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Advanced Horizontal Well Correlation Method for Dynamic Update of Subsurface Layers While Geosteering 地质导向时地下层动态更新的先进水平井相关方法
Pub Date : 2021-12-15 DOI: 10.2118/204721-ms
Abdul Mohsen Al-Maskeen, Sadaqat S. Ali
A new automated approach to well correlation is presented that utilizes real-time Logging While-Drilling (LWD) data and predicted well curve to dynamically update subsurface layers during geosteering operations. The automatically created predicted log and a dynamically updated structural framework provides the foundation of the process. The predicted log is created using vertical sections of the nearby wells, which provide high confidence for determining depth and stratigraphic position of the geosteered well. The results give a better understanding of thickness variation in the horizontal part of the reservoir and maximize the reservoir contact (Sung, 2008). A new advanced methodology introduced in this study involves the creation of a dynamic structural framework model, from which horizontal well correlation is performed using real-time well logs and predicted logs that are generated from adjacent wells. The predicted logs are correlated to the LWD logs using anchor points and an interactive stretching and squeezing process that honors true stratigraphic thickness. Each new anchor point results in the creation of an additional control point that is used to build a more precise structural framework model. This new approach enables more rapid well log interpretation, increased accuracy and the ability to dynamically update the subsurface model during drilling. It also enables more efficient steering of the wellbore into the most productive zones of the reservoir. This study demonstrates how wells with over 10,000 feet of horizontal reservoir contact can be correlated in a real-time geosteering environment in a dynamic, efficient and accurate manner. The proposed process dramatically helps reduce the cost of drilling and the time it takes to dynamically regenerate accurate updated maps of the subsurface. It represents a major improvement in the understanding and modeling of complex, heterogeneous reservoirs by fostering a multi-disciplinary environment of cross-domain experts that are able to collaborate seamlessly as asset-teams. Both accuracy and efficiency gains have been realized by incorporating this methodology in the characterization of multi-stacked reservoirs.
提出了一种新的自动化井相关性方法,该方法利用实时随钻测井(LWD)数据和预测井曲线,在地质导向作业期间动态更新地下层。自动创建的预测日志和动态更新的结构框架为流程提供了基础。预测测井是利用附近井的垂直剖面生成的,这为确定地质导向井的深度和地层位置提供了高可信度。结果可以更好地了解储层水平部分的厚度变化,并最大限度地提高储层接触(Sung, 2008)。该研究引入了一种新的先进方法,即创建动态结构框架模型,利用实时测井数据和邻近井的预测测井数据进行水平井对比。利用锚点和相互作用的拉伸和挤压过程,预测的测井曲线与随钻测井曲线相关联,从而获得真实的地层厚度。每个新的锚点都会导致创建一个额外的控制点,该控制点用于构建更精确的结构框架模型。这种新方法可以更快地解释测井曲线,提高精度,并能够在钻井过程中动态更新地下模型。它还可以更有效地将井眼导向到油藏的最高产区域。该研究展示了如何在实时地质导向环境下,以动态、高效和准确的方式,对超过10,000英尺水平油藏接触层的井进行关联。该方法极大地降低了钻井成本,减少了动态生成准确更新的地下地图所需的时间。它通过培养跨领域专家的多学科环境,代表了对复杂非均质油藏的理解和建模的重大改进,这些专家能够作为资产团队进行无缝协作。通过将该方法应用于多层储层的表征,实现了精度和效率的双重提高。
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引用次数: 0
Intelligent Predictor for Polymer Viscosity to Enhance Support for EOR Processes 聚合物粘度智能预测器提高EOR工艺支持
Pub Date : 2021-12-15 DOI: 10.2118/204839-ms
Mohammad Rasheed Khan, S. Kalam, Abdul Asad, Rizwan Ahmed Khan, M. Kamal
Research into the use of polymers for enhanced oil recovery (EOR) processes has been going on for more than 6 decades and is now classified as a techno-commercially viable option. A comprehensive evaluation of the polymer's rheology is pivotal to the success of any polymer EOR process. Laboratory-based evaluation is critical to EOR success; however, it is also a time/capital consuming process. Consequently, any tool which can aid in optimizing lab tests design can bring in great value. Accordingly, in this study a novel predictive correlation for viscosity estimation of commonly used "FP 3330S" EOR polymer is presented through use of cutting-edge machine learning neural networks. Mathematical equation for polymer viscosity is developed using machine learning algorithms as a function of polymer concentration, NaCl concentration, and Ca2+ concentration. The measured input data was collected from the literature and sub-divided into training and test sets. A wide-ranging optimization was performed to select the best parameters for the neural network which includes the number of neurons, neuron layers, activation functions between multiple layers, weights, and bias. Furthermore, the Levenberg-Marquardt back-propagation algorithm was utilized to train the model. Finally, measured and estimated viscosities were compared based on error-analysis. Novel correlation is developed for the polymer that can be used in predictive mode. This established correlation can predict polymer viscosity when applied to the test dataset and outperforms other published models with average error in the range of 3-5% and coefficient of determination in excess of 0.95. Moreover, it is shown that neural networks are faster and relatively better than other machine learning algorithms explored in this study. The proposed correlation can map non-linear relationships between polymer viscosity and other rheological parameters such as molecular weight, polymer concentration, and cation concentration of polymer solution. Lastly, through machine learning validation approach, it was possible to examine feasibility of the proposed models which is not done by traditional empirical equations.
