马尔科夫链分析在东海陆架盆地花港组沉积微相分析中的应用

    APPLICATION OF MARKOV CHAIN ANALYSIS IN THE MICROFACIES RECOGNITION OF HUAGANG FORMATION IN THE EAST CHINA SEA SHELF BASION

    • 摘要: 通过对东海陆架盆地某凹陷取心井岩心仔细观察和描述,采用双属性划分标准,在研究区花港组岩心中识别出了28种岩石相类型.其中砾岩相5种,砂岩相15种,细粒岩相8种.针对22口取心井岩心详细划分沉积微相和岩石相,共取得2227个岩石相数据.针对研究区发育的湖泊、三角洲、河流3种沉积体系,运用马尔科夫链分析不同沉积微相类型中岩石相沉积序列模式,建立了不同沉积微相类型可能的岩石相组合规律及岩石相定量组合概率,为后期研究相同或相似类型的沉积相提供地质知识库,并为沉积相的识别提供定量的基础.

       

      Abstract: With attentive observation and description for the cores from a depression of East China Sea shelf basin, 28 lithofacies types are identified from the cores of Huagang Formation in the study area, including 5 for conglomerate, 15 for sandstone and 8 for fine-grained rock. By the analysis for the cores from 22 wells, 2227 numbers of lithofacies and microfacies data are obtained. Three sedimentary systems, i.e. lakes, deltas and rivers, are developed in this area, dominated by lacustrine sediments. The Markov chain analysis is used to analyze the sequence patterns of lithofacies in different sedimentary microfacies and establish the possible lithofacies assemblages and quantitative lithofacies assemblage probability. The results will provide a geological database for further study of the same or similar types of sedimentary facies and a quantitative basis for the identification of sedimentary facies.

       

    /

    返回文章
    返回