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A novel inversion approach for fracture parameters and inflow rates diagnosis in multistage fractured horizontal wells

机译:裂缝参数的一种新型反演方法和多级裂缝水平井中的流入速率诊断

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摘要

Significant difficulties still exist in fracture parameters and inflow rates diagnosis for multistage fractured horizontal wells (MFHWs) using conventional method. The newly developed distributed temperature sensing (DTS) technology which can monitor the real-time downhole conditions for MFHWs provides enormous potential to solve this problem. However, due to the lack of robust inversion approaches, it's hard to quantitatively translate the DTS data to fracture parameters and inflow rates. In this work, firstly, a comprehensive inversion system combined with a forward and inversion model is proposed. The forward temperature model is developed to simulate the temperature behavior of an MFHW. The inversion model derived from the Markov Chain Monte Carlo(MCMC) algorithm is used to decrease the differences between the measured temperature and the predicted temperature iteratively. Subsequently, a synthetic case is presented to analyze the temperature characteristics and the application of this inversion approach. It has been found that any temperature drop (Delta T) corresponds to a created fracture and the Delta T are basically proportional to the inflow rates. According to that, a convenient equation is formulated to assign the initial inflow rate distribution to improve the computational efficiency of the inversion procedure. Finally, a field application (Well FH_1) is provided to demonstrate the capability of the developed inversion system to diagnose fracture parameters and inflow rates. Satisfactory inversion results are obtained within finite inversion iterations for this MHFW. The maximum temperature errors corresponding to each fractures are less than 0.02K. The inversed total production rate is 10.329 x 10(4) m(3)/d which matches the measured production rate (10.33 x 10(4)m(3)/d) very well that just validates the accuracy of the developed inversion system. The findings of this study can help for better understanding of fracture parameters and inflow rates diagnosis from the downhole temperature measurements for MFHWs.
机译:使用常规方法,骨折参数和骨折参数和流入速率诊断仍存在显着困难。新开发的分布式温度传感(DTS)技术可以监控MFHWS的实时井下条件提供了解决这个问题的巨大潜力。然而,由于缺乏稳健的反演方法,很难将DTS数据定量转换为断裂参数和流入速率。在这项工作中,提出了一种与前向和反演模型相结合的综合反演系统。开发了正向温度模型以模拟MFHW的温度行为。来自Markov链蒙特卡罗(MCMC)算法的衍生模型用于迭代地降低测量温度和预测温度之间的差异。随后,提出了一种合成案例以分析这种反转方法的温度特性和应用。已经发现,任何温度下降(δT)对应于产生的骨折,并且ΔT基本上与流入速率成比例。根据该方程式,配制了方程式,以分配初始流入速率分布以提高反转过程的计算效率。最后,提供了现场应用程序(井FH_1)以证明发达的反转系统的能力诊断断裂参数和流入速率。在该MHFW的有限反转迭代中获得满意的反演结果。对应于每个裂缝的最大温度误差小于0.02k。逆的总生产率为10.329 x 10(4)m(3)/ d符合测量的生产率(10.33 x 10(4)m(3)/ d),这很好地验证了发达的反转系统的准确性。本研究的结果可以帮助更好地了解骨折参数和来自MFHW的井下温度测量的流入速率诊断。

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