聚合物用于提高采收率(EOR)工艺的研究已经进行了60多年,现在被归类为技术和商业上可行的选择。聚合物流变性的综合评价是任何聚合物EOR工艺成功的关键。基于实验室的评估是提高采收率成功的关键;然而,这也是一个耗费时间/资本的过程。因此,任何可以帮助优化实验室测试设计的工具都可以带来巨大的价值。因此,在本研究中,通过使用尖端的机器学习神经网络,提出了一种新的预测相关性,用于估计常用的“FP 3330S”EOR聚合物的粘度。使用机器学习算法建立了聚合物粘度的数学方程,作为聚合物浓度、NaCl浓度和Ca2+浓度的函数。测量的输入数据从文献中收集,并细分为训练集和测试集。进行了广泛的优化,以选择神经网络的最佳参数,包括神经元数量、神经元层数、多层之间的激活函数、权重和偏置。利用Levenberg-Marquardt反向传播算法对模型进行训练。最后,在误差分析的基础上,对实测黏度和估算黏度进行了比较。提出了一种新的可用于预测模式的聚合物相关性。当应用于测试数据集时,这种建立的相关性可以预测聚合物粘度,并且优于其他已发表的模型,平均误差在3-5%范围内,决定系数超过0.95。此外,研究表明,神经网络比本研究中探索的其他机器学习算法更快,相对更好。所提出的相关性可以映射出聚合物粘度与其他流变性参数(如分子量、聚合物浓度和聚合物溶液阳离子浓度)之间的非线性关系。最后,通过机器学习验证方法,可以检查所提出模型的可行性,这是传统经验方程无法完成的。
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引用次数: 0
An Innovative Methodology for Estimating Rock Mechanical Properties from Weight or Volume Fractions of Mineralogy and its Application to Middle East Reservoirs 一种基于矿物重量或体积分数估算岩石力学特性的创新方法及其在中东油藏中的应用
Pub Date : 2021-12-15 DOI: 10.2118/204687-ms
U. Prasad, A. Hanif, I. McGlynn, F. Walles, A. Abouzaid, O. Hamid
The influences of mineralogy on rock mechanical properties have profound application in oil and gas exploration and production processes, including hydraulic fracturing operations. In conventional resources, the rock mechanical properties are predominantly controlled by porosity; however, in unconventional tight formations, the importance of mineralogy as a function of rock mechanical properties has not been fully investigated. In unconventional tight formations, mechanical properties are often derived from mineralogy weight fraction together with the best estimate of porosity, assumption of fluid types, the extent of pore fillings, and fluid properties. These properties are then adjusted for their volumetric fractions and subsequently calibrated with acoustics or geomechanical lab measurements. A new method is presented that utilizes mineralogy weight fractions (determined from well logs or laboratory measurements). This process uses public domain information of minerals using Voigt and Reuss averaging algorithms as upper and lower bounds, respectively. An average of these bounds (also known as Hill average) provides a representative value for these parameters. Further, based on isotropic conditions, all the elastic properties are calculated. A typical output consisting of bulk-, shear-, and Young's - modulus, together with Poisson's ratio obtained from traditional methods of volume fractions and this new method using weight fractions is discussed and analyzed along with the sensitivity and the trends for individual rock properties. Furthermore, corresponding strengths, hardness, and fracture toughness could also be estimated using well known public domain algorithms. Data from carbonate reservoirs has been discussed in this work. This method shows how to estimate grain compressibility that can be challenging to be measured in the lab for unconventional tight rock samples. In low-porosity samples, the relative influence of porosity is negligible compared to the mineralogy composition. This approach reduces several assumptions and uncertainties associated with accurate porosity determination in tight rocks as it does not require the amount of pore fluids and fluid properties in calculations. The grain-compressibility and bulk-compressibility (measured by hydrostatic tests in the laboratory on core plugs or calculated from density and cross-dipole log) are used to calculate poroelastic Biot's coefficient, as this coefficient will be used to calculate in-situ principal effective stresses (overburden, minimum horizontal, and maximum horizontal stresses), which are, together with rock properties and pore pressure, constitutes the geomechanical model. The geomechanical model is used for drilling, completions, and hydraulic fracture modeling, including wellbore stability, and reservoir integrity analyses.
