation of hydrate reservoir, which supports the selection of candidate site for gas hydrate production testing.©2022 China Geology Editorial Office.     

塔河油田奥陶系生物扰动型碳酸盐岩储集层特征及其孔隙度计算样本检验模型

塔河油田奥陶系一间房组和鹰山组生物扰动型碳酸盐岩储集层非常发育。在岩芯观测的基础上,通过薄片显微镜观测与柱塞孔隙度、渗透率分析,对研究区生物扰动型碳酸盐岩储集层宏、微观特征和成因机制进行了研究,并基于岩芯资料和常规测井数据提出了一种新的孔隙度计算样本检验模型。结果表明:1）研究区奥陶系生物扰动储集层在岩芯上多呈不规则状或绸带状分布的含油斑块,潜穴充填物以白云石为主,储集空间主要是晶间孔。随着生物扰动指数的增加,平均孔隙度呈先增大后减少趋势,平均渗透率则一直增大;2）在早—中奥陶世的沉积过程中,（古）生物在碳酸盐沉积物表面或内部建造了大量形态各异的潜穴,生物扰动使得潜穴充填物和围岩基质在成分、结构上出现差异,这些差异伴随着其后的成岩过程逐步增大,这对储集层的储、渗能力具有重要影响;3）在总结前人测井孔隙度计算方法的基础上,将生物扰动指数引入密度测井孔隙度计算模型中,提出了一种基于岩芯资料和常规测井数据的孔隙度计算样本检测检验模型,并用岩芯柱塞测试结果验证了该孔隙度计算模型的有效性和准确性;该模型弥补了现有常规孔隙度模型的不足,其计算产生的拟岩芯数据可为下一步建立的通用生物扰动碳酸盐岩储集层孔隙度计算模型提供可靠的样本训练数据,也对这类储层的储量估算与油藏描述有一定的借鉴意义。     

普光气田礁滩相复杂孔隙类型储集层渗透率地震预测方法*

礁滩相碳酸盐岩储集层孔隙类型多样,孔—渗关系复杂,由于缺少相应的岩石物理模型,储集层渗透率地震预测一直是一个难题。作者以普光气田为例,通过分析复杂孔隙类型对储集层渗透率的控制作用及不同孔隙类型储集层在常规测井和声学测井上的响应特征,引入反映孔隙形态和连通性的 “孔构参数”表征相似孔隙度样品的岩石物理参数变化;进而建立基于孔构参数的孔隙类型判别标准和不同孔隙类型储集层孔—渗关系模型,对储集层测井渗透率进行精细解释和评价;并通过分析不同孔隙类型储集层的弹性参数与孔构参数的关系,建立起基于孔构参数的岩石物理量版;采用叠前统计学反演方法首先开展孔隙度、孔构参数的地震反演,进一步开展基于孔隙度和孔构参数的渗透率地震反演,实现了复杂孔隙类型储集层渗透率的定量预测。     

电成像测井孔隙度分析技术及其在碳酸盐岩储层产能预测中的应用

深入研究了电成像测井的测量方式,提出一种基于电成像低频分量的电阻率刻度公式,结合Archie公式并引入常规测井数据及处理成果,严格推导出一种可将电成像测井数据直接标定为孔隙度的算法。此方法省略了先作电阻率刻度再应用Archie公式等中间步骤,处理过程得以简化,并可消除Archie公式中a、b、n、S_xo、R_mf等参数以及浅侧向测井R_LLS等因素对处理结果的影响,较大程度地实现了数据的自适应性处理。在此基础上,对孔隙度频谱进行多种统计分析,开展了类似核磁的区间孔隙度分析以及类似油藏描述中渗透率评价的孔隙度径向非均质性分析,将研究成果应用于碳酸盐岩储层产能预测中,引入“孔隙贡献因子”概念,并通过测井资料和试油资料建立了“孔隙度贡献因子”与储层产油强度的定量关系。     

