辽河坳陷兴马潜山储层测井解释方法研究
|
摘要
经过几十年的勘探开发，辽河油田已发现了大量的碳酸盐岩，火成岩、变质岩等复杂岩性油气藏，并且在这些复杂岩性储层中都获得了高产工业油流，取得了显著的经济效益。近3年辽河坳陷的太古界变质岩潜山是辽河油田增加探明储量的重要领域。2010年提出兴隆台潜山油气藏建成百万吨产能。虽然国内外在复杂岩性油气藏测井解释方法取得了一些认识，但是兴马太古界潜山储层测井评价还有一些问题亟待解决。本文采用“岩心刻度测井技术”，综合理论方法和模拟井实验方法，建立了水平井岩性自动识别方法、岩石矿物含量计算方法、基质孔隙度和次生孔隙度计算方法，以及裂缝识别和裂缝参数计算方法。
利用兴古、陈古、马古潜山水平井录井岩屑、旋转井壁取心以及薄片的岩心鉴定结果，结合测井响应特征，采用极值方差聚类分析方法能分辨水平井和直井测井曲线“锯齿状”和“平直状”两类岩性。采用二维、三维可视化技术的交会图法、模糊数学法、神经网络法和综合法能自动识别岩性。处理实际水平井测井资料能识别混合花岗岩类、混合片麻岩类、片麻岩类、角闪岩类、花岗岩类、闪长岩类和煌斑岩类等7类岩性，25口井的岩性识别结果与岩心分析符合率达90%以上。利用岩心实验分析资料，采用多矿物模型能准确计算岩石矿物含量、基质孔隙度和含油（气）饱和度。利用声电成像测井资料，采用孔隙度谱分析方法解释基质孔隙度和次生孔隙度，再结合成像测井、多极子阵列声波测井、交叉偶极子声波测井识别潜山裂缝。基于声电衰减理论，结合模拟井裂缝成像测井实验，得出裂缝宽度计算公式，并利用试油、试采资料，综合测井资料建立潜山储层评价标准。结合试采数据、录井及井壁取芯等资料，利用综合测井资料评价潜山储层有效性。综合研究发现:兴马潜山储层中混合花岗岩、混合片麻岩和闪长岩类有较好孔隙度、渗透率；岩性从马古—兴古—陈古潜山带侵入岩厚度逐渐增加，中酸性侵入岩主要发育在北部陈古潜山带，片麻岩、混合岩主要在中部兴古潜山带发育，而混合岩主要分布在南部马古潜山带；兴马潜山构造带的现今地应力方向为北东—南西方向，在应力集中的兴古潜山带，裂缝发育，储层净毛比高，储层发育程度与埋深无明显对应关系；变质岩从片麻岩、混合片麻岩到混合花岗岩，岩浆岩由基性、中性岩浆岩到酸性岩浆岩，储层发育程度逐渐变好，而角闪石岩、斜长角闪岩、煌斑岩脉和辉绿岩脉不发育储层，为非储集岩，为兴马变质岩潜山油气藏的勘探开发提供了有利的技术支持。
After decades of exploration and development, Liaohe Oilfield has found a large numberof complex lithologic reservoirs such as carbonate rocks, igneous, metamorphic and so on,and has obtained high-yield industrial oil flow in such complex lithologic reservoirs, andbenefits a lot from it. During the past3years, Liaohe depressed Archean group metamorphicrock buried hill is a very important area to increase proven reserves in Liaohe oilfield.XingLongtai buried hill reservoir produced a million tons capacity has prompt up in2010.Although complex lithologic reservoir logging interpretation method has developed a lot bothin and outside our country, there are still some problems to be settled urgently in Archeangroup metamorphic rock buried hill reservoir logging evaluation. In this paper, we use “corescale logging technology”, comprehensive theoretical method and simulation wellexperimental method to set up the automatic lithology identification method, rock andmineral content calculation, the matrix porosity and secondary porosity calculation methodand fracture identification and fracture parameters calculation method.