矿物学对岩石力学特性的影响在包括水力压裂在内的油气勘探和生产过程中有着广泛的应用。在常规资源中,岩石力学性质主要受孔隙度控制;然而,在非常规致密地层中,矿物学作为岩石力学特性函数的重要性尚未得到充分研究。在非常规致密地层中,力学性质通常由矿物学权重分数以及对孔隙度的最佳估计、流体类型的假设、孔隙填充程度和流体性质得出。然后根据其体积分数调整这些属性,随后通过声学或地质力学实验室测量进行校准。提出了一种利用矿物学权重分数(由测井或实验室测量确定)的新方法。该过程使用矿物的公共领域信息,分别使用Voigt和Reuss平均算法作为上界和下界。这些边界的平均值(也称为希尔平均值)为这些参数提供了一个代表性值。此外,基于各向同性条件,计算了所有弹性性能。讨论和分析了由体积、剪切和杨氏模量组成的典型输出,以及由传统的体积分数法和使用重量分数的新方法得到的泊松比,以及对单个岩石性质的敏感性和趋势。此外,相应的强度、硬度和断裂韧性也可以使用已知的公共领域算法来估计。本文讨论了碳酸盐岩储层资料。该方法展示了如何估计颗粒压缩性,这在实验室测量非常规致密岩石样品时是具有挑战性的。在低孔隙度样品中,孔隙度的相对影响与矿物组成相比可以忽略不计。这种方法减少了与致密岩石中精确孔隙度测定相关的一些假设和不确定性,因为它不需要计算孔隙流体的数量和流体性质。孔隙弹性比奥氏系数的计算采用颗粒压缩性和体积压缩性(通过岩心塞的实验室流体静力试验测量或通过密度和交叉偶极子测井计算),因为该系数将用于计算原位主有效应力(覆盖层、最小水平应力和最大水平应力),这些应力与岩石性质和孔隙压力一起构成地质力学模型。地质力学模型用于钻井、完井和水力压裂建模,包括井筒稳定性和储层完整性分析。
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引用次数: 0
High Performance Computing on the Cloud Successfully Deployed for 3D Geosteering and Reservoir Mapping While Drilling 云上的高性能计算成功应用于三维地质导向和随钻储层测绘
Pub Date : 2021-12-15 DOI: 10.2118/204828-ms
D. Salim, M. Thiel, Beate Nesttun Øyen, Kong Bakti Tan, J. Denichou, Vera Krissetiawati Wibowo, Desheng Zhang, K. Harms, M. Etchebes, F. Antonsen, Maria Emilia De Oliveira
The successful drilling of horizontal wells targeting reservoir zones of interest can be challenged by uncertainties in geological interpretation, identification of structure, and properties of reservoirs and fluid distribution. Optimizing the well placement of high-angle wells in order to intercept the sweet spots is crucial for the total hydrocarbon recovery in any development field. Thus, the geosteering domain was implemented to provide in real time a reservoir mapping characterization together with directional control to achieve the key performance objectives. In the past, many innovative technologies have been introduced in geosteering discipline, among them lately the deep EM directional resistivity tool that provides 1D formation resistivity mapping while drilling. However, despite the fact of delivering a multilayer mapping of the reservoir structure up to tens of meters away from wellbore, the real-time interpretation can be limited by this type of inversion. Since it is a 1D approach, these inversions map resistive boundaries on the vertical axis and assume infinite extend in all other directions. Consequently, in a complex geological setting, 1D approximation may fall short of properly describing the reservoir structure. This communication describes how the introduction of the 2D azimuthal resistivity inversions while drilling was conducted and details the various innovations required in the domains of downhole logging while drilling (LWD) measurements transmission in addition to adaptation of inversion methodology for real-time deployment, mainly through the use of high-performance cloud computing. The final enablement was the execution of automated workflows to process and deliver these advanced inversions into an integrated 3D geomodelling software within the turnaround time of drilling operations. This novel technology provides, while drilling, a better understanding of the 3D geological environment and fluid distribution with a deep depth of investigation, as well as the required information to make support for geosteering decisions for optimal well positioning. Initial field deployments were successfully conducted in horizontal wells, and three examples are presented here. Those real cases, executed with wire-drilled-pipe or mud-pulse telemetries, demonstrated the benefits of integrating 2D azimuthal inversions into the current geosteering workflow to provide a complete 3D structural understanding of the reservoir while drilling. This communication documents in detail how such an approach led to operational efficiency improvements in the form of 3D reservoir mapping in real-time, supporting a strategic change in the original well to turn toward the sweet spot, which was located sideways from the planned trajectory.
在地质解释、储层结构识别、储层性质和流体分布等方面的不确定性,可能会对目标储层水平井的成功钻探造成挑战。在任何开发领域,优化大角度井的井位以拦截甜点对于总油气采收率都是至关重要的。因此,实施地质导向领域,提供实时储层测绘特征以及定向控制,以实现关键性能目标。过去,在地质导向领域已经引入了许多创新技术,其中包括最近的深电磁定向电阻率工具,该工具可以在钻井时提供1D地层电阻率测绘。然而,尽管可以提供距离井眼几十米的油藏结构的多层图,但这种类型的反演可能会限制实时解释。由于这是一种一维方法,这些反转在垂直轴上映射电阻边界,并在所有其他方向上假设无限延伸。因此,在复杂的地质环境中,一维近似可能无法正确描述储层结构。本文介绍了随钻二维方位角电阻率反演是如何引入的,并详细介绍了随钻井下测井(LWD)测量数据传输领域所需的各种创新,以及主要通过使用高性能云计算来适应实时部署的反演方法。最后实现的是自动化工作流程的执行,在钻井作业的周转时间内,将这些先进的反演数据传输到集成的3D地质建模软件中。这项新技术可以在钻井过程中更好地了解三维地质环境和流体分布,并提供所需的信息,为地质导向决策提供支持,以实现最佳井位。最初的现场部署在水平井中取得了成功,这里给出了三个例子。这些使用线钻管或泥浆脉冲遥测技术的实际案例表明,将2D方位反演集成到当前的地质导向工作流程中,可以在钻井时提供完整的油藏3D结构信息。该沟通文件详细记录了这种方法如何以实时3D油藏测绘的形式提高作业效率,支持对原始井进行战略调整,使其转向位于计划轨迹外侧的最佳位置。
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引用次数: 0
High-Pressure Flexible Pipe for Fracturing Fluid Delivery 压裂液输送用高压柔性管
