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Prediction of Production in Multiple Clusters Stages Fracturing Horizontal Well by Support Vector Machine

机译:支持向量机在水平井压裂多簇阶段产量预测中的应用

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Conventional production prediction of multi-cluster stages fractured horizontal well is based on numerical simulation technology. While using this method, a large number of parameters needed, such as the reservoir parameters, fracturing treatment parameters, geological parameters etc. The huge computational time consuming of numerical method makes it too difficult for quick filed application. Against these deficiencies, the paper gives full consideration to the effects of reservoir, geology, and multi-cluster stages fractured parameters on productivity. A production prediction model of multi-cluster stages fractured horizontal wells is built by using SVM based on statistical theory and kernel function. First, its training algorithm is used to train the model. Then, samples are used to predict the production. Finally, production data is used to verify the model. Analysis the results show that the SVM model does not only have the advantage of quick prediction application, but also the prediction results obtained by the model have high consistency with the actual production data. It indicates that this method has good engineering practicability in production prediction of multi-cluster stages fractured horizontal wells.
机译:基于数值模拟技术的多簇压裂水平井常规产量预测方法。在使用该方法时,需要大量参数,例如储层参数,压裂处理参数,地质参数等。数值方法计算量大,耗时长,难以快速应用。针对这些缺陷,本文充分考虑了储层,地质和多团聚阶段的压裂参数对生产率的影响。基于统计理论和核函数,利用支持向量机建立了多团段压裂水平井产量预测模型。首先,使用其训练算法来训练模型。然后,将样本用于预测产量。最后,使用生产数据来验证模型。分析结果表明,SVM模型不仅具有快速预测应用的优势,而且该模型获得的预测结果与实际生产数据具有较高的一致性。说明该方法在多簇压裂水平井产量预测中具有良好的工程实用性。

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