首页> 外文会议>SPE International Oilfield Scale Conference and Exhibition >Carbonate and Sulphide Scale Prediction Modelling in Auto-Scaling Processes: Procedure for the Calculation of Reservoir Fluid Compositions and Scale Profiles in Production Systems using Topside Data
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Carbonate and Sulphide Scale Prediction Modelling in Auto-Scaling Processes: Procedure for the Calculation of Reservoir Fluid Compositions and Scale Profiles in Production Systems using Topside Data

机译:碳酸酯和硫化物尺度预测建模在自垢过程中:使用顶侧数据计算储层流体组合物和生产系统中的刻度分布的过程

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Carbonate and sulphide scales can form in CO2 and/or H2S-rich environments in a process which we refer to as "auto-scaling",i.e.these scales form in the produced brine due to a change in conditions such as pressure and temperature,not due to brine mixing.Particularly in production systems,carbonate and sulphide scales can form due to the evolution of CO2 and H2S from the aqueous phase to the gas phase caused by a pressure decrease.Carbonate scale formation in this manner is broadly understood; however,there are details of precisely how this occurs in auto-scaling processes which are not widely appreciated. Measuring the water composition at surface locations(e.g.at the separator)does not give a full indication per se of the amount of scale that has precipitated upstream of the sampling point.However,the composition of the water before precipitation occurs is required for predicting the scaling potential of the system,and this information is seldom available.In this paper,we propose a model that accounts for this issue,and that accurately calculates the carbonate and sulphide scaling profiles in CO2 and/or H2S-rich production systems by knowing only commonly available surface data – i.e.pressure,temperature,and fluid compositions (water,gas,and oil).A rigorous workflow which can do this calculation using any aqueous scale prediction model along with a PVT Model has already been published by the authors(Verri et al,2017a).The current paper describes a new model to do these calculations which also includes an approach for estimating both the "correct" scaling case within a range of cases up to the "worst case" carbonate scaling scenario. A scale prediction model has been developed to include a three-phase flash algorithm(using the Peng- Robinson Equation of State)coupled with an aqueous electrolyte model(using the Pitzer equations as the activity model).This model is used to run a demonstration example showing the procedure to calculate accurate auto-scaling profiles in CO2 and/or H2S-rich production systems,which is based on building a sensitivity analysis on the ions directly involved in precipitation reactions.We also note that auto-scaling profiles in production systems are commonly obtained by sectioning the production system – either by parameterising depth with pressure and temperature,or by selecting specific locations(e.g.DHSV,wellhead, etc.).Then,established guidelines to treat scale(or not)based on the calculated saturation ratios and precipitated masses of scale can be applied.We show that such an approach is not optimal and that it can lead to under or over-estimation of scale treatments.Furthermore,building on our previous method(Verri etal 2017a)we propose an approach to model the cumulative amount of scale formed under full equilibrium conditions,which is not dependent on how the production system is sectioned.By doing so,the correct amount of scale formed in the production system is always calculated,thus avoiding non-optimum scale treatments. Our approach focuses on calculating the correct auto-scaling profiles in CO2 and/or H2S-rich production systems,and on correctly interpreting the results obtained by thermodynamic modelling and it can be easily integrated with commonly available scale prediction software.
机译:碳酸酯和硫化物鳞片可以在我们称为“自动缩放”的过程中在CO 2和/或H 2 S的环境中形成,因此由于压力和温度等条件的变化,因此在生产的盐水中形成了在生产的盐水中的尺度形式,而不是由于盐水混合。在生产系统中,由于来自水相的CO 2和H 2 S的进化,碳酸盐和硫化物鳞片可以形成由由压力降低引起的气相的CO 2和H 2。以这种方式的碳酸盐级形成碳酸盐鳞片形成;但是,有详细说明这在不被广泛欣赏的自动缩放过程中发生这种情况。测量表面位置的水组合物(分离器)的水组合物不给出沉淀在取样点上游的水垢量的完全指示。然而,需要在沉淀之前进行水的组成来预测系统的缩放潜力,这些信息很少可用。在本文中,我们提出了一种占该问题的模型,并通过仅知道,准确地计算CO2和/或H2S的生产系统中的碳酸盐和硫化物缩放曲线通常可用的表面数据 - Inullure,温度和流体组成(水,气体和油)。作者已经发布了使用任何含水量预测模型进行该计算的严格工作流程已经由作者发表(Verri等等,2017A)。目前的论文描述了一种新模型,可以进行这些计算,该计算还包括一种用于估算一系列案例内的“正确”缩放案例的方法到“最糟糕的情况”碳酸盐缩放场景。已经开发了一种规模预测模型来包括三相闪存算法(使用状态的韧带罗宾逊方程)与含水电解质模型(使用Pitzer方程作为活动模型)。本模型用于运行演示示出了计算CO2和/或H2S富含生产系统中精确的自动缩放配置文件的过程,其基于直接涉及降水反应的离子的敏感性分析。我们还注意到生产系统中的自动缩放轮廓通常是通过分开生产系统 - 通过压力和温度的参数化深度,或者通过选择特定位置(EGDHSV,井口等)。然后,根据计算的饱和度比确定规模(或不)的建立指导可以应用和沉淀的鳞屑。我们表明这种方法不是最佳的,并且它可以导致规模治疗的范围或过度估计。繁华,建筑NG在我们以前的方法(Verri Etal 2017A)上,我们提出了一种模拟在完整均衡条件下形成的累积规模的方法,这不依赖于生产系统的切片方式。如此,形成了正确的规模量始终计算生产系统,从而避免了非最优比例处理。我们的方法侧重于计算CO2和/或H2S丰富的生产系统中的正确自动缩放配置文件,并在正确地解释通过热力学建模获得的结果,并且可以容易地与常规预测软件集成。

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