Pub Date : 2021-12-15 DOI: 10.2118/204530-ms
Enrique Villarroel, G. Chochua, Alex Garro, A. Gnanavelu
Hydraulic fracturing is a well stimulation treatment that has been around since the 1940s, becoming more popular in recent years because of the unconventional hydraulic fracturing boom in North America. Between the 1990s and 2000s, the oil and gas industry found an effective way to extract hydrocarbons from formations that were previously uneconomical to produce. Consolidated unconventional formations such as shale and other tight rocks can now be artificially fractured to induce connectivity among the pores containing hydrocarbons, enabling them to easily flow into the wellbore for recovery at the surface. The method of fracturing unconventional reservoirs requires a large amount of surface equipment, continuously working to stimulate the multiple stages perforated along the horizontal section of the shale formation. The operations normally happen on a single or multi-wells pad with several sets of perforations fractured by using the zipper-fracturing methodology (Sierra & Mayerhofer, 2014). Compared with conventional hydraulic fracturing, the surface equipment must perform for extended pump time periods with only short stops for maintenance and replacement of damaged components. This paper addresses improvements made to the fracturing fluid delivery systems as an alternative to the fracturing iron traditionally used in fracture stimulation services. The improvement aims to enhance equipment reliability and simplify surface setup while reducing surface friction pressure during the hydraulic fracturing treatment.
水力压裂是一种增产措施,自20世纪40年代以来一直存在,近年来由于北美非常规水力压裂热潮而变得更加流行。在20世纪90年代至21世纪初,石油和天然气行业找到了一种有效的方法,从以前不经济的地层中提取碳氢化合物。固结的非常规地层,如页岩和其他致密岩石,现在可以人工压裂,以诱导含有碳氢化合物的孔隙之间的连通性,使其容易流入井筒,以便在地面采收。非常规储层的压裂方法需要大量的地面设备,连续工作以刺激页岩地层水平段的多段射孔。该作业通常在单口或多口井上进行,采用拉链压裂方法对几组射孔进行压裂(Sierra & Mayerhofer, 2014)。与传统的水力压裂相比,地面设备必须延长泵的工作时间,只有短暂的停机来维护和更换损坏的部件。本文介绍了压裂液输送系统的改进,以替代传统压裂增产服务中使用的压裂铁。该改进旨在提高设备可靠性,简化地面安装,同时降低水力压裂过程中的地面摩擦压力。
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引用次数: 0
Talent Acquisition Process Optimization Using Machine Learning in Resumes’ Ranking and Matching to Job Descriptions 在简历排序和职位描述匹配中使用机器学习优化人才获取流程
Pub Date : 2021-12-15 DOI: 10.2118/204534-ms
Mohammed Alghazal
Employers commonly use time-consuming screening tools or online matching engines that are driven by manual roles and predefined keywords, to search for potential job applicants. Such traditional techniques have not kept pace with the new digital revolution in machine learning and big data analytics. This paper presents advanced artificial intelligent solutions employed for ranking resumes and CV-to-Job Description matching. Open source resumes and job descriptions' documents were used to construct and validate the machine learning models in this paper. Documents were converted to images and processed via Google cloud using Optical Character Recognition algorithm (OCR) to extract text information from all resumes and job descriptions' documents, with more than 97% accuracy. Prior to modeling, the extracted text were processed via a series of Natural Language Processing (NLP) techniques by splitting/tokenizing common words, grouping together inflected form of words, i.e. lemmatization, and removal of stop words and punctuation marks. After text processing, resumes were trained using the unsupervised machine learning algorithm, Latent Dirichlet Allocation (LDA), for topic modeling and categorization. Given the type of resumes used, the algorithm was able to categorize them into 4 main job sectors: marketing and business, engineering, computer science/IT and health. Scores were assigned to each resume to represent the maximum LDA probability for ranking. Another more advanced deep learning algorithm, called Doc2Vec, was also used to train and match potential resumes to relevant job descriptions. In this model, resumes are represented by unique vectors that can be used to group similar documents, match and retrieve resumes related to a given job description document provided by HR. The similarity is measured between each resume and the given job description file to query the top job candidates. The model was tested against several job description files related to engineering, IT and human resources, and was able to identify the top-ranking resumes from over hundreds of trained resumes. This paper presents an innovative method for processing, categorizing and ranking resumes using advanced computational models empowered by the latest fourth industrial resolution technologies. This solution is beneficial to both job seekers and employers, providing efficient and unbiased data-driven method for finding top applicants for a given job.
