With the increasing number of complex well types in the development stage of oil and gas fields, it is becoming increasingly urgent to use remote detection logging while drilling (LWD) to explore the geological structures in a formation. In this paper, the feasibility and reliability of the dipole remote detection of logging while drilling are demonstrated theoretically. For this purpose, we use an asymptotic solution of elastic wave far-field displacement to derive the calculation formula for the radiation pattern and energy flux of an LWD dipole source. The effects of influencing factors, including the source frequency, formation property, drill collar size, and mud parameter, on the radiation pattern and energy flux are analyzed. The results show that the horizontally polarized shear wave (SH-wave) has a greater advantage in imaging the reflector compared with the cases of the compressive wave (P-wave) and vertically polarized shear wave (SV-wave), which indicates the dominance of the SH-wave in dipole remote detection while drilling. The optimal source excitation frequency of 2.5 kHz and inner and outer radii of the drill collar of 0.02 and 0.1 m, respectively, should be considered in the design of an LWD dipole shear wave reflection tool. However, the heavy drilling mud is not conducive to remote detection during logging while drilling. In addition, the reflection of the SH-wave for the LWD condition is simulated. Under the conditions of optimal source frequency, drill collar size, and mud parameters, the reflection of the SH-wave signal is still detected under the fast formation.

Reliable segmentation of pores and minerals from high-resolution (HR) digital rock data is the fundamental prerequisite for accurately characterizing the digital rock's physical properties. Limited by the complexity of the super-resolution (SR) issues and the user bias for segmentation, conventional SR enhancement and segmentation methods are generally brutal in satisfying the research demands. In recent years, with the introduction of deep learning technology into digital rock research, deep learning-based approaches for SR enhancement or segmentation methods have emerged and achieved significantly better effects than conventional approaches. Most deep learning-based digital rock SR enhancement and segmentation processing steps are currently separate. Still, preliminary studies have demonstrated that an end-to-end approach that integrates the two steps could achieve better performance. However, the training cost of 3D deep neural networks that can be directly applied to 3D digital rock processing is usually expensive. In contrast, 2D networks cannot be effectively applied to SR segmentation of 3D digital rocks. Here, we present an end-to-end SR segmentation framework for 3D digital rock based on a 2D multi-task joint deep neural network. The multi-task joint networks utilize a parallel architecture that integrates the SegNet for the segmentation task and the EDSR for the SR task. We also improved the loss function to address the issue of category imbalance and proposed an approach to utilize the 2D network for 3D digital rock processing. We demonstrate the effectiveness of the proposed network framework, the improved loss function, and the 3D digital rock processing strategies through ablation experiments on the high and low-resolution (LR) CT image datasets captured by imaging devices. The results show that the evaluation metrics and physical properties of the SR-segmented 2D\3D digital rocks align with the HR-segmented results (ground truth). It indicates that the proposed framework can improve the performance of digital rock SR enhancement and segmentation and that it is essential to integrate deep learning frameworks into digital rock analysis.

由于渤中19-6气田潜山裂缝性储层的储集空间多样、非均质性很强,且制约产能的主控因素认识不清,从而造成潜山裂缝性储层的产能预测困难.为了解决这一难题,综合岩心、测井、地质等资料分析了潜山裂缝性储层的特征,并基于CT扫描实验定量表征裂缝,研究裂缝微观特征,形成了以裂缝渗透率为核心的一系列裂缝参数的计算方法,建立了潜山裂缝性储层的产能预测模型,大幅提高了潜山裂缝性储层的产能预测精度.研究结果表明,潜山裂缝性储层的裂缝渗透率主要由裂缝的长度、宽度及连通性控制,与孔隙度的大小无明显关系,可以通过斯通利波反演的总渗透率与基质渗透率之差计算得到,其中基质渗透率计算的相对误差为28.50％,总渗透率计算的相对误差为15.56％;综合考虑潜山裂缝性储层的裂缝渗透率、裂缝纵向连通性和有效厚度,建立了渤中19-6气田潜山裂缝性储层的产能预测模型,其中裂缝渗透率计算结果的准确性决定了潜山裂缝性储层产能预测结果的可靠性.

