砂砾岩储层测井评价方法研究
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摘要
随着勘探程度的逐步深入,隐蔽油气藏的勘探日益被重视,寻找新的储层已成为当前各油田所面临的重要研究课题。砂砾岩体油气藏一直是寻找隐蔽性油气藏的有利地区,而该类油气藏一般具有埋藏深、岩性复杂、低孔低渗、孔隙结构复杂、非均质性强等特点,导致有效储层与非有效储层难以划分,油水层无法准确判断。砂砾岩体测井储层评价、油气层解释、地质和工程应用在国内外石油勘探领域均属评价难题,都需要新的理论和先进的工程技术来支撑。
砂砾岩体油气藏的复杂性使该类油气藏储层测井评价受到了严重的挑战,造成用传统的测井评价方法难以准确计算储层参数和确定储层流体性质,进而使得测井解释结果与测试、试油试采结果不吻合。为此提出了采用测井相分析技术,根据测井响应特征首先将储集层按其岩石物理特征划分为不同类型的岩石物理相,然后按岩石物理相类型建立相应的测井解释模型的方法。该方法使同类岩石物理相具有相似的岩石学特征,孔-渗关系呈现出规律性变化,表现出相似的岩电关系和测井响应特征,从而将地层非均质性问题转变为相对均质性问题。在此基础上,选取和油水层关系密切的测井参数或计算的参数,采用主成分分析等数学方法,提取反映油水层特征的综合特征参数,进行油水层判别。
应用提出的方法及开发的软件对研究区14口井的资料进行了实际处理,取得了良好的效果,有效地提高了储层参数解释的精度和油水层判别的准确度。
With the development of oil prospecting, it is very important to find new oil-gas reservoir, we pay more attention on conceal oil-gas reservoir and glutenite reservoir is one type of good conceal oil-gas reservoir. Glutenite reservoir which has strong aeolotropism and complex lithology and ultra low porosity is difficult to evaluate with well logging data. It’s hard to identify effective reservoir and oil-water layer. The reservoir evaluation with well logging data and the discrimination of oil-water and the application of geology are all difficult problems to the field of oil prospecting at home and aboard, so it requires new theories and advanced technologies to support.
It is such a serious challenge for reservoir logging evaluation because of the complexity of glutenite reservoir, and reservoir parameters can not be calculated accurately and reservoir fluid properties also can not be determined accurately by traditional logging evaluation methods which lead to that the logging interpretation results are different from the test results. The paper makes use of electrofacies analysis technique, divides the whole reservoir into several lithophases according to logging response, then builds models for different lithophases. The method makes every lithophase have similar logging response, lithology characteristic and regular for porosity, permeability. We translate aeolotropic, nonlinear issues into homogeneous, linear issues. On basis of reservoir parameter calculation, we select the well logging or the reservoir parameters which closely relate to the oil-water, and we form the new parameters by electrofacies analysis to identify oil–water layer.
Applying the methods and the newly developed software, logging data of 14 wells of the region have been processed and the results are satisfactory. The accuracy of reservoir parameters and oil–water layer identification are obviously improved.
砂砾岩体油气藏的复杂性使该类油气藏储层测井评价受到了严重的挑战,造成用传统的测井评价方法难以准确计算储层参数和确定储层流体性质,进而使得测井解释结果与测试、试油试采结果不吻合。为此提出了采用测井相分析技术,根据测井响应特征首先将储集层按其岩石物理特征划分为不同类型的岩石物理相,然后按岩石物理相类型建立相应的测井解释模型的方法。该方法使同类岩石物理相具有相似的岩石学特征,孔-渗关系呈现出规律性变化,表现出相似的岩电关系和测井响应特征,从而将地层非均质性问题转变为相对均质性问题。在此基础上,选取和油水层关系密切的测井参数或计算的参数,采用主成分分析等数学方法,提取反映油水层特征的综合特征参数,进行油水层判别。
应用提出的方法及开发的软件对研究区14口井的资料进行了实际处理,取得了良好的效果,有效地提高了储层参数解释的精度和油水层判别的准确度。
With the development of oil prospecting, it is very important to find new oil-gas reservoir, we pay more attention on conceal oil-gas reservoir and glutenite reservoir is one type of good conceal oil-gas reservoir. Glutenite reservoir which has strong aeolotropism and complex lithology and ultra low porosity is difficult to evaluate with well logging data. It’s hard to identify effective reservoir and oil-water layer. The reservoir evaluation with well logging data and the discrimination of oil-water and the application of geology are all difficult problems to the field of oil prospecting at home and aboard, so it requires new theories and advanced technologies to support.