We use mod logging cuttings, rotary sidewall coring and the slice core identificationresult of XingGu, ChenGu, MaGu buried hill, combined with the logging responsecharacteristics and using the extreme variance cluster analysis method to identify the twodifferent logging curves(Jagged and flat-shaped) of the different lithology. We also use2D,3Dvisualization technology in crossplot method, fuzzy mathematics, neural networks andcomprehensive analysis method to identify the lithology automatically. We have dealt withactual logging data to identify the7lithology(mixed granite class, mixed gneiss, gneisses,amphibolites, granite, diorite and lamprophyre class), and the lithology identification result ofthe25well is90%or more meet with the actual result. Based on the core experimental data,we can accurately calculate the rock mineral content, matrix porosity and oil/gas saturationby using multi-mineral model. Based on the acoustoelectric imaging logging experimentaldata, we use porosity spectrum analysis method to explain the matrix porosity and secondaryporosity, and then combined with the imaging logging, multipole array acoustic logging,cross-dipole sonic log to identify the buried hill crack. Based on the acoustoelectricattenuation theory, combined with simulation well crack imaging logging experiment, derive the crack width calculation formula, and then use test oil, trial mining data andcomprehensive logging data to set up the buried hill reservoir evaluation standard. Combinedwith the trial mining data, mod logging and sidewall coring data, using comprehensivelogging data to evaluate the effectiveness of buried hill reservoir. After comprehensive study,we found that: mixed granite, mixed gneiss and diorite class in XingMa buried hill reservoiris with high porosity and permeability. The lithology intrusive rocks thickness is increasedfrom MaGu to XingGu and then ChenGu buried hills. In north part ChenGu buried hill, it ismainly the neutral acid intrusive rocks, and in the middle part XingGu buried hill, it is mainlygneiss and migmatite, in the south MaGu buried hill, it is mainly migmatite. The groundstress of XingMa buried hill tectonic zone is from North-east to south-west. In XingGuburied hill, the stress concentration area, crack developed, the reservoir net gross is high,there is no obvious correspondence between reservoir develop extent and buried depth. Thereservoir develop extent is becoming worse with the order mixed granite, mixed gneiss andgneiss in the metamorphic class, and the order acid magmatic rocks, neutral magmatic rocksand mafic magmatic rocks in the magmatic rock class. Hornblendite, amphibolite rocks,lamprophyre and diabase dikes are undeveloped reservoirs, they are non-reservoir rocks, andand provide beneficial support in exploration of metamorphic buried hill reservoir.
利用兴古、陈古、马古潜山水平井录井岩屑、旋转井壁取心以及薄片的岩心鉴定结果，结合测井响应特征，采用极值方差聚类分析方法能分辨水平井和直井测井曲线“锯齿状”和“平直状”两类岩性。采用二维、三维可视化技术的交会图法、模糊数学法、神经网络法和综合法能自动识别岩性。处理实际水平井测井资料能识别混合花岗岩类、混合片麻岩类、片麻岩类、角闪岩类、花岗岩类、闪长岩类和煌斑岩类等7类岩性，25口井的岩性识别结果与岩心分析符合率达90%以上。利用岩心实验分析资料，采用多矿物模型能准确计算岩石矿物含量、基质孔隙度和含油（气）饱和度。利用声电成像测井资料，采用孔隙度谱分析方法解释基质孔隙度和次生孔隙度，再结合成像测井、多极子阵列声波测井、交叉偶极子声波测井识别潜山裂缝。基于声电衰减理论，结合模拟井裂缝成像测井实验，得出裂缝宽度计算公式，并利用试油、试采资料，综合测井资料建立潜山储层评价标准。结合试采数据、录井及井壁取芯等资料，利用综合测井资料评价潜山储层有效性。综合研究发现:兴马潜山储层中混合花岗岩、混合片麻岩和闪长岩类有较好孔隙度、渗透率；岩性从马古—兴古—陈古潜山带侵入岩厚度逐渐增加，中酸性侵入岩主要发育在北部陈古潜山带，片麻岩、混合岩主要在中部兴古潜山带发育，而混合岩主要分布在南部马古潜山带；兴马潜山构造带的现今地应力方向为北东—南西方向，在应力集中的兴古潜山带，裂缝发育，储层净毛比高，储层发育程度与埋深无明显对应关系；变质岩从片麻岩、混合片麻岩到混合花岗岩，岩浆岩由基性、中性岩浆岩到酸性岩浆岩，储层发育程度逐渐变好，而角闪石岩、斜长角闪岩、煌斑岩脉和辉绿岩脉不发育储层，为非储集岩，为兴马变质岩潜山油气藏的勘探开发提供了有利的技术支持。
