首页|期刊导航|地质通报|鄂尔多斯盆地南部长7页岩油储层地质力学特征及可压裂性评价

鄂尔多斯盆地南部长7页岩油储层地质力学特征及可压裂性评价OA

Geomechanical characteristics and fracability evaluation of Chang 7 shale oil reservoir in the southern Ordos Basin

中文摘要英文摘要

[研究目的]鄂尔多斯盆地是中国重要的非常规油气产区,其内延长组长 7 储层页岩油富集,勘探开发潜力巨大.储层地质力学评价是指导和实现鄂尔多斯盆地页岩油效益开发的关键.查明长 7 页岩油储层地质力学特征,建立定量预测模型,是支撑储层可压裂性评价、甜点区段优选的重要依据.[研究方法]采集盆地南部典型井延长组长 7 储层岩心样品,通过实验测试获取弹性模量、泊松比、现今地应力等地质力学参数,以其为约束,借助 BP 神经网络构建基于测井数据的地质力学参数预测模型,分析长 7 页岩油储层的地质力学特征,并评价其可压裂性.[研究结果]研究结果表明,基于 BP 神经网络的储层地质力学参数预测模型精度高,预测结果与实测值误差小;长 7 页岩油储层关键地质力学参数具非均质性,弹性模量介于 16.26~59.12 GPa 之间,断裂韧性介于 0.2~1.2 MPa·m0.5 之间,水平最大主应力和水平最小主应力分别为 20~43 MPa 和 12~38 MPa;构建基于储层地质力学参数的长 7 页岩油储层可压裂性评价指标 F,据其划分储层为 4 等级:Ⅰ类储层 F>2.00,Ⅱ类储层2.00>F>1.50,Ⅲ类储层 1.50>F>0.10,Ⅳ类储层 F<1.00.[结 论]BP 神经网络是储层地质力学参数精细预测的有效方法,研究结果可为储层压裂优化设计提供科学指导.

[Objective]The Ordos Basin is a pivotal region for unconventional oil and gas production in China.The Yanchang Formation Chang 7 reservoir possesses abundant shale oil resources and significant exploration potential.Reservoir geomechanics evaluation is critical for guiding the efficient development of these resources.Characterizing the geomechanical properties of the Chang 7 shale oil reservoir and establishing a quantitative prediction model are essential for evaluating reservoir fracability and optimizing sweet spot intervals.[Methods]In this study,representative core samples were collected from the Chang 7 reservoir in the southern Ordos Basin.Geomechanical parameters,including elastic modulus,Poisson's ratio,and present-day in-situ stresses,were determined experimentally.Subsequently,a geomechanical parameter prediction model was constructed using the BP neural network based on logging data to achieve quantitative evaluation of the reservoir.[Results]The results indicate the following:The BP neural network-based model demonstrates high accuracy,with minimal error between predicted results and measured values;The key geomechanical parameters of the Chang 7 shale oil reservoir exhibit significant heterogeneity.Specifically,the elastic modulus is between 16.26 GPa and 59.12 GPa,the fracture toughness is between 0.2~1.2 MPa·m0.5,the horizontal maximum and minimum principal stress range from 20 MPa to 43 MPa,12 MPa to 38 MPa,respectively;A fracability evaluation index F was established based on these reservoir geomechanical parameters to classify the reservoir quality.The reservoirs are categorized into four levels:Class Ⅰreservoirs F>2.00,Class Ⅱ reservoirs 2.00>F>1.50,Class Ⅲ reservoirs 1.50>F>0.10,and Class Ⅳ reservoirs F<1.00.The BP neural network is an effective method for the precise prediction of reservoir geomechanical parameters.[Conclusions]These findings provide scientific guidance for the optimization of hydraulic fracturing designs in the region.

辛红刚;鞠玮;冯胜斌;宁卫科;马文忠;王治涛

中国石油长庆油田分公司勘探开发研究院,陕西 西安 710018||低渗透油气田勘探开发国家工程实验室,陕西 西安 710018煤层气资源与成藏过程教育部重点实验室,江苏 徐州 221008||中国矿业大学资源与地球科学学院,江苏 徐州 221116中国石油长庆油田分公司勘探开发研究院,陕西 西安 710018||低渗透油气田勘探开发国家工程实验室,陕西 西安 710018煤层气资源与成藏过程教育部重点实验室,江苏 徐州 221008||中国矿业大学资源与地球科学学院,江苏 徐州 221116中国石油长庆油田分公司勘探开发研究院,陕西 西安 710018||低渗透油气田勘探开发国家工程实验室,陕西 西安 710018中国石油长庆油田分公司勘探开发研究院,陕西 西安 710018||低渗透油气田勘探开发国家工程实验室,陕西 西安 710018

天文与地球科学

页岩油储层长7储层可压裂性储层地质力学BP神经网络鄂尔多斯盆地

shale oil reservoirChang 7 reservoirfracabilityreservoir geomechanicsBP neural networkOrdos Basin

《地质通报》 2026 (2)

236-248,13

新型油气勘探开发国家科技重大专项课题《长 7 夹层型页岩油精细分类评价及规模增储》(编号:2025ZD1404801)和中国石油天然气股份公司科技重大专项《陆相页岩油规模增储上产与勘探开发技术研究》(编号:2023ZZ15) Supported by the National Science and Technology Major Project for New Oil and Gas Exploration and Development(No.2025ZD1404801),and the Science and Technology Major Project of PetroChina Company Limited(No.2023ZZ15)

10.12097/gbc.2025.02.005

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