雇主通常使用耗时的筛选工具或由手动角色和预定义关键字驱动的在线匹配引擎来搜索潜在的求职者。这些传统技术已经跟不上机器学习和大数据分析的新数字革命。本文提出了一种先进的人工智能解决方案,用于简历排名和简历-职位描述匹配。本文使用开源简历和职位描述文档来构建和验证机器学习模型。文档被转换成图像,并通过谷歌云使用光学字符识别算法(OCR)从所有简历和职位描述文档中提取文本信息,准确率超过97%。在建模之前,提取的文本通过一系列自然语言处理(NLP)技术进行处理,包括拆分/标记常用词,将单词的屈折形式组合在一起,即词形化,以及去除停止词和标点符号。文本处理后,使用无监督机器学习算法潜狄利克雷分配(Latent Dirichlet Allocation, LDA)对简历进行训练,用于主题建模和分类。根据所使用的简历类型,该算法能够将它们分为4个主要的工作领域:市场营销和商业、工程、计算机科学/IT和健康。给每份简历分配分数,以表示排名的最大LDA概率。另一种更先进的深度学习算法Doc2Vec也被用来训练和匹配潜在的简历和相关的职位描述。在这个模型中,简历由唯一的向量表示,可以用来对相似的文档进行分组,匹配和检索与HR提供的给定职位描述文档相关的简历。测量每份简历与给定职位描述文件之间的相似性,以查询最佳职位候选人。该模型在与工程、IT和人力资源相关的几个职位描述文件中进行了测试,并能够从数百份经过培训的简历中识别出排名靠前的简历。本文提出了一种利用最新的第四次工业分辨率技术支持的先进计算模型对简历进行处理、分类和排名的创新方法。这种解决方案对求职者和雇主都是有益的,它提供了一种高效、公正的数据驱动方法,可以为特定的工作找到最优秀的求职者。
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引用次数: 0
Borehole Seismic: Essential Contributions Over the Oilfield Lifecycle 井眼地震:对油田生命周期的重要贡献
Pub Date : 2021-12-15 DOI: 10.2118/204889-ms
Rajeev Kumar, P. Bettinelli
During the evolution of the petroleum industry, surface seismic imaging has played a critical role in reservoir characterization. In the early days, borehole seismic (BHS) was developed to complement surface seismic. However, in the last few decades, a wide range of BHS surveys has been introduced to cater to new and unique objectives over the oilfield lifecycle. In the exploration phase, vertical seismic profiling (VSP) provides critical time-depth information to bridge time indexed subsurface images to log/reservoir properties in depth. This information can be obtained using several methods like conventional wireline checkshot or zero-offset vertical seismic profiling (ZVSP), seismic while drilling (SWD) or distributed acoustic sensing (DAS) techniques. SWD is a relatively new technique to record real-time data using tool deployed in the bottomhole assembly without disturbing the drilling. It helps to improve decision making for safer drilling especially in new areas in a cost-effective manner. Recently, a breakthrough technology, distributed acoustic sensing (DAS), has been introduced, where data are recorded using a fiber-optic cable with lots of saving. ZVSP also provides several parameters like, attenuation coefficient (Q), multiples prediction, impedance, reflectivity etc., which helps with characterizing the subsurface and seismic reprocessing. In the appraisal phase, BHS applications vary from velocity model update, anisotropy estimation, well- tie to imaging VSPs. The three-component VSP data is best suited for imaging and amplitude variation with offset (AVO) due to several factors like less noise interference due to quiet downhole environment, higher frequency bandwidth, proximity to the reflector, etc. Different type of VSP surveys (offset, walkaway, walkaround etc.) were designed to fulfill objectives like imaging, AVO, Q, anisotropy, and fracture mapping. In the development phase, high-resolution images (3D VSP, walkaway, or crosswell) from BHS surveys can assist with optimizing the drilling of new wells and, hence reduce costs. it can help with landing point selection, horizontal section placement, and refining interpretation for reserve calculation. BHS offers a wide range of surveys to assist the oilfield lifecycle during the production phase. Microseismic monitoring is an industry-known service to optimize hydraulic fracturing and is the only technique that captures the induced seismicity generated by hydraulic fracturing and estimate the fracture geometry (height, width, and azimuth) and in real time. During enhanced oil recovery (EOR) projects, BHS can be useful to optimize the hydrocarbon drainage strategies by mapping the fluid movement (CO2, water, steam) using time-lapse surveys like walkaway, 3D VSP and/or crosswell. DAS has brought a new dimension to provide vital information on injection or production evaluation, leak detection, flow behind tubing, crossflow diagnosis, and cement evaluation during production phas