Due to the complexity of lithologies and pore types, the permeability calculation of complex carbonate reservoirs has always been a difficult problem. To accurately calculate the permeability of complex carbonate reservoirs, a data mining technique is introduced. The technical process of data mining is established and divided into seven steps: data warehousing, data preprocessing, classification of reservoir types, selection of sensitive parameters, establishment of the classification model, evaluation of classification model, and application of classification model. The data-driven method can find effective knowledge that conventional reservoir evaluation methods cannot recognize and that are still contained in oil and gas data. Since the data-driven method may acquire a large amount of invalid knowledge while obtaining effective knowledge, the domain knowledge needs to be introduced to participate in the data mining process. The domain-knowledge-driven method can extract the most valuable and effective information from oil and gas data. The combination of data-driven and domain knowledge-driven methods is possible to avoid subdividing lithologies and pore types of complex carbonate reservoirs. As a result, the permeability of complex carbonate reservoirs can be accurately calculated based on the combination of data-driven and domain-knowledge-driven methods. Compared with the permeability calculation result by the previous method, the accuracy of the permeability calculation result by the data mining technique is improved by 18.39%. The combination of data-driven and domain-knowledge-driven methods can solve the difficult problem that traditional reservoir evaluation methods cannot overcome. Additionally, they can also provide new theories and techniques for reservoir evaluation. The permeability calculation result proves the feasibility and correctness of the method.

近年在中国渤海、南海海域陆续发现大中型潜山裂缝性油气田,使得潜山逐渐成为中国海上勘探开发的重要领域.潜山裂缝性储层岩石矿物组分复杂、储集空间多样、非均质性很强,从而给测井评价带来了前所未有的技术挑战.系统梳理渤海海域锦州25-1南、蓬莱9-1、渤中19-6、渤中13-2和南海东部惠州26-6等潜山油气田,从潜山裂缝性储层的岩石矿物特征、储层物性分布和储集空间结构出发,总结了潜山裂缝性储层测井评价的研究进展,主要包括石英、长石、云母等岩石矿物组分的精细解释,以不同类型渗透率为核心的储层参数计算,结合裂缝类型、密度、有效性等方面的综合评价;阐明了潜山裂缝性储层测井评价的技术难点,重点包含油、气、水层的准确识别,以裂缝宽度和裂缝延伸长度为核心的裂缝定量表征以及储层产出能力的分级预测;理清了潜山裂缝性储层测井评价的攻关对策,核心是实施测井采集—处理—解释一体化、研制—试验—应用一体化和测井—录井—测试一体化,三位一体有机结合,进行多方位、多角度、多层次地攻关研究,旨在系统地建立海上潜山裂缝性储层测井评价技术体系,从而为海上潜山裂缝性油气藏的高效勘探开发提供测井技术支撑.

复杂储层中普遍存在孔隙度相近而渗透率差异较大的现象.为了揭示其原因,采用铸体薄片、核磁共振、CT扫描成像等实验评价孔隙的连通性.连通孔隙度是渗透率的一个主要贡献参数.因此,从岩石孔隙空间的导电机理出发,以导电孔隙度为桥梁,建立连通孔隙度的计算模型,并分析十二种不同类型岩石中连通孔隙度与总孔隙度的函数关系;基于连通孔隙度的计算模型,建立普适性的核磁共振T2模型;以石灰岩储层为例,在相近孔隙度条件下,从不同类型岩石渗透率之间的差异出发,推导、建立孔隙度指数模型,得到孔隙度指数的分布范围.基于普适性的核磁共振T2模型,可将石灰岩储层渗透率预测的平均绝对误差从20.41mD降至0.83mD.该方法具有一定的理论价值和实际意义.

生产动态测井资料的应用,往往局限在直观的判断性应用,在深度挖掘生产动态测井数据的应用方面较少.以油、水两相渗流理论和物质平衡方程为基础,提出了利用时移生产动态测井资料计算剩余油饱和度的新方法;根据产水率与含水饱和度的分布范围和特征,利用不完全Beta函数进行曲线拟合,通过迭代算法找到全局最优解,得到了产水率与含水饱和度的定量转换关系式.在此基础上进一步建立了产水率与驱油效率之间的定量关系,实现了本文方法在不同储层类型水淹级别划分中的应用.实例应用结果表明,水淹级别解释符合率达到90％.本文方法可推广应用于多种储层的水淹级别判别中.

