Petroleum Science >2022,??lssue 1:??- DOI: https://doi.org/10.1016/j.petsci.2021.10.008
Application of multi-attribute matching technology based on geological models for sedimentary facies: A case study of the 3rd member in the Open?Access
文章信息
作者：Zong-Quan Yao, Fan Yang, Deleqiati Jianatayi, Wei Wang, Yang Gao, Le Sun, Wen-Feng Wang, Bo-Yu Mu, Pin-Bai Pan,
作者單位：
投稿時(shí)間：
引用方式：Zong-Quan Yao, Fan Yang, Deleqiati Jianatayi, Wei Wang, Yang Gao, Le Sun, Wen-Feng Wang, Bo-Yu Mu, Pin-Bai Pan, Application of multi-attribute matching technology based on geological models for sedimentary facies: A case study of the 3rd member in the Lower Jurassic Badaowan Formation, Hongshanzui area, Junggar Basin, China, Petroleum Science, Volume 19, Issue 1, 2022, Pages 116-127, https://doi.org/10.1016/j.petsci.2021.10.008.
文章摘要
Abstract
Regarding high drilling costs, an effort should be made to substantially reduce the drilling operation. To achieve this goal, exploration and development stages should be carried out precisely with maximum information acquired from the reservoir. The use of multi-attribute matching technology to predict sedimentary system has always been a very important but challenging task. To resolve the challenges, we utilized a quantitative analysis method of seismic attributes based on geological models involving high resolution 3D seismic data for sedimentary facies. We developed a workflow that includes core data, seismic attribute analysis, and well logging to highlight the benefit of understanding the facies distribution in the 3rd Member of the Lower Jurassic Badaowan Formation, Hongshanzui area, Junggar Basin, China. 1) Data preprocessing. 2) Cluster analysis. 3) RMS attribute based on a normal distribution constrains facies boundary. 4) Mapping the sedimentary facies by using MRA (multiple regression analysis) prediction model combined with the lithofacies assemblages and logging facies assemblages. The confident level presented in this research is 0.745, which suggests that the methods and data-mining techniques are practical and efficient, and also be used to map facies in other similar geological settings.
Regarding high drilling costs, an effort should be made to substantially reduce the drilling operation. To achieve this goal, exploration and development stages should be carried out precisely with maximum information acquired from the reservoir. The use of multi-attribute matching technology to predict sedimentary system has always been a very important but challenging task. To resolve the challenges, we utilized a quantitative analysis method of seismic attributes based on geological models involving high resolution 3D seismic data for sedimentary facies. We developed a workflow that includes core data, seismic attribute analysis, and well logging to highlight the benefit of understanding the facies distribution in the 3rd Member of the Lower Jurassic Badaowan Formation, Hongshanzui area, Junggar Basin, China. 1) Data preprocessing. 2) Cluster analysis. 3) RMS attribute based on a normal distribution constrains facies boundary. 4) Mapping the sedimentary facies by using MRA (multiple regression analysis) prediction model combined with the lithofacies assemblages and logging facies assemblages. The confident level presented in this research is 0.745, which suggests that the methods and data-mining techniques are practical and efficient, and also be used to map facies in other similar geological settings.
關(guān)鍵詞
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Clustering analysis; Mapping the sedimentary facies; Normal distribution; Multi-attribute matching; Hongshanzui area