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Impact of Reservoir Reactions on Thermodynamic Scale Predictions

机译:水库反应对热力学规模预测的影响

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Evaluation of the scaling risk at production wells is generally carried out using thermodynamic prediction models. These models are generally very accurate in terms of predicting the type of scale that may form, the degree of supersaturation, and the mass of scale that will deposit by the time the system reaches equilibrium – provided the brine composition or compositions involved are well known, and the pressure and temperatures conditions are accurately specified. However, in performing these calculations, engineers and chemists often fail to take account of reactions occurring in the reservoir, and assume that brines reaching the production wells have not reacted in any way prior to entering the wellbore. This often leads to a significant overestimate of the scaling risk. The work presented in this paper addresses this issue by studying data from various fields to identify what can be learnt from the produced brine compositions. A new technique to estimate the range of scaling tendencies that takes account of reservoir precipitation is developed, and the results are displayed in a 3D response surface. This is illustrated for barium sulphate scaling tendency, accounting for different levels of ion stripping. In order to calibrate some simulation parameters, and to identify the more important equations that should be inserted in the reservoir simulation, studies were performed based on the observed data. Different reservoir simulations were used and compared, with a focus on scale management to identify positive and negative aspects of each one. This work has identified that in fields with reservoir temperatures above 120°C and calcium concentrations above 7000 mg/l, significant sulphate stripping occurs due to anhydrite precipitation. This effect is increased where ion exchange leads to a reduction in magnesium and an increase in calcium concentration as the injected brine is displaced through the reservoir.
机译:在生产井上的缩放风险评估通常使用热力学预测模型进行。这些模型在预测可能形成的量级的规模和通过系统达到平衡时的储存程度的规模的类型通常非常准确 - 如果涉及所涉及的盐水组合物或组合物是众所周知的,则并且压力和温度条件被准确地指定。然而,在执行这些计算时,工程师和化学家通常不能考虑水库发生的反应,并且假设达到生产井的盐水在进入井筒之前没有以任何方式反应。这通常会导致缩放风险的显着高估。本文提出的工作通过研究来自各个领域的数据来识别可以从生产的盐水组合物中学到的内容来解决这个问题。开发了一种估计考虑储层降水的缩放倾向范围的新技术,结果显示在3D响应表面中。这是针对硫酸钡缩放趋势的说明,占不同水平的离子剥离。为了校准一些模拟参数,并识别应该在储库模拟中插入的更重要的等式,基于观察到的数据进行研究。使用不同的储层模拟并进行比较,重点是规模管理,以识别每个人的正面和负面方面。该工作已经确定,在具有高于120℃的储层温度和7000mg / L以上的钙浓度的领域,由于空气水石沉淀,发生了显着的硫酸盐剥离。这种效果增加,其中离子交换导致镁的还原,随着注射盐水的钙浓度的增加通过储存器移位。

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