中国人口资源与环境
中國人口資源與環境
중국인구자원여배경
China Polulation.Resources and Environment
2010年
6期
41~46
,共null页
BP神经网络 储量价值 主成分分析 价值评价
BP神經網絡 儲量價值 主成分分析 價值評價
BP신경망락 저량개치 주성분분석 개치평개
BP neural network; reserve value; principal component analysis; value appraisal
在广泛选取原始指标的基础上,从可采储量、油气价格、开发投资、经营成本4个方面,构建了基于主成分分析法的油气储量价值等级划分指标体系,建立了基于BP神经网络的油气储量价值等级划分模型,并对胜利油田的数据进行实证分析。本文的创新及特色一是通过用7个主成分保留了95%的原始信息建立指标体系,避免了指标间相关性对后期评价的影响,提高了后期评价的准确性。二是通过设置初始权重、学习率、动态系数等参数使基于BP神经网络的油气储量价值等级划分模型的精度高达96.61%,避免了传统评价中模糊随机因素和人为主观因素的影响,提高了评价的准确性和科学性。结果表明,采收率、储量丰度、储量规模、储层埋深、凝固点等5个指标是影响油气储量价值等级的关键因素。储量价值越高,采收率越大、储量规模越大、储量丰度越大、储层埋深越小、凝固点越低。
在廣汎選取原始指標的基礎上,從可採儲量、油氣價格、開髮投資、經營成本4箇方麵,構建瞭基于主成分分析法的油氣儲量價值等級劃分指標體繫,建立瞭基于BP神經網絡的油氣儲量價值等級劃分模型,併對勝利油田的數據進行實證分析。本文的創新及特色一是通過用7箇主成分保留瞭95%的原始信息建立指標體繫,避免瞭指標間相關性對後期評價的影響,提高瞭後期評價的準確性。二是通過設置初始權重、學習率、動態繫數等參數使基于BP神經網絡的油氣儲量價值等級劃分模型的精度高達96.61%,避免瞭傳統評價中模糊隨機因素和人為主觀因素的影響,提高瞭評價的準確性和科學性。結果錶明,採收率、儲量豐度、儲量規模、儲層埋深、凝固點等5箇指標是影響油氣儲量價值等級的關鍵因素。儲量價值越高,採收率越大、儲量規模越大、儲量豐度越大、儲層埋深越小、凝固點越低。
재엄범선취원시지표적기출상,종가채저량、유기개격、개발투자、경영성본4개방면,구건료기우주성분분석법적유기저량개치등급화분지표체계,건립료기우BP신경망락적유기저량개치등급화분모형,병대성리유전적수거진행실증분석。본문적창신급특색일시통과용7개주성분보류료95%적원시신식건립지표체계,피면료지표간상관성대후기평개적영향,제고료후기평개적준학성。이시통과설치초시권중、학습솔、동태계수등삼수사기우BP신경망락적유기저량개치등급화분모형적정도고체96.61%,피면료전통평개중모호수궤인소화인위주관인소적영향,제고료평개적준학성화과학성。결과표명,채수솔、저량봉도、저량규모、저층매심、응고점등5개지표시영향유기저량개치등급적관건인소。저량개치월고,채수솔월대、저량규모월대、저량봉도월대、저층매심월소、응고점월저。
On the ground of the widely chosen efficiency indexes of reserve value of oil and gas,an index system of reserve value of oil and gas is established based on principal component analysis.The index system is formed through four aspects,such as recoverable reserves,oil-gas price,development investment and operating cost.Then,BP neural network is applied to grade reserve value.The contribution of this article came from the following three aspects. Firstly,the new index system is built based on improved principal component analysis which keeps 96.50% of the original information with 7 indexes and avoids the influence of the correlation between different indexes on later appraise.Secondly,BP neural network is established which avoids the influence of the subjective factors.By setting the initial weights,learning rate,the dynamic coefficient of parameters,the accuracy of the model is 96.61%.Thirdly,the result reflects that the major factors that affect the grade reserve value of oil and gas are the recovery factor,the reserve abundance,the reserve scale,the reserve depth and freezing point.