After decades of exploration and development, Liaohe Oilfield has found a large numberof complex lithologic reservoirs such as carbonate rocks, igneous, metamorphic and so on,and has obtained high-yield industrial oil flow in such complex lithologic reservoirs, andbenefits a lot from it. During the past3years, Liaohe depressed Archean group metamorphicrock buried hill is a very important area to increase proven reserves in Liaohe oilfield.XingLongtai buried hill reservoir produced a million tons capacity has prompt up in2010.Although complex lithologic reservoir logging interpretation method has developed a lot bothin and outside our country, there are still some problems to be settled urgently in Archeangroup metamorphic rock buried hill reservoir logging evaluation. In this paper, we use “corescale logging technology”, comprehensive theoretical method and simulation wellexperimental method to set up the automatic lithology identification method, rock andmineral content calculation, the matrix porosity and secondary porosity calculation methodand fracture identification and fracture parameters calculation method.
We use mod logging cuttings, rotary sidewall coring and the slice core identificationresult of XingGu, ChenGu, MaGu buried hill, combined with the logging responsecharacteristics and using the extreme variance cluster analysis method to identify the twodifferent logging curves(Jagged and flat-shaped) of the different lithology. We also use2D,3Dvisualization technology in crossplot method, fuzzy mathematics, neural networks andcomprehensive analysis method to identify the lithology automatically. We have dealt withactual logging data to identify the7lithology(mixed granite class, mixed gneiss, gneisses,amphibolites, granite, diorite and lamprophyre class), and the lithology identification result ofthe25well is90%or more meet with the actual result. Based on the core experimental data,we can accurately calculate the rock mineral content, matrix porosity and oil/gas saturationby using multi-mineral model. Based on the acoustoelectric imaging logging experimentaldata, we use porosity spectrum analysis method to explain the matrix porosity and secondaryporosity, and then combined with the imaging logging, multipole array acoustic logging,cross-dipole sonic log to identify the buried hill crack. Based on the acoustoelectricattenuation theory, combined with simulation well crack imaging logging experiment, derive the crack width calculation formula, and then use test oil, trial mining data andcomprehensive logging data to set up the buried hill reservoir evaluation standard. Combinedwith the trial mining data, mod logging and sidewall coring data, using comprehensivelogging data to evaluate the effectiveness of buried hill reservoir. After comprehensive study,we found that: mixed granite, mixed gneiss and diorite class in XingMa buried hill reservoiris with high porosity and permeability. The lithology intrusive rocks thickness is increasedfrom MaGu to XingGu and then ChenGu buried hills. In north part ChenGu buried hill, it ismainly the neutral acid intrusive rocks, and in the middle part XingGu buried hill, it is mainlygneiss and migmatite, in the south MaGu buried hill, it is mainly migmatite. The groundstress of XingMa buried hill tectonic zone is from North-east to south-west. In XingGuburied hill, the stress concentration area, crack developed, the reservoir net gross is high,there is no obvious correspondence between reservoir develop extent and buried depth. Thereservoir develop extent is becoming worse with the order mixed granite, mixed gneiss andgneiss in the metamorphic class, and the order acid magmatic rocks, neutral magmatic rocksand mafic magmatic rocks in the magmatic rock class. Hornblendite, amphibolite rocks,lamprophyre and diabase dikes are undeveloped reservoirs, they are non-reservoir rocks, andand provide beneficial support in exploration of metamorphic buried hill reservoir.
引文
[1] Al-Chalabi，M. An analysis of stacking RMS Average and Interval Velocities Over a HorizontallyLayered Ground[J].Geophysical Prospecting，1974，22：458～475.
