海上油气生产实验模拟与智能优化技术研究
发布时间：2018-12-10 12:50
【摘要】：海上油田生产优化不同于陆上油田生产优化,由于海上生产平台空间有限,在一个局限的空间中分布着几十口井,井口相聚较近,导致井间干扰现象的出现。因而单井的优化方法不能满足生产需要。本论文建立了海上油气生产实验模拟装置,利用该装置进行了平台生产效率和产量的优化实验;分别进行了单井无模型梯度寻优实验、多井无模型梯度寻优实验、水井无模型梯度寻优实验、无模型一体化优化实验,得到了收敛的优化结果,实现了海上油气生产的无模型梯度智能寻优。将实验所得数据运用于BP人工神经网络的训练,建立了海上生产实验装置的BP仿真模型,且该模型计算精度高;同时对海上油气生产系统的优化目标进行筛选,以产量和系统效率为优化目标,建立了适用于海上油气生产系统的多目标优化数学模型。在对NSGA-Ⅱ算法与其他三种算法进行性能对比后,确定选用NSGA-Ⅱ作为优化算法。将海上生产系统多目标优化模型、BP仿真模型与NSGA-Ⅱ算法进行结合,对海上油气生产体统进行了多目标优化,得到了精确度较高的优化结果,实现了最大系统效率、高采油量、低注水能耗的优化目标。通过实验验证多目标优化结果的有效性与精确度,最后对无模型梯度优化结果和多目标优化结果进行了对比评价。
[Abstract]:The production optimization of offshore oil field is different from that of onshore oil field production. Because of the limited space of offshore production platform, dozens of wells are distributed in a limited space, and the wellhead is close to each other, which leads to the phenomenon of inter-well interference. Therefore, the single well optimization method can not meet the production needs. In this paper, a simulation device for offshore oil and gas production is established, and the platform production efficiency and output are optimized by using the device. Experiments of single well without model gradient optimization, multi-well without model gradient optimization, wells without model gradient optimization, without model integration optimization experiment were carried out, and the convergence optimization results were obtained. The model-free gradient intelligent optimization of offshore oil and gas production is realized. The experimental data are applied to the training of BP artificial neural network, and the BP simulation model of offshore production experimental device is established, and the accuracy of the model is high. At the same time, the optimization objectives of offshore oil and gas production system are screened, and the multi-objective optimization mathematical model for offshore oil and gas production system is established with the objective of production and system efficiency as the optimization goal. After comparing the performance of NSGA- 鈪，
本文编号：2370595
[Abstract]:The production optimization of offshore oil field is different from that of onshore oil field production. Because of the limited space of offshore production platform, dozens of wells are distributed in a limited space, and the wellhead is close to each other, which leads to the phenomenon of inter-well interference. Therefore, the single well optimization method can not meet the production needs. In this paper, a simulation device for offshore oil and gas production is established, and the platform production efficiency and output are optimized by using the device. Experiments of single well without model gradient optimization, multi-well without model gradient optimization, wells without model gradient optimization, without model integration optimization experiment were carried out, and the convergence optimization results were obtained. The model-free gradient intelligent optimization of offshore oil and gas production is realized. The experimental data are applied to the training of BP artificial neural network, and the BP simulation model of offshore production experimental device is established, and the accuracy of the model is high. At the same time, the optimization objectives of offshore oil and gas production system are screened, and the multi-objective optimization mathematical model for offshore oil and gas production system is established with the objective of production and system efficiency as the optimization goal. After comparing the performance of NSGA- 鈪，
本文编号：2370595
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