生产动态测井是油田监测的重要措施,目前对其系统性应用研究较少.以七参数生产动态测井技术为例,对该测井技术进行了简要介绍,并对其在注水油田中的应用进行了全面、系统的总结.七参数生产动态测井技术现场应用体现在以下5方面:①基于涡轮转速变化情况识别管柱状况;②通过小层产量劈分评价合采储层有效性;③通过动静态组合测井识别有效裂缝;④基于时移生产动态测井监测水淹动态;⑤基于注入剖面测井的非均质储层注入能力评价.实践表明,生产动态测井在油田动态监测中具有良好的应用效果,可为油田生产措施的制定与调整奠定基础.

渤中19-6气田潜山储层储集空间类型复杂多样,除发育粒间孔、溶蚀孔以外,裂缝十分发育,导致储层具有较强的非均质性,使得不同探井之间测试产能差异较大,因此有效评价储层裂缝的发育情况至关重要.本文利用快、慢横波速度差异计算得到地层的各向异性大小,通过电成像测井获取的裂缝密度进行标定,建立了渤中19-6气田评价近井地层裂缝发育程度的各向异性判别标准,使声波各向异性评价地层裂缝由定性发展到半定量,弥补了电成像测井质量差时难以识别裂缝的不足.在此基础上,首次将偶极横波远探测技术应用到变质岩潜山地层中探测井外数十米内的大尺度裂缝,建立了一套由近及远、纵横结合的裂缝测井评价技术体系,从而为该气田裂缝准确评价及后续高效开发提供了有力支持.

目前M油田面临含水率不断升高、产油量降低的问题,需对油田实施动态监测并进行生产措施调整.生产动态测井资料能够对油井产出层位、流体性质进行识别并计算产量,其解释结果对井筒生产状况认识和开发措施调整至关重要.由于生产动态测井曲线质量受管柱条件、施工状况、流体类型等多方面因素的影响,其解释结果的精度往往较低,影响现场决策.重点研究了复杂管柱条件下生产动态测井资料的精细解释方法,将生产动态测井所提供的产出剖面和注入剖面应用于产水层位识别、封堵作业以及注水方案制定.实际应用表明,生产动态测井在M油田动态监测、增油上产中应用效果良好.

分析复杂孔隙结构和强非均质性储层渗透率的影响因素,引入流动单元指标,耦合决策树分类模型;基于测井曲线及其衍生参数,建立适用于复杂油气储层的高精度渗透率模型;采用高精度渗透率模型精细处理某油田白垩系石灰岩储层的10口取芯井,与岩心渗透率、比采油指数进行对比.结果表明:在划分复杂油气储层纵向流动单元时,决策树分类模型及每一类流动单元中孔隙度与渗透率的函数关系均需具备较高的精度;高精度渗透率模型大幅度地改进石灰岩储层渗透率的计算精度,尤其是在渗透率大于100×10-3μm2的中高渗层;高精度渗透率模型所计算的渗透率无论是与岩心渗透率,还是与比采油指数的相关性均较好,即能更准确地表征流体在岩石孔隙与喉道中的渗流能力,证实方法的可行性和正确性.

针对无法用现有资料区分碳酸盐岩不同沉积成岩相的情况,本文采用了流动带指数(FZI)理论划分岩石类型以解释中低渗灰岩储层的测井渗透率.先从岩心标准柱样塞常规物性分析资料入手,以岩心样本为分析对象用FZI指数划分岩石类型,并拟合各类型的渗透率计算公式.再以孔隙度解释曲线等测井资料为基础,将关系式推广到非取心段,从而完成整个目的层段的渗透率测井解释.结果表明,在中东F油田白垩系Mishrif组灰岩中,该方法得到的渗透率与岩心实测渗透率之间的差异较小,在非取心段渗透率曲线的连续性好,取得了良好的解释效果.该方法能够有效解决中低渗灰岩储层的渗透率解释,对相似油田具有借鉴意义.

There are abundant carbonate reservoirs from the Cenozoic to Mesozoic era in the Middle East. Due to variation in sedimentary environment and diagenetic process of carbonate reservoirs, several porosity types coexist in carbonate reservoirs. As a result, because of the complex lithologies and pore types as well as the impact of microfractures, the pore structure is very complicated. Therefore, it is difficult to accurately calculate the reservoir parameters. In order to accurately evaluate carbonate reservoirs, based on the pore structure evaluation of carbonate reservoirs, the classification methods of carbonate reservoirs are analyzed based on capillary pressure curves and flow units. Based on the capillary pressure curves, although the carbonate reservoirs can be classified, the relationship between porosity and permeability after classification is not ideal. On the basis of the flow units, the high-precision functional relationship between porosity and permeability after classification can be established. Therefore, the carbonate reservoirs can be quantitatively evaluated based on the classification of flow units. In the dolomite reservoirs, the average absolute error of calculated permeability decreases from 15.13 to 7.44 mD. Similarly, the average absolute error of calculated permeability of limestone reservoirs is reduced from 20.33 to 7.37 mD. Only by accurately characterizing pore structures and classifying reservoir types, reservoir parameters could be calculated accurately. Therefore, characterizing pore structures and classifying reservoir types are very important to accurate evaluation of complex carbonate reservoirs in the Middle East.

