论文详情
大数据统计在碳酸盐岩油气田开发中的应用
西南石油大学学报(自然科学版)
2018年 40卷 第6期
阅读:134
查看详情
Title
Application of Big Data to Carbonate Oil and Gas Field Exploitation
Authors
HAN Jie
ZHANG Shaowei
WU Jiangyong
CHEN Si
MA Xiaoping
单位
中国石油塔里木油田分公司勘探开发研究院, 新疆 库尔勒 841000
Organization
Research Institute of Exploration and Development, Tarim Oilfield Company, PetroChina, Korla, Xinjiang 841000, China
摘要
为解决塔里木盆地下古生界奥陶系碳酸盐岩油气田后续高效井的部署难题,在精细构造成图的基础上,进行有效圈闭的识别和分类,通过海量钻井资料统计分析油气富集规律,重新落实构造对油气的控制作用。结果表明,研究区主要的构造圈闭类型可分为背斜圈闭、断背斜圈闭及与走滑断裂相关的断裂圈闭共3大类6小类;研究区碳酸盐岩储层具有一定的连续性和连通性,油、气、水的分布宏观上和微观上符合油气差异聚集原理。构造圈闭是油气最富集的区域,是高效井集中分布区,油气藏富集模式可分为圈闭内富集型、斜坡全充注型、斜坡半充注型和斜坡全漏失型四种,其中斜坡全充注型和圈闭内富集型是钻探获高效井最有利的地质目标。
Abstract
To solve the issue of arranging follow-up high-performance wells in the Ordovician carbonate oil and gas fields in the Tarim Basin, effective traps are recognized and classified based on detailed structural mapping. Statistical analyses of numerous drilling data were conducted to obtain oil and gas accumulation patterns and verify controls on structures in oil and gas reserves. The results reveal that the major types of structural traps in the study area can be divided into three main categories and six sub-categories. The three main categories are anticline traps, faulted anticline traps, and strike-slip fault-related faulted traps. The carbonate reservoir in the study area is, to a certain degree, continuous and inter-connected. Distributions of oil, gas, and water macroscopically and microscopically agree with the differential entrapment theory of oil and gas. Structural traps are regions where oil and gas are the most concentrated, and therefore should be prioritized for areas with concentrations of high-performance wells. Oil and gas accumulation modes can be classified into four types, accumulation within traps, fully filled slopes, partially filled slopes, and completely leaking slopes. Among these, fully filled slopes and accumulation within traps are the most favorable geological conditions for drilling and obtaining high-performance wells.
关键词:
奥陶系;
大数据;
圈闭;
构造油气藏;
差异聚集;
富集规律;
Keywords:
Ordovician system;
big data;
traps;
structural oil/gas reservoirs;
differential entrapment;
accumulation patterns;
DOI
10.11885/j.issn.1674-5086.2017.09.08.01