Intelligent methods for predicting nuclear magnetic resonance of porosity and permeability by conventional well-logs: a case study of Saharan field

In the well-log data processing, the principal advantage of the nuclear magnetic resonance (NMR) method is the measurement of fluid volume and pore size distribution without resorting to parameters such as rock resistivity. Preliminary processing of the well-log data allowed first to have the petrophysical parameters and then to evaluate the performances of the transverse relaxation time T ₂ NMR. Petrophysical parameters such as the porosity of the formation as well as the effective permeability can be estimated without having recourse the fluid type. The well-log data of five wells were completed during the construction of intelligent models in the Saharan oil field Oued Mya Basin in order to assess the reliability of the developed models. Data processing of NMR combined with conventional well data was performed by artificial intelligence. First, the support vector regression method was applied to a sandy clay reservoir with a model based on the prediction of porosity and permeability. NMR parameters estimated using intelligent systems, i.e., fuzzy logic (FL) model, back propagation neural network (BP-NN), and support vector machine, with conventional well-log data are combined with those of NMR, resulting in a good estimation of porosity and permeability. The results obtained during the processing are then compared to the FL and NN regression models performed by the regression method during the validation stage. They show that the correlation coefficients R ² estimated vary between 0.959 and 0.964, corresponding to the root mean square error values of 0.20 and 0.15.     

利用测井资料计算阳离子交换量Qv的方法对比

为了准确计算泥质砂岩储层的Q_v,提出了利用核磁共振测井计算Q_v的方法,通过对56块同时具有阳离子交换量和孔隙度、渗透率数据的岩心样品的分析,建立了阳离子交换量与综合物性指数的关系模型。为了解决准确而连续地计算综合物性指数的问题,提出了利用核磁共振测井横向驰豫时间几何平均值求取Swanson参数、进而利用Swanson参数获取综合物性指数的方法。同时利用核磁共振测井法、自然伽马测井相对值法、自然电位测井图版法3种计算Q_v的方法对准噶尔盆地南缘4口井资料进行了处理,并对处理结果作了对比分析。结果表明：在泥质砂岩厚层段,3种方法都可以简单而有效地计算Q_v。与岩心资料相比,核磁共振测井法计算的相对误差为13%,自然伽马测井法计算的相对误差为19%,自然电位测井法计算的相对误差为22%;在砂泥岩薄互层,用核磁共振测井法计算的Q_v比其它两种方法计算的结果更为可靠,更能反映地层的真实情况。     

High-resolution facies and porosity models of the upper Jurassic Arab-D carbonate reservoir using an outcrop analogue, central Saudi Arabia

Subsurface models of hydrocarbon reservoirs are coarse and of low resolution when compared with the actual geologic characteristics. Therefore, the understanding of the three-dimensional architecture of reservoir units is often incomplete. Outcrop analogues are commonly used to understand the spatial continuity of reservoir units. In this study, a Late Jurassic outcrop analogue for the Arab-D reservoir of central Saudi Arabia was used to build a high-resolution model that captures fine geologic details. Subsurface reservoir lithofacies were matched with those from the studied outcrop, and porosity values derived from published core and well log data from the Ain Dar, Uthmanyah, and Shudgum areas of the Ghawar Field, eastern Saudi Arabia, were then applied to the equivalent lithofacies in the outcrop. Maximum, minimum, and average subsurface porosity for each lithofacies were distributed in the facies model using a geostatistical algorithm to produce nine porosity models for the field data. Several realisations were run to visualise the variability in each model and to quantitatively measure the uncertainty associated with the models. The results indicated that potential reservoir zones were associated with grainstone, packstone, and some wackestone layers. Semivariogram analysis of the lithofacies showed good continuity in the N-S direction and less continuity in the E-W direction. The high-resolution lithofacies models detected permeability barriers and isolated low porosity bodies within the potential reservoir zones. This model revealed the porosity distribution in areas smaller than one cell in the subsurface model and highlighted the uncertainty associated with several aspects of the model.     

