地震属性分析在越南巴赫河油田东北部下中新统储层表征中的应用

H. M. Nguyen, A. Le, Muoi Nguyen, N. Bui
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摘要

龟龙盆地是越南南部早第三纪裂谷盆地,是越南最具油气开发潜力的高产盆地。对龟龙盆地中新统下储层的特别关注是由于裂缝性基底中独特的含油能力逐渐枯竭,并且有可能将生产井转移到沉积盖层陆源岩的上覆矿床并进入新的矿床开发。近年来,地震属性分析已成为预测非构造圈闭中可能存在砂体的古河床的有效工具。了解这些砂体的分布规律对油气勘探定向具有重要意义。应用地震属性分析方法结合人工神经网络(ANN)和井资料,对巴赫河油田东北部下第三系砂岩储层进行了预测。选择地震属性作为人工神经网络训练的输入,包括相对声阻抗、均方根、甜度。这些属性为显示不同地震振幅特征的地质特征以及预测岩相、岩石学和砂体分布提供了最明显的机会。研究结果确定了巴赫河油田东北部具有河流、边缘湖相和三角洲沉积环境的潜在储层。
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Application of seismic attribute analysis in Lower Miocene reservoir characterization, northeast Bach Ho field, Vietnam
The Cuu Long basin is an Early Tertiary rift basin of southern Vietnam, and the most potential basin in the country with high productive for oil and gas. Special interest in the Lower Miocene reservoir in the Cuu Long basin is caused by the gradual depletion of unique oil-bearing in the fractured basement and the possibility of transferring production wells to overlying deposits in the terrigenous rocks of the sedimentary cover and entering new deposits into development. In recent years, seismic attributes analysis has emerged as an effective tool to predict ancient riverbeds where sand bodies may exist in nonstructural traps. Understanding the distribution of these sand bodies will be of great significance in the orientation of oil and gas exploration activities. The paper applied seismic attribute analysis method combined with artificial neural network (ANN) and well data to predict the distribution of sandstones reservoirs of Lower Miocene sediments in the Northeastern Bach Ho oil field. Seismic attributes selected as input for ANN training including Relative Acoustic Impedance, Root Mean Square, Sweetness. The attributes provide the most obvious opportunity to display geological features with varying seismic amplitude characteristics as well as predict lithofacies, petrology and the distribution of sand bodies. The research results have identified the potential reservoirs in the Northeastern area of Bach Ho field, which are deposited in the fluvial, marginal lacustrine and deltaic environments.
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