白云岩的分类命名:研究现状与方案初探OA
Classification and nomenclature of dolostones:research status and scheme discussion
现有碳酸盐岩分类体系多基于石灰岩建立,直接套用至结构多样、成因复杂的白云岩,存在成因指示性薄弱、对成岩结构改造的表征不足、关键矿物学信息缺失、适用性不足等问题,制约了白云岩沉积学研究与油气储层精细评价.为此,系统梳理国内外白云岩分类命名现状及代表性方案,对比古今白云岩结构、构造与成因差异,总结前寒武系白云岩命名争议与现存短板,并结合岩石宏微观特征与人工智能技术探索适配的分类路径.研究结果表明:①现有方案因缺乏统一标准,命名原则差异较大且多基于单一分类依据,未系统考虑结构组分复杂性与微生物因素;②整合宏微观多尺度特征,初步构建以"宏微观结合、多因素综合、成因关联"为原则的白云岩二级结构-成因分类框架,涵盖晶粒、颗粒、微生物三类基础岩性与成因修饰体系;③提出引入图像识别与机器学习技术,可实现岩石特征定量提取,提升分类命名的客观性与标准化水平.结论认为,研究明确了传统分类方案的局限性,构建了适配白云岩成因与结构特征的初步分类体系,可为统一白云岩命名标准、深化白云岩成因研究及油气勘探应用提供理论支撑.
The existing classification system for carbonate rocks is primarily based on limestone,and is directly applied to dolostones with diverse textures and complex origins.As a result,this approach faces problems such as weak genetic indication,insufficient characterization of diagenetic textural alterations,lack of key mineralogical information,and inadequate applicability,all of which hinder the study of dolostone sedimentology and the fine evaluation of oil and gas reservoirs.To this end,this paper systematically reviews the current status and representative schemes of dolostone classification and nomenclature both domestically and internationally,and compares ancient and modern dolostones in terms of texture,structure and genesis.In addition,the controversies and existing shortcomings in the nomenclature of Precambrian dolostones are summarized,and a suitable classification path is explored based on rock macro-and micro-characteristics,together with artificial intelligence technology.The following results are obtained.First,the existing schemes are lack of a unified standard,exhibiting significant differences in nomenclature principles,and are mostly based on a single classification basis,without systematically taking into account the textural and compositional complexity and microbial factors.Second,a secondary texture and genesis based dolostone classification framework following the principles of"combining macro-and micro-characteristics,integrating multiple factors,and correlating with genesis"is preliminarily constructed by integrating macro-and micro-scale characteristics.It encompasses three basic lithological and genetic modification systems:crystalline,granular,and microbial.Third,it is proposed to introduce image recognition and machine learning technology to enable the quantitative extraction of rock features and thus enhance the objectivity and standardization level of classification and nomenclature.In conclusion,the research findings clarify the limitations of traditional classification schemes,and establish a preliminary classification system that is adaptive to the genetic and textural characteristics of dolostones,thereby providing theoretical support for unifying dolostone nomenclature standards,advancing the study of dolostone genesis,and facilitating its application in oil and gas exploration.
文华国;甯濛;冯滟杰;陈家乐;王夏
成都理工大学沉积地质研究院||油气藏地质及开发工程全国重点实验室 (成都理工大学)||中国石油碳酸盐岩储层重点实验室成都理工大学研究分室||自然资源部深时地理环境重建与应用重点实验室成都理工大学沉积地质研究院||油气藏地质及开发工程全国重点实验室 (成都理工大学)||中国石油碳酸盐岩储层重点实验室成都理工大学研究分室||自然资源部深时地理环境重建与应用重点实验室成都理工大学沉积地质研究院||油气藏地质及开发工程全国重点实验室 (成都理工大学)中国石油华北油田公司山西煤层气勘探开发分公司成都理工大学沉积地质研究院||油气藏地质及开发工程全国重点实验室 (成都理工大学)||中国石油碳酸盐岩储层重点实验室成都理工大学研究分室||自然资源部深时地理环境重建与应用重点实验室
能源科技
碳酸盐岩分类命名白云岩研究现状结构-成因分类原则分类命名框架分级命名人工智能
Classification and nomenclature of carbonate rocksDolostoneResearch statusPrinciple of texture-and genesis-based classificationClassification and nomenclature frameworkHierarchical nomenclatureArtificial intelligence
《天然气工业》 2026 (9)
45-59,15
国家自然科学基金项目"微生物白云石/岩成因机制研究:以巴西现代微生物白云石和华北地台元古代微生物白云岩为例"(编号:42472156)、"四川盆地寒武系龙王庙组白云岩-蒸发岩共生体系耦合机制"(编号:42272133),四川省自然科学基金项目"四川盆地灯影组白云岩储层海相白云石胶结物成因机制及油气储集意义"(编号:2026NSFSC1157),四川省青年科技创新研究团队项目"天然气成藏物质基础"(编号:22CXTD0064).
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