It is such a serious challenge for reservoir logging evaluation because of the complexity of glutenite reservoir, and reservoir parameters can not be calculated accurately and reservoir fluid properties also can not be determined accurately by traditional logging evaluation methods which lead to that the logging interpretation results are different from the test results. The paper makes use of electrofacies analysis technique, divides the whole reservoir into several lithophases according to logging response, then builds models for different lithophases. The method makes every lithophase have similar logging response, lithology characteristic and regular for porosity, permeability. We translate aeolotropic, nonlinear issues into homogeneous, linear issues. On basis of reservoir parameter calculation, we select the well logging or the reservoir parameters which closely relate to the oil-water, and we form the new parameters by electrofacies analysis to identify oil–water layer.
Applying the methods and the newly developed software, logging data of 14 wells of the region have been processed and the results are satisfactory. The accuracy of reservoir parameters and oil–water layer identification are obviously improved.
引文
[1]胡复堂.砂砾岩油藏开发模式[M].北京:石油工业出版社,1997
[2] Bush J M. Determination of lithology from well logs by statistical analysis[J].SPE, 1985,14 (301)
[3]范宜仁,黄隆基,代诗华.交会图技术在火山岩岩性与裂缝识别中的应用[J].测井技术,1999,23(1):53-56
[4]范翔宇,夏宏泉,钟敬敏.基于多矿物模型的测井相识别研究[J].测井与射孔,2003,4(4):13-15
[5] Bucheb J A,Evans H B. Some application of methods used in electrofacies identification[J].The Log Analyst,1994,35(1):14-26
[6]寥明光.模糊模式识别沉积相[J].测井技术,1991,15 (3):157-162
[7]席道瑛,张涛.神经网络模型在测井岩性识别中的应用[J].煤田地质与勘探,1994,22(6):56-61
[8]刘业新,李衍达.测井资料多目标优化处理的研究与应用[J].测井技术,1994,18(1):1-7
[9]李舟波.地球物理测井数据处理与综合解释[M].长春:吉林大学出版社,2003:4-106
[10]罗利,姚声贤,任兴国,等.神经网络及模式识别技术在测井解释中的应用[J].测井技术,2002,26(5):364-368
[11]夏宏泉,任兴国.基于神经网络法的逐点渗透率测井解释研究[J].西南石油学院学报,2001,23(1):11-13
[12]孙建孟,王永刚.地球物理资料综合运用[M].山东东营:石油大学出版社,2001:1-44
