致密砾岩油藏压裂甜点预测研究—以玛18井区为例
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TE348

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国家自然科学基金(51904257)


Investigation on the fracturing sweet spot prediction of conglomerate tight oil reservoir: A case study of the Ma18 well block
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National Natural Science Foundation of China (51904257)

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    摘要:

    致密油藏压裂甜点的准确预测是合理部署井位和压裂改造成功的关键。玛湖致密砾岩油藏复杂的地质特征和强非均质性,导致其压裂甜点的预测较为困难。针对目前缺乏有效预测玛湖砾岩油藏压裂甜点方法的问题和提高水平井压裂改造效果的迫切需求,本文在压裂改造效果主控因素分析基础上,以储层改造体积(Stimulated Reservoir Volume, SRV)为预测指标,首先优选已有基于可压性指数的压裂甜点评价模型,同时建立了基于机器学习的致密砾岩油藏压裂甜点预测模型,最终形成了适用于玛湖致密油藏压裂甜点的预测方法。研究结果表明:在基于可压性指数的压裂甜点预测模型中,Cui、Di、Lai等人建立的模型与实际监测结果有具有较高吻合度;在基于机器学习算法的压裂甜点预测模型中,随机森林、GRBT、Bagging模型表现出较好的性能;虽然当前数据下基于可压性计算的压裂甜点模型的性能更佳,但是随着现场数据的更新与准确度的提高,基于机器学习的压裂甜点模型预测精度将不断改善。研究成果对于玛湖致密砾岩油藏压裂甜点和综合甜点评价、井位部署、压裂改造设计具有重要的指导意义。

    Abstract:

    Accurate prediction of fracturing sweet spots in tight reservoirs is the key to rational well placement and successful stimulation. It is difficult to predict the fracturing sweet spot of Mahu tight conglomerate reservoir due to its complex geological characteristics and strong heterogeneity. In view of the lack of effective methods to predict the fracturing sweet spot of the Mahu conglomerate reservoir and the urgent need to improve the fracturing effect of horizontal wells, based on the analysis of the main controlling factors of fracturing effect, this paper took stimulated reservoir volume (SRV) as the prediction index. Firstly, the existing evaluation model of fracturing sweet spot based on the fracability is optimized, and the prediction model of fracturing sweet spot based on machine learning is established for tight conglomerate reservoir. Finally, the prediction method for fracturing sweet spot is formed for Mahu tight reservoir. The results show that the models established by Cui, Di, La etc. have high precision in the prediction model of fracturing sweet spots based on the fracability. Among fracture sweet spot prediction models based on machine learning algorithm, random forest, GRBT and Bagging models show good performance. Although the performance of the fracturing sweet spot model based on the compressibility calculation is better under the current data, the prediction accuracy of the fracturing sweet spot model based on machine learning will continue to improve as the field data is updated and the accuracy improves. The research results have important guiding significance for evaluation of fracturing sweet spots and comprehensive sweet spots, well placement and fracturing stimulation design of Mahu tight conglomerate reservoir.

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杨琨,罗山贵,花凌旭,等. 致密砾岩油藏压裂甜点预测研究—以玛18井区为例[J]. 科学技术与工程, 2022, 22(32): 14174-14183.
Yang Kun, Luo Shangui, Hua Lingxu, et al. Investigation on the fracturing sweet spot prediction of conglomerate tight oil reservoir: A case study of the Ma18 well block[J]. Science Technology and Engineering,2022,22(32):14174-14183.

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历史
  • 收稿日期:2022-02-28
  • 最后修改日期:2022-08-18
  • 录用日期:2022-07-06
  • 在线发布日期: 2022-12-05
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