矩阵增产- ipr方法优选候选井

E. M. Amarfio, P. T. Adusu
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引用次数: 2

摘要

选择合适的候选井进行增产作业是该过程经济成功的最关键步骤。选择标准包括评估井损和选择合适的增产措施。大多数选择方法只考虑破坏的影响及其相应的处理方法,而忽视了这一过程的经济影响。因此,本研究利用Vogel流入动态关系(IPR)曲线分析,提出了一种详细的方法来选择基质增产的候选井。利用这一分析,在Microsoft Excel中建立了非线性数学优化模型。该模型需要每口井的特定输入参数,以便生成可以分析的结果,从而做出正确的决策。为了验证该模型,使用了Nero油田四口井的数据作为输入参数。结果表明,N3井增产后总产油量最高,为12 833 886桶,应考虑进行增产作业。对N3井也进行了敏感性分析,以了解在油价、贴现率和增产时间等自变量变化时该井的表现。结果表明,增产后油井动态受油价的正影响,随油价的升高而增大。然而,增产后的油井性能受到折现率和增产时间的负面影响,随着这两个参数的增加而减小
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Optimising Candidate Well Selection for Matrix Stimulation-IPR Approach
The selection of appropriate candidate wells for a stimulation operation is the most vital step for the economic success of the process. The selection criteria include assessing the well damage and choosing the appropriate approach to stimulate it. Most selection approaches consider the effects of damage and their corresponding treatment methods neglecting the economic influence of the process. This research, therefore, presents a detailed approach to candidate well selection for matrix stimulation using Vogel’s Inflow Performance Relationship (IPR) curve analysis. A non-linear mathematical optimisation model was developed in Microsoft Excel using this analysis. This model requires certain input parameters for each well in order to generate results which could be analysed for the right decision. To validate the model, data from four wells on the Nero Field were used as input parameters. The results show that Well N3 has the highest total post-stimulation production of 12 833 886 barrels of oil and therefore should be considered for the stimulation operation. Sensitivity analysis was also conducted on Well N3 to see the performance of the well when certain independent variables such as price of oil, discount rate, and stimulation time are varied. The results show that the post-stimulation well performance is positively influenced by oil price, increasing as the oil price increase. The post-stimulation well performance, however, show a negative influence from both the discount rate and stimulation time, decreasing as those two parameters increase
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