基于测井资料的页岩油储层甜点预测

doi:10.11885/j.issn.16745086.2021.04.28.10

摘要/Abstract

摘要： 页岩油储层甜点预测受很多因素的影响，明确其主控因素并赋以合理权重是快速、高效地进行甜点评价的关键。传统的页岩油甜点预测法在赋以权重以及划分标准方面不尽合理。为此，首先，采用灰色关联分析法进行主控因素分析；其次，利用复相关系数法对优选的主控因素按照其所属储层类型进行合理的赋值；最后，综合建立储层的地质工程甜点系数来实现页岩储层甜点的精准预测。以长庆油田陇东地区长₇段页岩油储层为研究对象，利用测井资料从烃源岩特性品质（SQ）、储层物性品质（RQ）和完井品质（CQ）评价方面优选了10个具有代表性的地质和工程甜点参数，并建立了工区页岩油储层地质工程双甜点评价标准：X_SQ>0.581、X_RQ>0.494和X_CQ>0.715，该标准预测得到的工区甜点与实际高低产区吻合度高，证实了该方法的准确性。本研究可为陇东地区长₇段页岩油储层的甜点预测和井位部署提供理论依据。

关键词: 测井资料, 甜点预测, 主控因素, 灰色关联分析法, 评价标准

Abstract: The prediction of sweet spots in shale oil reservoirs is affected by many factors. Clarifying the main controlling factors and assigning reasonable weights is the key to fast and efficient sweet spot evaluation. The traditional prediction method of shale oil sweet spots is not reasonable in terms of weight and classification standard. For this reason, firstly, the grey correlation analysis method is used to analyze the main control factors; then, the multiple correlation coefficient method is used to reasonably assign the optimal main control factors according to the type of reservoir to which they belong; finally, the geological engineering sweet spot coefficient of the reservoir is established to realize accurate prediction of shale reservoir sweet spots. Taking the Chang 7 shale oil reservoir in Longdong Aera of Changqing Oilfield as the research object, by using logging data, 10 representative geological and engineering parameters are selected from the aspects of source rock property quality(SQ), reservoir physical property quality(RQ) and completion quality(CQ) and the geological engineering double sweet spot eva-luation standard of shale oil reservoir in the work area is established: X_SQ>0.581, X_RQ>0.494 and X_CQ>0.715. The sweet spots predicted by this standard are in good agreement with the actual high and low production areas, which confirms the accuracy of the method. The research can provide a theoretical basis for the sweet spot prediction and well location layout of the Chang 7 shale oil reservoir in Longdong area.

Key words: logging data, sweet spot prediction, main controlling factors, grey correlation analysis, evaluation standard

中图分类号:

TE348

夏宏泉, 赖俊, 李高仁, 杨赟. 基于测井资料的页岩油储层甜点预测[J]. 西南石油大学学报(自然科学版), 2021, 43(4): 199-207.

XIA Hongquan, LAI Jun, LI Gaoren, YANG Yun. Sweet Spot Prediction of Shale Oil Reservoir Based on Logging Data[J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2021, 43(4): 199-207.

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http://journal15.magtechjournal.com/Jwk_xnzk/CN/Y2021/V43/I4/199

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