In the marine sandstone reservoirs of the M oilfield the water cut is up to 98%, while the recovery factor is only 35%. Additionally, the distribution of the remaining oil is very scattered. In order to effectively assess the potential of the remaining oil, the logging evaluation of the water-flooded layers and the distribution rule of the. remaining oil are studied. Based on the log response characteristics, the water-flooded layers can be qualitatively identified. On the basis of the mercury injection experimental data of the evaluation wells, the calculation model of the initial oil saturation is built. Based on conventional logging data, the evaluation model of oil saturation is established. The difference between the initial oil saturation and the residual oil saturation can be used to quantitatively evaluate the. water-flooded layers. The evaluation result of the water-flooded layers is combined with the ratio of the water-flooded wells in the. marine sandstone reservoirs. As a result, the degree of water flooding in. the marine sandstone reservoirs can be assessed. On the basis of structural characteristics and sedimentary environments, the horizontal and vertical water-flooding rules of the different types of reservoirs are elaborated upon, and the distribution rule of the remaining oil is disclosed. The remaining oil is mainly distributed in the high parts of the structure. The remaining oil exists in the top of the reservoirs with good physical properties while the thickness of the remaining oil. ranges from 2-5 m. However, the thickness of the remaining oil of the reservoirs with poor physical properties ranges from 5-8 m. The high production of some of the drilled horizontal wells. shows that the above distribution rule of the remaining oil is accurate. In the marine sandstone reservoirs of the M oilfield, the research. on the well logging evaluation of the. water-flooded layers and the distribution rule of the. remaining oil has great practical significance to the prediction of the. distribution of the. remaining oil and the optimization of well locations.

The acoustic logs are essential in the process of seismic inversion.If there are not acoustic logs,they should be forecasted.In X oil field,most development wells have not compression and shear waves logging.Therefore,it is very difficult for looking for the remaining oil.On the basis of three methods including cluster analysis algorithms,petrophysical models and multilinear fitting,the compression wave logging is forecasted.The measurable indicators include the stability,accuracy and practicability of forecasting models.As a result,the multilinear fitting is used to forecast the compression wave logging.The relative error of forecasting model built the multilinear fitting is about 3.18％.Then,the Han formula,Greengerg-Castagna(GC) formula and Xu-White model are applied to forecasting the shear wave logging.Based on the GC formula,the accuracy of forecasting model is highest and its relative error is about 4.36％.At last,the GC formula is used to forecast the shear wave logging.It laid a solid foundation that the accurate forecast of compression and shear waves logging for the distribution prediction of remaining oil and the optimization of well location.In addition,it also has a strong practical significance.

为了准确评价岩相控制下复杂碳酸盐岩储层的饱和度,分析了J函数和Archie公式计算饱和度的原理,认识到毛管压力曲线的准确分类、胶结指数的精确计算分别是利用J函数和Archie公式去准确评价饱和度的核心问题.对于J函数,基于毛管压力曲线类型,分类建立J函数与饱和度之间的关系是不可取的;而应针对J函数的曲线类型,分类建立J函数与饱和度之间的关系;另外,可以对J函数的形式进行适当地改进,达到准确分类的目的.在分类建立饱和度评价模型之后,可以引入完备空间中对多参数进行分类的模型——决策树,来建立不同类型储层的分类模型.对于Archie公式,将多个参数的变化反映到一个参数上——视胶结指数,综合测井数据和储层参数,建立视胶结指数的计算公式,再利用Archie公式准确计算复杂碳酸盐岩储层的饱和度.J函数的改进思路、决策树分类模型的引入和视胶结指数的提出,为在特殊测井资料缺乏的情况下,利用常规测井资料和有限的岩心分析数据,准确评价岩相控制下复杂碳酸盐岩储层的饱和度奠定了一定的理论和实践基础.