在石油工业的发展过程中,地面地震成像在储层表征中起着至关重要的作用。早期,井眼地震(BHS)是作为地面地震的补充而发展起来的。然而,在过去的几十年里,为了满足油田生命周期中新的和独特的目标,广泛引入了BHS调查。在勘探阶段,垂直地震剖面(VSP)提供了关键的时间-深度信息,将时间索引的地下图像与测井/储层的深度属性联系起来。这些信息可以通过几种方法获得,如传统的电缆检查或零偏移垂直地震剖面(ZVSP)、随钻地震(SWD)或分布式声波传感(DAS)技术。SWD是一项相对较新的技术,可以在不干扰钻井的情况下,使用井底钻具组合中的工具记录实时数据。它有助于提高钻井安全性的决策,特别是在新区域以经济有效的方式进行钻井。最近,一项突破性的技术——分布式声传感技术(DAS)被引入,该技术使用光纤电缆记录数据,大大节省了成本。ZVSP还提供了几个参数,如衰减系数(Q)、倍数预测、阻抗、反射率等,这有助于表征地下和地震再处理。在评价阶段,BHS的应用范围从速度模型更新、各向异性估计到成像vsp。三分量VSP数据最适合于成像和偏移振幅变化(AVO),因为有几个因素,如安静的井下环境、更高的频率带宽、靠近反射器等。设计了不同类型的VSP测量(偏移、行走、行走等),以实现成像、AVO、Q、各向异性和裂缝作图等目标。在开发阶段,BHS测量的高分辨率图像(3D VSP、walk - away或crosswell)可以帮助优化新井的钻井,从而降低成本。它可以帮助着陆点的选择、水平剖面的布置以及储量计算的精细化解释。BHS在生产阶段提供广泛的测量,以协助油田的生命周期。微地震监测是业内公认的水力压裂优化服务,也是唯一一种能够实时捕获水力压裂产生的诱发地震活动并估计裂缝几何形状(高度、宽度和方位角)的技术。在提高采收率(EOR)项目中,BHS可以通过使用walkaway、3D VSP和/或井间等延时测量来绘制流体运动(CO2、水、蒸汽),从而有助于优化油气排采策略。DAS带来了新的维度,为生产阶段的注入或生产评估、泄漏检测、油管后流、横流诊断和水泥评估提供了重要信息。本文重点介绍了BHS在油田全生命周期中的应用。
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引用次数: 0
Dissolvable Rubbers Development and its Applications in Downhole Tools 可溶橡胶的发展及其在井下工具中的应用
Pub Date : 2021-12-15 DOI: 10.2118/204622-ms
Jiaxiang Ren, Pengyu Cheng, Xu Wang
Dissolvable tools have been used more in unconventional oil and gas operations in recent years. Sealing element is one of the important parts of the dissolvable tools. The dissolvable rubbers in the market either have low strength or the dissolution rate was low. A series of high strength dissolvable rubbers with various dissolution rate have been developed by CNPC-USA to meet the industrial requirements. The mechanical properties of the dissolvable rubbers were tested at ambient and high temperatures. The dissolvable rubber coupons were soaked in water, 0.3%, 1% KCl at 80, 90 and 120 °C for various durations up to 47 days. The mass, dimensions, volume, hardness, density, and tensile properties of the samples were measured after different durations to characterize the dissolution rate. In addition, the pressure rating of dissolvable rubber sealing element was tested in water environment at 90 °C or 100 °C and in oil environment at 120 °C for 24 hours. The dissolution rate of the dissolvable rubber sealing element was tested at 90 °C or 80 °C in brine. It was found that the tensile strength of the dissolvable rubber at high temperature was in the range of 800-3000 psi and the elongation of the dissolvable rubber at high temperature was higher than 500%, which was higher than that of the most of the commercial dissolvable rubbers. For 90-120°C rated dissolvable rubbers, the dissolvable rubber coupons were disintegrated in brine at 90 °C in 5-15 days and the dissolvable rubber was completely dissolved in brine at 120°C in 4 days. The dissolvable rubber sealing elements hold 10,000 psi pressure differential at 90 °C in water and at 120 °C in oil environment for more than 24 hours. On the other hand, the dissolvable rubber sealing element were disintegrated in 90°C, 1% KCl in 7-11 days. For 80-120°C rated dissolvable rubbers, the dissolvable rubber coupons were disintegrated in brine at 80°C in 3-10 days. The dissolvable rubber sealing elements hold 8,700 psi pressure differential for 24 hours and 10,000 psi pressure differential at 100 °C for 15 minutes. On the other hand, the dissolvable rubber sealing elements were disintegrated at 80°C in 1% KCl in 3-5 days. The pressure rating properties and dissolution rate properties of the dissolvable rubber sealing elements met the field operation requirements. The dissolvable plugs with the dissolvable rubber sealing elements have been successfully used in multiple tight-oil wells and more than 15 shale gas wells fracturing operations in China. The dissolution rate of the dissolvable rubber could be controlled by adjusting the formulations. The dissolution rate of the dissolvable rubber was independent of brine concentration. CNPC-USA has developed a series of dissolvable rubbers in the temperature range from 40°C to 175°C applications to meet different operation requirements.
