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The Stimulation Optimization Research Of Xingshugang Oil Field

Posted on:2016-11-28Degree:MasterType:Thesis
Country:ChinaCandidate:Q Y MengFull Text:PDF
GTID:2271330461481521Subject:Oil and gas field development project
Abstract/Summary:PDF Full Text Request
The apricot six districts of Xingshugang oil field in daqing has entered the determining developmentment,currently oil field faces limited remaining recoverable reserves,remaining oil distribution is highly fragmented,increased difficulties of complex geological situation,Development is difficult,production decline rapidly and other world-class development problem,after several years of water flooding,the oil field formation between the three major contradictions,injection-production relationship is complex,the salt effect is very poor,Therefore, how to effectively balance the contradiction,solve the above problems,for oilfield continue to increase production,scientific and reasonable and sustainable development strategy,now has become a common problem facing the late high water cut oilfield.In this paper,Taking The apricot six districts of Xingshugang oil field in daqing as the research object,the apricot xingshugang oil field geological characteristics in this block,reservoir characteristics,the development present situation,the remaining oil potential,block the main problems and contradictions are analyzed.First analysis the apricot six different data,oil and water Wells after the stimulation from the oil well fracturing,oil well fill holes,oil well water plugging and Wells acidification specific stimulation effect analysis and evaluation,in order to know the various influencing factors of production and the growing oil amount,the correlation degree between this paper adopts the single factor analysis method,grey fuzzy comprehensive evaluation method and artificial neural network in fracturing Wells,to evaluate the correlation between the factors.Six areas of apricot oil field development evaluation has certain guiding significance.
Keywords/Search Tags:Apricot six area, Stimulation Grey, Fuzzy Evaluation, Artificial Neural Networks
PDF Full Text Request
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