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深水浊积水道训练图像建立与多点地质统计建模应用
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  • 英文篇名:Establishment of training images of turbidity channels in deep waters and application of multi-point geostatistical modeling
  • 作者:胡迅 ; 尹艳树 ; 冯文杰 ; 王立鑫 ; 段太忠 ; 赵磊 ; 张文彪
  • 英文作者:Hu Xun;Yin Yanshu;Feng Wenjie;Wang Lixin;Duan Taizhong;Zhao Lei;Zhang Wenbiao;Yangtze University;Petroleum Exploration and Production Research Institute,SINOPEC;
  • 关键词:变差函数 ; 三维训练图像 ; 多点地质统计学 ; 算法改进 ; 深水水道 ; 沉积过程
  • 英文关键词:variogram;;three-dimensional training image;;multi-point geostatistics;;algorithm improvement;;deep-water channel;;depositional process
  • 中文刊名:石油与天然气地质
  • 英文刊名:Oil & Gas Geology
  • 机构:长江大学;中国石化石油勘探开发研究院;
  • 出版日期:2019-07-24 10:37
  • 出版单位:石油与天然气地质
  • 年:2019
  • 期:05
  • 基金:国家自然科学基金项目(40572081);; 国家科技重大专项(2016ZX05033-003-002)
  • 语种:中文;
  • 页:184-192
  • 页数:9
  • CN:11-4820/TE
  • ISSN:0253-9985
  • 分类号:P618.13
摘要
深水浊积水道具有丰富油气,是油气勘探开发的热点领域。以安哥拉深水浊积水道为对象,开展基于多点地质统计的储层建模研究。针对深水水道沉积以及迁移特征,对基于沉积过程的Alluvsim算法进行了改进。通过在Alluvsim中增加整体迁移算法,模拟浊积水道的整体迁移沉积过程。根据浊积水道决口少而弯曲度增加的特点,在Alluvsim中增加了弯曲度指标约束,从而再现浊积水道的弯曲特征。根据安哥拉深水浊积水道地质知识库文献调研,获得了研究区浊积水道形态以及统计特征参数信息。采用改进的Alluvsim算法获得了研究区浊积水道的训练图像。以此训练图像作为模式输入,以井资料作为条件输入,以地震资料作为趋势约束,采用多点地质统计Snesim算法建立了安哥拉深水浊积水道三维地质模型,再现了安哥拉浊积水道的空间分布特征。对模型进行了检验表明,建立的地质模型计算的变差函数与地震属性获得变差函数具有较好的一致性,建立的三维地质模型可以用于后续油藏工程与数值模拟研究,指导油田勘探开发。该研究不仅为多点地质统计应用于实际储层建模提供了完整的建模流程,也为浊积水道训练图像自动生成提供了技术保障。
        Deep-water turbidity channels are rich in oil and gas,and a hot area of hydrocarbon exploration and development. The deep-water turbidity channels in Angola are taken for reservoir modeling based on multi-point geostatistics. Alluvsim algorithm based on sedimentary process was improved to capture deep-water channels' sedimentation and migration characteristics. First,the integral migration and deposition processes of turbidity channels were simulated by adding integral migration algorithm to Alluvsim algorithm. Second,the curvature index constraint was also added to represent the original curvature characteristics of turbidity channels,to simulate the morphology of fewer crevasses and higher sinuosity for the channels of Angola deep waters. In addition,we obtained the morphology and statistical characteristic parameters of turbidity channels in the study area through literature surveys on the geological knowledge database of deep-water turbidity channels in Angola. The so acquired training images of turbidity channels in the study area improved Alluvsim algorithm. Thereafter,a three-dimensional geological model of the deep-water channels in Angola was established based on Snesim algorithm of multi-point geostatistics,to reproduce the spatial distribution of these channels,in which the training image was the model,logging data were the conditions,and seismic data were the trend constraint. The inspection of the model result shows that the variogram calculated by the geological model is in good agreement with that obtained by seismic attributes,and the geological model set up in this study may be used for subsequent reservoir engineering and numerical simulation research to guide oilfield exploration and development. Apart from providing a complete modeling workflow for the application of multi-point geostatistics to actual reservoir modeling,the study also demonstrates the technical feasibility for the automatic generation of turbidity channel training images.
引文
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