[2] A M Sibbit, O Faivre,1985,The Dual Laterolog Response in Fracture rocks, SPWLA26th Symposium.
[3] BRIE A，ENDO T，et a1.Quantitative formation permeability,evaluation from Stoneley waves[C].SPEReservoir Eval＆Eng．2000．
[4] Bill Kenyon. Nuclear Magnetic Resonance Imaging Technology for the21stCentury[J]. OilfieldReview，Autumn1995:19～33.
[5] Benoit W R, Sethi D K, Fertl W H. Geothermal well log analysis at Desert Peak,Neaada[J].Transactions of SPWAL21stAnnual Lagging Symposium,1980,AA.
[6] B R, Marie Odile.The Zagor structural investigation for deep petroleum traps. Geology Arabia,2000,Vol5,(1):59～60.
[7] Davies，D．，et al．“Azimuthal Resistivity Imaging：A New Generation Laterolog，”SPE FormationEvaluation，(Sept1994)165～174.
[8] Delhomme，J P, Bedford, J etc.Permeability and porosity upscaling in the near-wellbore domain thecontribution of borehole electrical images. Society of Petroleum Engineers,1996，21(1):89～101.
[9] Ehrenberg-S-N. Factors controlling porosity in the Upper Carboniferous–Lower Permian carbonatestrata of the Barents Sea.AAPGBulletni.2004，88(12):1653～1676.
[10] ENDO T，BRIE A，et a1．Fracture and permeability evaluation in a fault zone from sonic waveformdata[C]．SPWLA38thAnnual Logging Symposium，1997．
[11] Hornby B.E.，Luthi S.M.，An integrated interpretation of fracture apertures computed from electricalborehole scans and reflected Stoneley waves，Geological Society Special Publication，1992，（65）:185～198.
[12] Hindle A D. Petroleum migration pathways and charge concentration：A three-dimensionalmodel[J].AAPG Bulletin，1997，81(9)：1451～1481.
[13] Horby，B.E，Luthi，s m. An integrated interpretation of fracture aperture computed from electricalborehole scans and reflected stoneley waves[J].an integration interpretation the log Analyst，1992，33（1）：158～159.
[14] J Durhuus，B S Aadnoy.In situ stress from inversion of fracturing data from oil wells and boreholeimage logs[J].Journal of Petroleum Science and Engineering,2003,38:121～130．
[15] J.L.Arroyo Franco, M.A.Mercado Ortiz. Sonic Investigations In and Around the Borehole[J]. OilfieldReview, Spring2006:14～33.
[16] Jakob B.U, Haldorsen，David Linton Johnson. Borehole Acoustic Waves[J]. Oilfield Review，Spring2006:34～43.
[17] Kennedy-M-C. Solutions to some Problems in the analysis of well logs in carbonate rocks. AAPGMethods in Exploration Series，13:2002.
[18] Kuland B R. Dean S. L. Ward B. J. Fractured Core Analysis: Interpretation Logging and use ofNatural and induced fractures in core. AAPG Methods in exploration series, No.8Tulsa, Oklahoma,1990.
[19] Khoshbakht F, Memarian H and Mohammadnia M.2009.Comparison of Norwegian formation'sfractures, derived from image log [J].Journal of Petroleum Science and Engineering,67:65～74.
[20] Kohonen T. The Self-organizing map[J]. Proceedings of the IE，1990，78(9):1464～1480.
[21] Khatchikian A. Log Evaluation of Oil-Bearing Igneous Rocks[J].Transactions of SPWLA23th Annuallagging Symposium，1982，AA.
[22] Landes K.K. et al. Petroleum Resource in Basement Bocks.Bull Of A.A.P.G.1960,Vol44,NO.10:1682～1691.
[23] Luthi S M, Souhaite P. Fracture apertures from electrical borehole scans[J]. Geophysics,1990,55(3)：821～833.