[13]雍世和,张超谟,2006,测井数据处理与综合解释[M].山东东营:中国石油大学出版社,2007:32-270,312-463
[14]洪有密.测井原理与综合解释[M].山东东营:石油大学出版社,2002:1-23
[15]欧阳健.石油测井解释与储层描述[M].北京:石油工业出版社,1994:54-131
[16]侯雨庭,李高仁,郭清娅.特低渗油层测井精细解释与分类评价技术[J].油气勘探,2006,11(1):51-54
[17]姚光庆,赵彦超,张森龙.新民油田低渗细粒储集砂岩岩石物理相研究[J].地球科学,1995,20(3):355-360
[18]谢然红,肖立志,张建民,等.低渗透储层特征与测井评价方法[J].中国石油大学学报(自然科学版),2006,30(1):47-55
[19]张丽艳,王磊,孙建孟.罗家地区砂砾岩体岩相特征及其分析技术[J].石油大学学报(自然科学版),2004,28(3):33-35
[20]吴海燕.滨浅湖相滩坝砂岩储层测井判识技术——以胜利油区正理庄油田高89块为例[J].石油天然气学报,2007,29(6):87-91
[21]石油测井情报协作组.测井新技术应用[M].山东东营:石油大学出版社,1998:210-212
[22]贾文玉,田素月,孔耀庭,等.成像测井技术与应用[M].北京:石油工业出版社,2000:15-21
[23]陈钢花,吴文圣,毛克宇.利用地层微电阻率扫描图像识别岩性[J].石油勘探与开发,2001,28(2):53-55
[24]吴文圣,陈钢花,工中文,等.用地层微电阻率扫描成像测井识别沉积构造特征[J].测井技术,2000,24(1):60-65
[25]肖立志.核磁共振成像测井原理与核磁共振岩石物理实验[M].北京:科学出版社,1998:3-35
[26]黄隆基.核测井原理[M].山东东营:石油大学出版社,1996:194-197
[27]肖立志.核磁共振测井资料解释与应用导论[M].北京:石油工业出版社,2001:13-28
[28]运华云,赵文杰.NMR测井资料在复杂砂泥岩油气层解释中的应用[J].测井技术,2001,16(2):42-49
[29]陈钢花,王中文,李德云,等.用多元统计方法自动识别沉积微相[J].石油物探,1997,36(1):71-76
[30]雍世和,陈钢花.测井曲线自动分层[J].测井技术,1987,11(6):44-47
[31]刘光祖.概率论与应用数理统计[M].北京:高等教育出版社,2000:25-30
[32]雍世和,陈钢花.应用Bayes逐步判别分析自动确定岩性[J]:石油物探,1990,29(2):68-77
[33]石玉江,张海涛,侯雨庭,等.基于岩石物理相分类的测井储层参数精细解释建模[J].测井技术,2005,29(4):328-332
[34]高博禹,彭仕宓,刘红岐.蒙古林砾岩油藏储层测井精细解释模型[J].测井技术,2005,29(1):55-58
[35]董经利,张晋言.东营凹陷北带砂砾岩体天然气测井评价方法[J].测井技术, 2007,31(3):216-220
[36] Lee,S.H., ARUN,K., and AKHIL, D.G. Electrofacies characterization and permeability predictions in complex reservoirs[J].SPE Reservoir Evaluation & Engineering,2002,6:237-248
[37]马丽娟,何新贞.东营凹陷北部砂砾岩储层描述方法[J].石油物探,2002,41 (3):354-358
[38]谭成仟,宋子文.碎屑岩储集层测井评价技术[M].西安:陕西科学技术出版社,2001:50-108
[39]张丽艳,才巨宏,陈钢花.砂砾岩储集层含油性解释方法[J].测井技术,2002,26(2):134-136
[2] Bush J M. Determination of lithology from well logs by statistical analysis[J].SPE, 1985,14 (301)
[3]范宜仁,黄隆基,代诗华.交会图技术在火山岩岩性与裂缝识别中的应用[J].测井技术,1999,23(1):53-56
[4]范翔宇,夏宏泉,钟敬敏.基于多矿物模型的测井相识别研究[J].测井与射孔,2003,4(4):13-15
[5] Bucheb J A,Evans H B. Some application of methods used in electrofacies identification[J].The Log Analyst,1994,35(1):14-26