低渗储层可动流体核磁共振研究

以低磁场核磁共振岩心分析技术为主,辅助以岩石薄片、环境电镜扫描、高分辨率CT、成像测井等常规测试手段,对国内3种不同岩性的典型低渗储层共计277块基质岩样进行可动流体评价研究,分析储层可动流体分布规律和影响因素,计算可动流体的T₂截止值和孔喉半径下限值。研究表明：低渗储层可动流体参数变化范围较宽;岩样渗透率越高,其与可动流体参数的相关性越强;低渗透砂岩储层可动流体百分数与孔隙度、渗透率之间相关性均较好,利用非线性最优化方法得到的计算值与实测值吻合很好;微裂缝的发育程度、孔径分布、粘土矿物含量及其充填程度等微观孔隙结构特征是低渗储层可动流体的主要影响因素。     

基于地质统计学的地震反演冲积扇相研究——以新疆C油藏为例

新疆C油藏属于开发早期区块,井资料少、井距较大,采用地震反演等数据进行沉积相研究,可提高研究精度。采用约束稀疏脉冲反演和地质统计学反演两种方法进行地震反演研究,前者受到地震分辨率的限制,纵向上分辨率不能够满足研究需求;而后者可提高反演纵向上的分辨率。本文采用地质统计学反演的储层厚度分布图进行沉积相分析,得到沉积相平面展布图,并总结了沉积相模式,解决了勘探阶段沉积相难以描述等问题,并取得了较好的效果。     

普光地区碳酸盐岩储层孔隙类型测井识别及孔渗关系

普光地区长兴组和飞仙关组碳酸盐岩储层孔隙度与渗透率之间没有严格通用的数学关系,导致储层渗透率计算具有很大困难.通过对该地区测井资料、常规薄片、铸体薄片和岩心物性等资料进行分析,表明碳酸盐岩孔隙类型是影响孔渗关系的主要因素.基于常规测井资料构造出对孔隙结构比较敏感的测井特征:声波时差与密度比值和深浅侧向电阻率比值,可用于对该地区碳酸盐岩孔隙类型进行识别,再针对不同的孔隙类型建立相应的孔渗关系模型,用于计算该地区储层渗透率.实例资料处理结果表明,模型计算渗透率与岩心分析渗透率符合较好,且井间规律具有一致性,基于孔隙结构建立的储层孔隙度与渗透率模型能较好地确定储层渗透率.      

新疆塔里木盆地温宿凸起区新近系薄互层储层预测方法研究与应用

针对塔里木盆地温宿凸起区新近系砂岩储层厚度薄、单砂体厚度小、砂体相变快的特点, 通过研究分析砂体储层与地震属性、测井曲线之间的关系, 采用伽玛拟声波地质统计学反演方法对研究区新近系进行储层预测, 并与常规的波阻抗反演、声波测井约束地质统计学反演方法生成的预测结果进行了对比分析。结果表明, 本文采用的方法极大地提高了预测结果的垂向分辨率, 可以有效识别出薄层砂体。该预测结果有效支撑了井位优选, 并经过了新钻井钻探证实, 实现了该区油气调查的突破。     

塔河油田12区块奥陶系裂缝分布规律研究

通过对露头、铸体薄片、岩性分析和成像测井资料观察和分析发现,塔河油田12区块奥陶系储层内缝洞发育,并且裂缝在一间房和鹰山组的储层中起了至关重要的作用,它既是地层流体的存储空间,又是连通孔洞缝的主要通道。裂缝的发育也增加了储层的非均质性。所以,精细研究裂缝的发育和分布规律,并定量地计算裂缝的相关参数对于识别奥陶系储层和对...     