近年来,可溶解工具在非常规油气作业中得到了越来越多的应用。密封元件是可溶工具的重要部件之一。市场上的可溶橡胶要么强度低,要么溶出率低。为满足工业要求,中石油美国公司开发了一系列具有不同溶解速率的高强度可溶橡胶。在常温和高温条件下测试了可溶橡胶的力学性能。将可溶胶片分别在水、0.3%、1% KCl中浸泡,温度分别为80、90和120°C,最长可达47天。在不同时间后测量样品的质量、尺寸、体积、硬度、密度和拉伸性能,以表征溶解速率。此外,在90°C、100°C的水环境和120°C的油环境中,测试了可溶橡胶密封元件的耐压等级,持续24小时。在90°C和80°C的盐水中测试了可溶橡胶密封元件的溶解速率。结果表明,该可溶橡胶的高温拉伸强度在800 ~ 3000psi范围内,高温延伸率大于500%,高于大多数市售可溶橡胶。对于90-120℃等级的可溶橡胶,可溶胶片在90℃的盐水中5-15天分解,可溶橡胶在120℃的盐水中4天完全溶解。可溶解橡胶密封元件在90°C的水中和120°C的油环境中可承受10,000 psi的压差超过24小时。另一方面,可溶性橡胶密封元件在90℃、1% KCl条件下,在7 ~ 11天内发生崩解。对于80-120℃的可溶橡胶,可溶橡胶片在80℃的盐水中溶解3-10天。可溶解的橡胶密封元件在24小时内可承受8,700 psi的压差,在100°C下可承受10,000 psi的压差15分钟。另一方面,可溶性橡胶密封元件在1% KCl中于80℃下在3-5天内发生崩解。可溶橡胶密封元件的耐压性能和溶解速率性能均满足现场使用要求。具有可溶解橡胶密封元件的可溶解桥塞在中国已成功应用于多口致密油井和超过15口页岩气井的压裂作业。可溶橡胶的溶解速率可通过调整配方来控制。可溶橡胶的溶解速率与盐水浓度无关。中石油美国开发了一系列温度范围为40°C至175°C的可溶解橡胶,以满足不同的操作要求。
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引用次数: 1
Study on the Oil Displacement Effect and Application of Soft Microgel Flooding Technology 软微凝胶驱油技术驱油效果及应用研究
Pub Date : 2021-12-15 DOI: 10.2118/204764-ms
Jian Zhang, Zhe Sun, Xiujun Wang, Xiaodong Kang
Due to the reservoir heterogeneity, there is still a lot of remaining oil that cannot be displaced by water flooding. Therefore, taking the whole injection-production flow field as the research object, the dominant channel is divided into macro and micro channel. Then the corresponding oil displacement system is adopted to realize the continuous flow diversion and effective expansion of swept volume. For micro channels, the soft microgel particle dispersion can be used. It is a novel flooding system developed in recent years. Due to its excellent performance and advanced mechanism, the oil recovery rate can be greatly improved. Soft microgel particle dispersion consists of microgel particles and its carrier fluid. After coming into porous media, its unique phenomenon of particle phase separation appears, which leads to the properties of "plugging large pore and leave the small one open", and the deformation and migration characteristic in the poros media. Therefore, particle phase separation of soft microgel particle dispersion is studied by using the microfluidic technology and numerical simulation. On this basis, by adopting the NMR and 3D Printing technology, the research on its oil displacement mechanism is further carried out. Furthermore, the typical field application cases are analyzed. Results show that, soft microgel particles have good performance and transport ability in porous media. According to the core displacement experiment, this paper presents the matching coefficient between microgels and pore throat under effective plugging modes. Also, the particle phase separation happens when injecting microgels into the core, which makes the particles enter the large pore in the high permeability layer and fluid enters into small pore. Therefore, working in cooperation, this causes no damage to the low permeability layer. On this basis, theoretically guided by biofluid mechanics, the mathematical model of soft microgel particle is established to simulate its concentration distribution, which obtained the quantitative research results. Furthermore, the micro displacement experiment shows that, microgels has unique deformation and migration characteristic in the poros media, which can greatly expand swept volume. The macro displacement experiment shows that, microgels have good oil displacement performance. Finally, the soft microgel particle dispersion flooding technology has been applied in different oilfields since 2007. Results show that these field trials all obtain great oil increasing effect, with the input-output ratio range of 2.33-14.37. And two field application examples are further introduced. Through interdisciplinary innovative research methods, the oil displacement effect and field application of soft microgel particle dispersion is researched, which proves its progressiveness and superiority. The research results play an important role in promoting the application of this technology.
由于储层非均质性,仍有大量剩余油不能通过水驱驱替。因此,以整个注采流场为研究对象,将主导通道分为宏观通道和微通道。然后采用相应的驱油系统,实现连续导流和有效扩大扫气量。对于微通道,可采用软质微凝胶颗粒分散。它是近年来发展起来的一种新型驱油系统。由于其优异的性能和先进的机理,可以大大提高采收率。软微凝胶颗粒分散体由微凝胶颗粒及其载液组成。进入多孔介质后,其独特的颗粒相分离现象出现,导致其具有“大孔堵小孔开”的特性,以及在多孔介质中的变形和迁移特征。因此,采用微流控技术和数值模拟的方法对软微凝胶颗粒分散的颗粒相分离进行了研究。在此基础上,采用核磁共振和3D打印技术,进一步开展其驱油机理研究。并对典型的现场应用案例进行了分析。结果表明,软质微凝胶颗粒在多孔介质中具有良好的性能和输运能力。通过岩心驱替实验,给出了有效封堵模式下微凝胶与孔喉的匹配系数。微凝胶注入岩心发生颗粒相分离,颗粒进入高渗层的大孔隙,流体进入小孔隙。因此,在协同工作中,这不会对低渗透层造成损害。在此基础上,以生物流体力学为理论指导,建立软质微凝胶颗粒的数学模型,模拟其浓度分布,获得定量研究结果。此外,微位移实验表明,微凝胶在孔隙介质中具有独特的变形和迁移特性,可以极大地扩大扫描体积。宏观驱油实验表明,微凝胶具有良好的驱油性能。最后,自2007年以来,软微凝胶颗粒分散驱油技术在不同油田得到了应用。结果表明:现场试验均取得了较好的增产效果,投入产出比在2.33 ~ 14.37之间。并进一步介绍了两个现场应用实例。通过跨学科的创新研究方法,研究了软质微凝胶颗粒分散体的驱油效果及现场应用,证明了其先进性和优越性。研究成果对该技术的推广应用具有重要的推动作用。
