石油学报 ›› 2022, Vol. 43 ›› Issue (7): 912-924.DOI: 10.7623/syxb202207003

• 地质勘探 • 上一篇    下一篇

页岩油综合甜点测井评价——以沧东凹陷孔店组二段为例

姚东华1,2, 周立宏3, 王文革3, 韩国猛2, 蒲秀刚2, 宋延杰1, 许承武1   

  1. 1. 东北石油大学陆相页岩油气成藏及高效开发教育部重点实验室 黑龙江大庆 163318;
    2. 中国石油大港油田公司勘探开发研究院 天津 300280;
    3. 中国石油大港油田公司 天津 300280
  • 收稿日期:2020-10-21 修回日期:2022-01-07 出版日期:2022-07-25 发布日期:2022-08-01
  • 通讯作者: 许承武,男,1978年6月生,2008年获中国科学院地质与地球物理研究所博士学位,现为东北石油大学非常规油气研究院副教授,主要从事储层表征和非常规油气勘探工作。Email:Xuchw@nepu.edu.cn
  • 作者简介:姚东华,男,1983年1月生,2010年获吉林大学博士学位,现为东北石油大学非常规油气研究院讲师,主要从事致密油、页岩油测井解释及岩石物理实验等工作。Email:yaodh@nepu.edu.cn
  • 基金资助:
    中国石油天然气股份有限公司科技重大专项"大港油区效益增储稳产关键技术研究与应用"(2018E-11)和黑龙江省自然科学基金项目"原位加热下油页岩储层孔-裂隙动态演化机制研究"(LH2020D005)资助。

Logging evaluation of composite sweet spots for shale oil: a case study of Member 2 of Kongdian Formation in Cangdong sag

Yao Donghua1,2, Zhou Lihong3, Wang Wen'ge3, Han Guomeng2, Pu Xiugang2, Song Yanjie1, Xu Chengwu1   

  1. 1. MOE Key Laboratory of Continental Shale Hydrocarbon Accumulation and Efficient Development, Northeast Petroleum University, Heilongjiang Daqing 163318, China;
    2. Research Institute of Exploration and Development, PetroChina Dagang Oilfield Company, Tianjin 300280, China;
    3. PetroChina Dagang Oilfield Company, Tianjin 300280, China
  • Received:2020-10-21 Revised:2022-01-07 Online:2022-07-25 Published:2022-08-01

摘要: 地质甜点和工程甜点的识别与融合是实现页岩油效益开发的关键,以沧东凹陷孔店组二段页岩油为例,基于高精度岩石物理实验和常规测井资料,建立了页岩油综合甜点测井评价方法。利用最优化、神经网络、多元非线性拟合以及测井属性分析等技术手段,分别建立了页岩岩性、储集物性、含油性、脆性、断裂韧性、地应力特性以及天然裂缝发育程度等产能敏感参数的测井定量预测模型。进一步构建了表征地质甜点的储油指数、表征工程甜点的可压指数和缝网复杂指数。采用几何平均法建立页岩油综合甜点评价指数,实现了页岩油综合甜点分类,形成了各类综合甜点的地层参数评价标准。通过分析处理沧东凹陷孔店组二段11口页岩油试油井的测井资料,验证了分类方法及评价标准的有效性。研究方法及认识可以为页岩油勘探开发部署、压裂方案优化及储量评价提供必要的技术支撑。

关键词: 页岩油, 储油指数, 可压指数, 缝网复杂指数, 综合甜点

Abstract: The recognition and integration of geological sweet spots and engineering sweet spots is critical to achieving the efficient development of shale oil. Taking the shale oil in Member 2 of Kongdian Formation in Cangdong sag as an example, a logging evaluation method of composite sweet spots for shale oil has been established based on high-precision petrophysical experiments and conventional logging data. Quantitative logging prediction models of the productivity sensitive parameters including shale lithology, physical reservoir properties, oiliness, brittleness, fracture toughness, in-situ stress characteristics and degree of natural fracture development were separately established by means of optimization, neural network, multivariable nonlinear fitting and logging attribute analysis. Further, this study conducts the oil storage index and fracability index characterizing geological sweet spots and engineering sweet spots respectively, as well as fracture network complexity index. The composite sweet spot evaluation index of shale oil has been established using geometric method, so as to classify the composite sweet spots of shale oil. As a result, the formation parameter evaluation criteria for various sweet spots have been set up. Furthermore, the validity of classification methods and evaluation criteria has been verified by analyzing and processing the logging data of 11 shale oil testing wells in Member 2 of Kongdian Formation in Cangdong sag. To sum up, the above research methods and understandings can provide necessary technical support for the shale oil exploration and development deployment, optimization of fracture scheme and evaluation of reserves.

Key words: shale oil, oil storage index, fracability index, fracture network complexity index, composite sweet spot

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