Uncertainty quantification of overpressure buildup through inverse modeling of compaction processes in sedimentary basins

This study illustrates a procedure conducive to a preliminary risk analysis of overpressure development in sedimentary basins characterized by alternating depositional events of sandstone and shale layers. The approach rests on two key elements: (1) forward modeling of fluid flow and compaction, and (2) application of a model-complexity reduction technique based on a generalized polynomial chaos expansion (gPCE). The forward model considers a one-dimensional vertical compaction processes. The gPCE model is then used in an inverse modeling context to obtain efficient model parameter estimation and uncertainty quantification. The methodology is applied to two field settings considered in previous literature works, i.e. the Venture Field (Scotian Shelf, Canada) and the Navarin Basin (Bering Sea, Alaska, USA), relying on available porosity and pressure information for model calibration. It is found that the best result is obtained when porosity and pressure data are considered jointly in the model calibration procedure. Uncertainty propagation from unknown input parameters to model outputs, such as pore pressure vertical distribution, is investigated and quantified. This modeling strategy enables one to quantify the relative importance of key phenomena governing the feedback between sediment compaction and fluid flow processes and driving the buildup of fluid overpressure in stratified sedimentary basins characterized by the presence of low-permeability layers. The results here illustrated (1) allow for diagnosis of the critical role played by the parameters of quantitative formulations linking porosity and permeability in compacted shales and (2) provide an explicit and detailed quantification of the effects of their uncertainty in field settings.     

基于机器学习和测井数据的碳酸盐岩孔隙度与渗透率预测

准确预测碳酸盐岩储层孔隙度和渗透率对于碳酸盐岩油气藏储层评价具有重要意义。碳酸盐岩储层裂缝与溶孔广泛发育,基于经验公式从测井曲线预测储层孔隙度和渗透率具有较大误差。以中东某碳酸盐岩油藏为研究对象,选取914块取心井岩心,测定孔隙度与渗透率,利用随机森林（RF）、K-近邻（KNN）、支持向量机（SVM）和长短期记忆网络（LSTM）4种不同机器学习方法,通过测井数据进行孔隙度与渗透率预测,优化机器学习参数,筛选出适用于碳酸盐岩油藏的测井孔隙度与渗透率预测方法。研究结果表明：4种机器学习方法预测储层孔隙度结果差异不大,通过调整输入参数种类,可进一步提高孔隙度与渗透率预测效果,当以补偿中子（NPHI）、岩性密度（RHOB）和声波时差（DT）3种测井参数数据作为输入时,基于LSTM的储层孔隙度预测精度最高,孔隙度预测结果均方根误差（RMSE）为4.536 2;由于碳酸盐岩储层的强非均质性,基于机器学习的测井储层渗透率预测效果较差,相对而言,仅以NPHI作为机器学习输入参数时,基于RF的储层渗透率预测精度最高,渗透率预测结果的RMSE为45.882 3。     

页岩油评价的关键参数及求取方法研究

随着非常规油气勘探的进一步深入,页岩油气逐渐成为现今勘探研究的热点和难点。目前国内针对页岩油的勘探开发没有成功的案例可循,实际工作中一直沿用了国外页岩气的勘探及评价思路。通过研究指出,页岩油自身的特点决定了其勘探不能照搬国外的页岩气评价思路,将研究重点仅仅停留在有机碳含量上无法满足勘探需要,页岩油勘探的核心问题在于地层已生成的游离烃含量的评价。利用胜利油区第一口页岩密闭取芯井分析化验资料为基础,系统研究了孔隙度与单位含油体积以及含水体积之间的关系,发现了烃源岩中孔隙性越好,含油性越好的特点。利用孔隙度、含油饱和度等岩心分析数据推导出了反映泥质页岩游离烃含量的评价模型,并构建了基于实测的深侧向电阻率、孔隙度、有机质成熟度等参数的求取模型。利用页岩地层游离烃中有机碳含量和总有机碳含量对比可以直观反映地层中游离烃含量的垂向变化规律,指示页岩层段的有利油气区段。以胜利油田沾化凹陷罗家地区罗69井实验分析资料为例,对模型的参数求取及效果分析进行了阐述,构建的地层有机质成熟度模型及游离烃中有机碳含量均精度较高,在此基础上,通过游离烃有机碳含量绝对值、以及游离烃中有机碳含量与地层有机碳含量的比值实现了对页岩油地层可动油气富集带的指示,可动油气相对富集的层段即为页岩油地层的勘探目标。该思路可为目前的陆相页岩油勘探提供借鉴和参考。     

