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Accurate Modeling of Asphaltene Onset Pressure in Crude Oils Under Gas Injection Using Peng-Robinson Equation of State

机译:鹏罗宾逊国家省气注射液下沥青质发病压力的准确建模

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Asphaltene precipitation is considered a precursor of the plugging of oil wells and subsurface equipment and is a topic of continuous interest among companies and academic institutions. Numerous models to predict asphaltene precipitation at reservoir conditions have emerged over the years, and some have been dropped for several reasons. One particular case is the utilization of cubic equations of state such as Peng-Robinson (PR) and Soave-Redlich-Kwong (SRK), which although are relatively simple to code and utilize, have not been as effective in predicting asphaltene precipitation as compared to other models such as the perturbed chain version of the statistical associating fluid theory equation of state (PC-SAFT EOS). However, we have found that after improving the crude oil characterization procedure to obtain a proper set of simulation parameters from the available experimental data, the cubic equation of state can show excellent predictive capabilities in modeling asphaltene onset pressure under gas injection. In this work, we develop a characterization methodology based on the contents of Saturates-Aromatics-Resins-Asphaltenes (SARA) that can be used with PR EOS. Several case studies with published data from six crude oils are conducted to assess the predictive capability of the new approach in modeling asphaltene onset pressure under gas injection. Comparisons are made with PC-SAFT EOS to highlight the advantages and disadvantages of each model. Also, the modeling approach is tested against high-pressure and high-temperature data from four wells from the Middle East that have not been previously published in the literature. The results indicate that PR EOS yields results that are at least as good as those obtained from PC-SAFT in predicting the onset of asphaltene precipitation in crude oil under various amounts and types of gas injection.
机译:沥青质沉淀被认为是油井和地下设备堵塞的前体,是公司和学术机构中持续兴趣的主题。多年来已经出现了许多模型,以预测储层条件下的沥青质沉淀,有些原因被丢弃。一个特定情况是利用彭 - 罗宾逊(PR)和Soave-Redlich-Kwong(SRK)的立方方程,虽然代码和利用相对简单,但在比较相比,尚未有效预测沥青质沉淀到其他模型,如统计关联流体理论方程的统计关联流体理论方程(PC-SAFT EOS)的扰动链条版本。然而,我们发现,在改善原油表征过程之后从可用的实验数据获得适当的模拟参数后,立方体方程可以显示出在气体喷射下沥青质发作压力的良好预测能力。在这项工作中,我们基于可以与Pr EOS一起使用的饱和芳烃 - 树脂 - 沥青质(SARA)的含量开发表征方法。进行了几种具有来自六种原油的公布数据的案例研究,以评估新方法在气体注射下模拟沥青质发病压力的新方法的预测能力。使用PC-SAFT EOS进行比较,以突出每个模型的优缺点。此外,模拟方法是从中东的四个井中的高压和高温数据测试,这些井上未以前在文献中发表。结果表明,PR EOS产生至少与从PC-SAFT获得的结果一样好,以预测在各种量和类型的气体注射液下原油中沥青质沉淀的发作。

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