致密砂岩储层复杂油水层成因分析与测井评价OA北大核心
Cause analysis and logging evaluation of complex oil-water layer in tight sandstone reservoir:a case study of the 6th member of Yanchang Formation in Ningxian Area,Ordos Basin
致密砂岩储层非均质性强,孔隙结构复杂,微弱地质信号增加测井解释的多解性,油水层识别难度大.以鄂尔多斯盆地宁县地区延长组6段砂岩储层为研究对象,采用岩性、物性、孔隙结构、流体性质及其赋存状态实验,分析研究区复杂油水层成因;采用BP神经网络法建立储层物性、含油性测井解释模型,采用交会图版法和随机森林法建立流体性质识别模型.结果表明:黏土矿物附加导电、碳酸盐胶结物和炭质沥青堵塞孔隙、原油以束缚态和半束缚态形式存在,是研究区延长组6段致密油储层油水关系复杂的主要因素;采用BP神经网络法建立的储层物性、含油性测井解释模型,可提高储层参数计算精度;采用交会图版法可有效识别油层、油水同层和水层(包括含油水层);采用随机森林法建立的流体性质识别模型,可精确区分油层、一类油水同层(日产油2 t以上)、二类油水同层(日产油2 t以下)及水层(包括含油水层),提高测井解释符合率.该结果为鄂尔多斯盆地宁县地区延长组6段储层的经济开发和有效动用提供支持.
The tight sandstone reservoir has strong heterogeneity and complex pore structure.Weak geo-logical signals increase the multiplicity of logging interpretation,and it is difficult to identify oil and wa-ter layers.Taking the sandstone reservoir of the 6th member of Yanchang Formation in Ningxian Area of Ordos Basin as the research object,the genesis of complex oil and water layers in the study area was analyzed by experiments on lithology,physical property,pore structure,fluid property and fluid occur-rence state of the cores.The BP neural network method is used to establish reservoir physical property and oiliness logging interpretation models,the fluid property identification model is established by cross-plot method and random forest method.The results show that the additional conductivity of rock clay minerals,the blockage of pores by carbonate cements and carbonaceous asphalt,the crude oil in the form of bound state and semi-bound state are the main factors for the complex oil-water relationship in the tight oil reservoirs of the 6th member of Yanchang Formation in the study area.The interpretation models of reservoir physical property and oiliness established by BP neural network method,which can improve the calculation accuracy of reservoir parameters.The intersection chart of porosity and oil satu-ration can effectively identify oil layers,oil-water layers and water layers(including oil-bearing water layers).The fluid property identification model based on random forest algorithm can accurately distin-guish oil layer,such as class Ⅰ oil-water layer(more than 2 t/d),class Ⅱ oil-water layer(less than 2 t/d)and water layer(including oil-bearing water layer).The results can improve the coincidence rate of log-ging interpretation greatly and provide technical support for the economic development and effective uti-lization of reservoirs in the study area.
姚东华;陈言;许承武;孙先达;潘毅
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苏州冠德能源科技有限公司,江苏苏州 215000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
石油、天然气工程
致密砂岩复杂油水层孔隙结构BP神经网络随机森林延长组6段鄂尔多斯盆地
tight sandstonecomplex oil-water layerpore structureBP neural networkrandom for-est6th member of Yangchang FormationOrdos Basin
《东北石油大学学报》 2025 (2)
60-70,11
国家自然科学基金项目(42172163)
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