[6]寥明光.模糊模式识别沉积相[J].测井技术,1991,15 (3):157-162
[7]席道瑛,张涛.神经网络模型在测井岩性识别中的应用[J].煤田地质与勘探,1994,22(6):56-61
[8]刘业新,李衍达.测井资料多目标优化处理的研究与应用[J].测井技术,1994,18(1):1-7
[9]李舟波.地球物理测井数据处理与综合解释[M].长春:吉林大学出版社,2003:4-106
[10]罗利,姚声贤,任兴国,等.神经网络及模式识别技术在测井解释中的应用[J].测井技术,2002,26(5):364-368
[11]夏宏泉,任兴国.基于神经网络法的逐点渗透率测井解释研究[J].西南石油学院学报,2001,23(1):11-13
[12]孙建孟,王永刚.地球物理资料综合运用[M].山东东营:石油大学出版社,2001:1-44
[13]雍世和,张超谟,2006,测井数据处理与综合解释[M].山东东营:中国石油大学出版社,2007:32-270,312-463
[14]洪有密.测井原理与综合解释[M].山东东营:石油大学出版社,2002:1-23
[15]欧阳健.石油测井解释与储层描述[M].北京:石油工业出版社,1994:54-131
[16]侯雨庭,李高仁,郭清娅.特低渗油层测井精细解释与分类评价技术[J].油气勘探,2006,11(1):51-54
[17]姚光庆,赵彦超,张森龙.新民油田低渗细粒储集砂岩岩石物理相研究[J].地球科学,1995,20(3):355-360
[18]谢然红,肖立志,张建民,等.低渗透储层特征与测井评价方法[J].中国石油大学学报(自然科学版),2006,30(1):47-55
[19]张丽艳,王磊,孙建孟.罗家地区砂砾岩体岩相特征及其分析技术[J].石油大学学报(自然科学版),2004,28(3):33-35
[20]吴海燕.滨浅湖相滩坝砂岩储层测井判识技术——以胜利油区正理庄油田高89块为例[J].石油天然气学报,2007,29(6):87-91
[21]石油测井情报协作组.测井新技术应用[M].山东东营:石油大学出版社,1998:210-212
[22]贾文玉,田素月,孔耀庭,等.成像测井技术与应用[M].北京:石油工业出版社,2000:15-21
[23]陈钢花,吴文圣,毛克宇.利用地层微电阻率扫描图像识别岩性[J].石油勘探与开发,2001,28(2):53-55
[24]吴文圣,陈钢花,工中文,等.用地层微电阻率扫描成像测井识别沉积构造特征[J].测井技术,2000,24(1):60-65
[25]肖立志.核磁共振成像测井原理与核磁共振岩石物理实验[M].北京:科学出版社,1998:3-35
[26]黄隆基.核测井原理[M].山东东营:石油大学出版社,1996:194-197
[27]肖立志.核磁共振测井资料解释与应用导论[M].北京:石油工业出版社,2001:13-28
[28]运华云,赵文杰.NMR测井资料在复杂砂泥岩油气层解释中的应用[J].测井技术,2001,16(2):42-49
[29]陈钢花,王中文,李德云,等.用多元统计方法自动识别沉积微相[J].石油物探,1997,36(1):71-76
[30]雍世和,陈钢花.测井曲线自动分层[J].测井技术,1987,11(6):44-47
[31]刘光祖.概率论与应用数理统计[M].北京:高等教育出版社,2000:25-30
[32]雍世和,陈钢花.应用Bayes逐步判别分析自动确定岩性[J]:石油物探,1990,29(2):68-77
[33]石玉江,张海涛,侯雨庭,等.基于岩石物理相分类的测井储层参数精细解释建模[J].测井技术,2005,29(4):328-332
[34]高博禹,彭仕宓,刘红岐.蒙古林砾岩油藏储层测井精细解释模型[J].测井技术,2005,29(1):55-58
[35]董经利,张晋言.东营凹陷北带砂砾岩体天然气测井评价方法[J].测井技术, 2007,31(3):216-220
[36] Lee,S.H., ARUN,K., and AKHIL, D.G. Electrofacies characterization and permeability predictions in complex reservoirs[J].SPE Reservoir Evaluation & Engineering,2002,6:237-248
[37]马丽娟,何新贞.东营凹陷北部砂砾岩储层描述方法[J].石油物探,2002,41 (3):354-358
[38]谭成仟,宋子文.碎屑岩储集层测井评价技术[M].西安:陕西科学技术出版社,2001:50-108
[39]张丽艳,才巨宏,陈钢花.砂砾岩储集层含油性解释方法[J].测井技术,2002,26(2):134-136