储层物性的空间结构特征分析与预测—以青海尕斯库勒油田E3^1油藏为例

储层物性受诸多地质因素的影响，经常表现出强烈的非均质性。这种非均质性在一定的空间尺度上往往具有明显的结构特点。本文以青海尕斯库勒油田E3^1油藏为例，讨论了地质统计学方法在油田储层特性空间结构特征分析与预测中的应用。采用变异函数定量描述了孔隙度和渗透率的空间分布结构特征，并在此基础上利用克立格法进行了最成插值预测。结果表明，研究区储层物性（孔隙度和渗透率）具有显著的空间结构性特点，变程一般在800－2000m之间；不同小层的储层物性具有不同的空间结构方向性。这种特征主要沉积相带空间展布的影响，各小层孔隙度和渗透率的实验半变异函数均可用具有块金效应的球状模型来拟合并进行预测。作为验证，本文还采用“多重趋势面”预测模型对储层的孔隙度和渗透率进行了预测分析。     

储层物性的空间结构特征分析与预测——以青海尕斯库勒油田E_3~1油藏为例

储层物性受诸多地质因素的影响,经常表现出强烈的非均质性。这种非均质性在一定的空间尺度上往往具有明显的结构特点。本文以青海尕斯库勒油田E_3~1油藏为例,讨论了地质统计学方法在油田储层物性空间结构特征分析与预测中的应用。采用变异函数定量描述了孔隙度和渗透率的空间分布结构特征,并在此基础上利用克立格法进行了最优插值预测。结果表明,研究区储层物性(孔隙度和渗透率)具有显著的空间结构性特点,变程一般在800～2000m之间;不同小层的储层物性具有不同的空间结构方向性。这种特征主要受沉积相带空间展布的影响,各小层孔隙度和渗透率的实验半变异函数均可用具有块金效应的球状模型来拟合并进行预测。作为验证,本文还采用“多重趋势面”预测模型对储层的孔隙度和渗透率进行了预测分析。     

沁水盆地南部TS地区煤层气储层测井评价方法

煤层气是一种自生自储于煤岩地层的非常规天然气资源,其储层测井评价内容及方法不同于常规天然气,在煤层气勘探开发过程中更关注于有关煤岩工业分析组分、基质孔隙度、裂缝渗透率及煤层含气量等一系列关键的储层参数。针对沁水盆地南部TS地区煤层气勘探目标层,分析了各种测井响应特征,采用回归分析法计算煤岩工业分析组分;针对煤层气含量影响因素众多且较为复杂的特点,结合相关地区煤岩样品实验分析结果,利用基于等温吸附实验的兰氏煤阶方程估算煤层含气量参数;通过煤岩孔隙结构的分析,采用变骨架密度的密度孔隙度计算公式求取煤岩总孔隙度,利用迭代逼近算法计算裂缝孔隙度;根据煤岩裂缝中面割理发育而端割理不甚发育的特点,以简化的单组系板状裂缝模型计算煤岩裂缝渗透率。通过对TS-A井进行实际计算,结果表明,煤岩工业分析组分和煤层含气量计算结果精度高,总孔隙度一般在5.5%左右,而裂缝孔隙度则大多小于0.5%,裂缝渗透率主要分布在0.001×10-3～10×10-3μm2之间,孔渗参数计算结果与相邻井区现有资料相符。采用测井方法可以快速、系统地对煤层气储层多种参数进行准确评价。