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引用次数: 1
Application of Wellbore Strengthening Techniques in Carbonate Formation Solves Lost Circulation Challenges During Liner Running and Cementing 碳酸盐地层井眼强化技术的应用解决了尾管下入和固井过程中的漏失问题
Pub Date : 2021-12-15 DOI: 10.2118/204594-ms
Muneer Al Noumani, Younis Al Masoudi, M.M. Al Mamari, Yaqdhan Khalfan Al Rawahi, Mohammed Al Yaarubi, Safa Al Nabhani, I. Cameron, David Knox, Roberto Peralta, Emmanuel Thérond
For many years, the oil and gas industry has deployed techniques which enhance formation strength via the successful propping and plugging of induced fractures. Induced fracture sizes have been successfully treated using this method up to the 600 – 1,100-micron range. Static wellbore strengthening techniques are commonly deployed to cover 1,000 micron and all fracture size risks underneath. The deployment of wellbore strengthening techniques has historically been confined to permeable formations. In most cases, wellbore strengthening has been deployed to operationally challenging sand fracture gradients or, where boundaries are pushed, lower ranges of permeability, such as silts. The subject of wellbore strengthening in shales or carbonates to this day, remains a challenge for the industry, with very few documented success stories or evidence of sustained ability to enhance fracture gradient across a drilling campaign. This paper covers the history of lost circulation events which have been reported in the Khazzan/Ghazeer field in the carbonate Habshan formation. It also describes the design changes which were introduced to strengthen the rock and enable circulation/returns, during liner cementation. The design work built on experience applying wellbore strengthening techniques in carbonates in the Norwegian sector of the North Sea. This work is also summarized in this paper. The Habshan carbonate formation in Oman presents a lost circulation challenge through an ‘induced’ fracture risk. Since the beginning of the drilling campaign in the Khazzan/Ghazeer field, the Habshan formation has repeatedly experienced induced mud losses during well activities such as liner running, mud conditioning with liner on bottom and cementing, when the formation is exposed to higher pressures, less so during drilling. The Habshan challenge in Oman has led to regular, significant lost circulation events during cement placement, adding operational cost and more importantly, presenting difficulties around meeting zonal isolation objectives. Through previous field experience in Norway, a set of criteria was developed to qualify a standard pill approach to carbonate strengthening. The currently deployed strategy is designed to address both the risk of induced fracture by propping and plugging (wellbore strengthening) and provide some ability to seal natural fractures which are often encountered with carbonates, or similarly flawed rocks. The strategy deployed aims to cover these two risks with a blanket approach to lost circulation risk in carbonates. The success of this approach is demonstrated using well performance data from a total of 43 wells drilled before and after the introduction of the wellbore strengthening strategy. As it was initially assumed that wellbore strengthening could not be applied to carbonate formations, other techniques had been tried to prevent lost circulation. Those techniques provided mixed results. Since the implementation of wellb
多年来,油气行业一直在采用通过成功支撑和封堵诱导裂缝来提高地层强度的技术。该方法已成功处理了600 - 1100微米范围内的诱导裂缝。静态井筒强化技术通常用于覆盖1000微米及以下所有裂缝尺寸风险。井筒强化技术的应用一直局限于渗透性地层。在大多数情况下,井筒加固已经部署到具有作业挑战性的砂裂缝梯度,或者在边界被推动的地方,渗透率范围较低,如淤泥。迄今为止,页岩或碳酸盐岩井眼加固仍然是行业面临的一个挑战,很少有成功的案例或证据表明在整个钻井过程中能够持续提高裂缝梯度。本文介绍了在Habshan碳酸盐岩地层Khazzan/Ghazeer油田已报道的漏失事件的历史。它还描述了在尾管胶结期间引入的设计变化,以加强岩石并实现循环/返回。设计工作基于挪威北海地区碳酸盐岩井眼强化技术的应用经验。本文还对本文的工作进行了总结。阿曼Habshan碳酸盐岩地层存在“诱发”裂缝风险,存在漏失风险。自从Khazzan/Ghazeer油田开始钻井作业以来,Habshan地层在作业过程中多次发生泥浆流失,如尾管下入、底部尾管调节泥浆和固井,当地层暴露在较高的压力下,而在钻井过程中则较少发生泥浆流失。在阿曼的Habshan井面临挑战,在固井过程中经常发生严重的漏失,增加了作业成本,更重要的是,在实现层间隔离目标方面存在困难。通过之前在挪威的现场经验,制定了一套标准,以确定标准丸强化碳酸盐的方法。目前部署的策略旨在解决通过支撑和封堵(井筒强化)引发裂缝的风险,并提供一定的能力来密封经常遇到碳酸盐或类似缺陷岩石的天然裂缝。所采用的策略旨在通过全面解决碳酸盐岩漏失风险来解决这两种风险。采用该方法前后共钻了43口井的井况数据,证明了该方法的成功。由于最初认为井眼加固不适用于碳酸盐地层,因此尝试了其他技术来防止漏失。这些技术带来了好坏参半的结果。自实施井眼强化以来,在达到层间隔离要求和减少流体漏失方面取得了显著进展。
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Day 3 Tue, November 30, 2021
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