基于深度学习的纳米级页岩三维数字岩心重构及导电机理研究OA
Research on 3D digital rock reconstruction and conductive mechanism of nanoscale shale based on deep learning
岩石电阻率是计算储层含水饱和度的关键岩石物理参数.针对页岩油储层导电机理复杂且岩电实验困难的问题,提出了基于深度学习的纳米级页岩三维数字岩心重构和数值模拟流程,以揭示页岩的导电机理并计算其电性参数.首先针对页岩孔隙结构的各向异性特征,利用深度学习技术构建具有纳米级精度的三维数字岩心;进而采用数学形态学方法,在不同饱和度状态下模拟储层中的油水微观赋存状态;利用Waxman-Smits模型改进有限元电性模拟方法,以实现对页岩岩电参数的精确计算.数值模拟结果表明,页岩导电性具有显著的各向异性:水平方向的导电能力优于垂直方向,但垂直方向上黏土矿物附加导电性影响更为突出,导致垂直方向的地层因素和胶结指数大于水平方向,而其饱和度指数则小于水平方向;电阻增大率及其对应的饱和度指数变化受孔隙结构与黏土矿物附加导电性的共同控制,孔隙结构的影响越大,则电阻增大率曲线变化越快,而黏土矿物附加导电性越强,则曲线变化越趋平缓.通过三维数字岩心数值模拟流程,能够有效揭示页岩油储层复杂的导电机理并获取关键岩电参数,为含油气饱和度计算及储量评估提供重要的物理依据和技术支撑.
Rock resistivity is a critical petrophysical parameter for calculating reservoir water saturation.To address the challenges of complex electrical conduction mechanisms and difficult rock electrical experiments in shale oil reservoirs,a process for reconstructing 3D digital shale rocks at the nanoscale and conducting numerical simulations based on deep learning was proposed to reveal the electrical conduction mechanisms and calculate the electrical parameters of shale.First,by considering the anisotropic characteristics of shale pore structures,deep learning was employed to construct 3D digital rocks with nanoscale precision;subsequently,mathematical morphology methods were utilized to simulate the microscopic oil and water distribution states in reservoirs under different saturation conditions;the Waxman-Smits model was incorporated to improve the finite element electrical simulation method,enabling accurate calculation of shale rock electrical parameters.Numerical simulation results demonstrate that shale conductivity exhibits significant anisotropy.The horizontal direction exhibits superior electrical conductivity compared to the vertical direction,yet the additional conductivity effect of clay minerals is more pronounced in the vertical direction,resulting in a greater formation resistivity factor and cementation exponent in the vertical direction than in the horizontal direction,whereas the saturation exponent is smaller in the vertical direction than in the horizontal direction.The resistivity index and its corresponding saturation exponent are jointly controlled by pore structure and additional conductivity of clay minerals.A greater influence of pore structure indicates faster variation of the resistivity index curve,while stronger additional conductivity of clay minerals leads to a more gradual curve variation.Through this 3D digital rock numerical simulation workflow,the complex electrical conduction mechanisms of shale oil reservoirs can be effectively revealed,and key rock electrical parameters are obtained,providing an essential physical basis and technical support for hydrocarbon saturation calculation and reserve evaluation.
李忠新;曹小朋;吕琦;蒋龙;程紫燕;迟蓬;孙福璟;林承焰
中国石油大学(华东)地球科学与技术学院,山东 青岛 266580||中国石化胜利油田分公司 勘探开发研究院,山东 东营 257015||页岩油气富集机理与高效开发全国重点实验室,山东 东营 257015中国石化胜利油田分公司 勘探开发研究院,山东 东营 257015中国石化胜利油田分公司 勘探开发研究院,山东 东营 257015中国石化胜利油田分公司 勘探开发研究院,山东 东营 257015中国石化胜利油田分公司 勘探开发研究院,山东 东营 257015中国石化胜利油田分公司 勘探开发研究院,山东 东营 257015中国石化胜利油田分公司 油藏动态监测中心,山东 东营 257001中国石油大学(华东)地球科学与技术学院,山东 青岛 266580
能源科技
页岩油数字岩心纳米级孔隙电阻率数值模拟深度学习
shale oildigital rocknanoscale poreresistivitynumerical simulationdeep learning
《油气地质与采收率》 2026 (2)
36-47,12
国家科技重大专项"渤海湾盆地济阳坳陷古近系陆相页岩油勘探开发技术与集成示范"(2024ZD1405100),中国石化股份有限公司科技项目"页岩油地质精细评价技术研究"(P24031).
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