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基于蚂蚁算法的断裂自动识别技术在叙利亚戈贝贝油田的应用 被引量:2

Application of automatic fault-fracture system interpretation technique based on ACO in Gbeibe oilfield
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摘要 叙利亚戈贝贝油田为已开发36a的老油田,2004年之前其钻井成功率和油井产量均很低,主要原因是储层断裂体系分布规律及油藏地质特征不明确,而储层断裂体系识别是目前困扰石油开发的世界性难题之一。将基于蚂蚁算法的断裂自动识别技术应用于戈贝贝油田,对断裂体系进行识别,结果表明,研究区的断裂带主要呈东西和南北走向,发育3个彼此不连通且相对独立的断裂连通体系;其油气分布及生产井产能主要受断裂体系控制,高产井和中产井一般位于断裂带及其附近,且在断裂带中生产井段越长,其产量越高。低产井特别是干井一般位于远离断裂带的区域。通过准确描述研究区的断裂带发育特征,新钻水平井成功率大幅提高,达95%,产油量由800m3/d提高至2350m3/d。 The Gbeibe oilfield is an old oilfield with 36 years development history in Syria, and the success rate of drilling and the production of old oil producer are very low before Chinese company took over it in 2004, the geologic characteristics and the oil and gas distribution in the reservoir fracture system are less clear, the reservoir fracture system identification technology itself is currently one of globe problem about the oilfield development technology, in view of this situation, the fault and fracture automatic identification technology which is based on the ant colony optimization(ACO) is successfully applied in Gbeibe oilfield, the technology has clarified that there are 2 fracture zone whose direction are the main east-west and north-south all over Gbeibe oilfield, and 3 fracture system which are not in communication with each other and relatively independent communication system, moreover, it also presents that the distribution of oil and gas well productivity and production is mainly controlled by fault system, that is. the high and middle oil producers are generally located in or near the fracture zone, and the longer the perforated section in the fault zone, the higher the yield, low production wells especially dry-wells are generally located far away from the fault zone in the region. After we use this technique accurately to predict the fault and fracture zone distribution and design of horizontal well in Gbeibe oilfield, the drilling success rate of horizontal well is greatly improved, up to 95%, and the daily oil production is greatly increased to 2350 m3/d from 800 m3/d, the research achievements support the efficient development of Gbeibe oilfield.
出处 《油气地质与采收率》 CAS CSCD 北大核心 2013年第2期48-51,114,共4页 Petroleum Geology and Recovery Efficiency
关键词 断裂体系 蚂蚁算法 自动识别 三维地震 戈贝贝油田 fault and fracture system ant colony optimization (ACO) automatic interpretation three-dimensional seismic data Gbeibe oilfield
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