近几年,在海外区块遇到了大量的孔隙型碳酸盐岩储层.由于岩性复杂,孔隙类型多样,致使其孔隙结构十分复杂,储层参数难以准确计算,油气储量难以客观评价.文中针对研究靶区这一类型的碳酸盐岩储层,首先从沉积作用和成岩作用两个方面分析了孔隙结构的影响因素,得出在不同岩性之间,孔隙类型之间的差异是造成孔隙结构存在较大差异的主要原因.而在同种岩性之间,泥质含量的增加会降低孔隙结构的品质.另外,成岩作用对颗粒粒径较大的岩石的影响更大一些.其次,讨论了储层参数的定量评价,由于不同类型孔隙的共存,导致孔隙度相似,而渗透率、饱和度等储层参数却存在较大差异.针对这一问题,指出了可以采用核磁和成像等特殊测井资料来表征不同类型孔隙的数值分布,利用三维数字化成像技术来展示不同类型孔隙的空间分布,为储层参数的准确计算和油气储量的客观评价奠定基础.

Due to complex structures and strong heterogeneity of pores, the cementation exponent (m) is no longer a constant, thus it is difficult to quantificationally evaluate the saturation of porous carbonate reservoirs. In order to solve this problem, a high-precision m model was build. Based on lithologies of loose, medium and tight sandstones, conglomerate, tuff, breccia, basalt, andesite, dacite and rhyolite, firstly, to analyse the impact on the saturation caused by changes in m and the saturation index (n), it can be found that the change of m affects the saturation largely. Secondly, on the basis of the Maxwell equation, a strong linear correlation between m and the difference in the effective porosity and conductive porosity was discovered. This correlation was found changeable and behaving in a linear, exponential, power or polynomial format, so a general expression between m and the effective porosity was deduced. A high-precision m model of Well AG-3 in a certain oilfield of Iraq was applied to dealing with the dolomite and limestone reservoirs in Well AG-3, respectively. The results were compared with those of core analysis, indicating that the high-precision m model had improved the calculation accuracy of the saturation of porous carbonate reservoirs and laid a theoretical and practical foundation for the quantitative evaluation of the saturation of complex porous reservoirs.

Due to complex structures and strong heterogeneity of pores,the cementation exponent ( m )is no longer a constant,thus itis difficult to quantificationally evaluate the saturation of porous carbonate reservoirs.In order to solve this problem,a high-precision m model was build.Based on lithologies of loose,medium and tight sandstones,conglomerate,tuff,breccia,basalt,andesite,daciteand rhyolite,firstly,to analyse the impact on the saturation caused by changes in m and the saturation index (n),it can be foundthat the change of m affects the saturation largely.Secondly,on the basis of the Maxwell equation,a strong linear correlation be-tween m and the difference in the effective porosity and conductive porosity was discovered.This correlation was found changeableand behaving in a linear,exponential,power or polynomial format,so a general expression between m and the effective porosity wasdeduced.A high-precision m model of Well AG-3 in a certain oilfield of Iraq was applied to dealing with the dolomite and limestonereservoirs in Well AG-3,respectively.The results were compared with those of core analysis,indicating that the high-precision m model had improved the calculation accuracy of the saturation of porous carbonate reservoirs and laid a theoretical and practical foun-dation for the quantitative evaluation of the saturation of complex porous reservoirs.

Based on the Archie formula,the effect of variable m and n on the saturation is analyzed,and the error formula of calculating the water saturation of reservoirs caused by the error of m and n is derived. On the basis of the loose sandstone, medium sandstone,tight sandstone,conglomerate,tuff,breccia,basalt,andesite,dacite and rhyolite,this paper first analyzes the distribution range and change amplitude of m and n. Secondly,the impact of m and n on the calculation of the water saturation of reservoirs is discussed. With regard to each lithology,the distribution range and change amplitude of m is greater than those of n. Therefore,compared with n,the effect of m on the saturation is stronger. When the error of m is ±0.2,the error in the calculation of the water saturation of reservoirs is almost all above 5%,and the maximum is even more than 30%. Meanwhile,when the error of n is ±0.2,the error in the calculation of the water saturation of reservoirs is almost all below 5%. The influence of m and n on the saturation is determined,and the error in the calculation of the water saturation of reservoirs caused by the error of m and n are calculated. It is theoretically and practically significant to the precise calculation of saturation of complex reservoirs.