[24] Masanori Ienaga, Lisa C. McNeill etc.Borehole image analysis of the Nankai Accretionary Wedge，ODP Leg196，Structural and stress studies[J].Tectonophysics，2006，426：207～220．
[25] Mahmood Akbar, et al. A Snapshot of Carbonate Reservoir Evaluation [J].Oilfield Review,2001,21.
[26] Martin Brudy, Halvor, Kjorholt. Stress orientation on the Norwegian continental shelf Derived fromborehole failures observed in high-resolution borehole imaging logs[J].Tectonophysics,2001,337:65～84.
[27] Ian Bryant, et al. Understanding Uncertainty [J].Oilfield Review,2002,2.
[28] Pollard, D. D&Aydin.A Progress in Understanding Jointing over the Past Century. GSA Bulletin.1988,100(6):1181～12041.
[29] Powers S, Reflected Buried Hills and Their Importance in Petroleum Geology. EconomicGeology，1922，17（4）：23～259.
[30] Pete Hegeman，Jacques Pelissier. Production Logging for Reservoir Testing[J].Oilfield Review，Summer1997:16～20.
[31] Pan B Z，Xue L F, Huang B Z. Evaluation volcanic reservoirs with“QAPM mineral model”usinggenetic algorithm[J].Applied Geophysics，2008，5(1):1～8.
[32] Ramamoorthy R. A look at Spectroscopy [J].Formation Evaluation Review,2001,2(6):1～3.
[33] Rigby F A. Fracture identification in an igneous geothermal reservoir Surprise Valley，California[J].Transactions of SPWLA21stAnnual Lagging Symposium，1980，Z.
[34] Sait Ismail Ozkaya.Fractures length estimation from borehole image logs[J].Mathematical Geology，2003，35(6)：737～753．
[35] Suan HL, Michael MH. Application of Nuclear Spectroscopy Logs to Derivation of Formation MatrixDensity (A).41stAnnual Logging Symposium of the Society of Professional Well Log Analysts〔C〕.Dallas, Texas: Society of Professional Well Log Analysis,2000,1～12.
[36] Sanyal S K，Juprasert S，Jusbasche M. An evaluation of rhyolite-basalt-volcanic ash sequence fromwell logs[J].Transactions of SPWLA21stAnnual lagging Symposium,1979，TT.
[37] Tang, XM. Predictive Processing of Array Acoustic Waveform Data[J].Geophysics,1997,62:1710～1714.
[38] Tokhmchi B, Memarian H, Rezaee M R.2010.Estimation of the fracture density in fractured zonesusing petrophysical logs[J].Journal of Petroleum Science and Engineering,(in press),doi:10.1016/j.petrol.2010.03.018.
[39] Vernik L, Zoback M D.Estimation of the maximum horizontal principal stress magnitude from stressinduced well bore breakout in the Cajon pass scientific research borehole[J]． Journal ofGeophysical Research,1992,97(b4):5109～5119．
[40] ZIOLKOWSKIS A． A method for calculating the output pressure waveform from anair-gun[J].Geophys J R Astr Soc,1970,21(2):137～161.
[41]曹鉴华.塔河油田奥陶系复杂碳酸盐岩储层测井解释与评价方法研究[M].成都：西南石油学院，2004.
[42]常书豪.太古界潜山地层岩性识别方法[J].科技信息，2011.
[43]程华国，袁祖贵.用地层元素测井(ECS)资料评价复杂地层岩性变化[J].核电子学与探测技术，2005，25(3):233～238.
[44]陈钢花,范宜仁,代诗华.火山岩储层测井评价技术[J].中国海上油气(地质)，2004，14(6):422～428.
[45]陈钢花,吴文圣,毛克文.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.
[46]崔晓娟.大民屯凹陷太古界潜山储层测井评价方法研究[J].石油地质与工程，2008,22（4）：45～48.
[47]崔云江.渤海锦州25_1南油田太古界潜山储层测井评价技术[M].东营：中国石油大学（华东），2008.
[48]崔秀梅，王建瑞，李清，等.冀中坳陷新河凸起变质岩油气藏成藏条件探讨[J].特质油气藏,2011.
[49]丁秀春.测井响应在火成岩储层研究中的应用[J].特种油气藏，2003，10(1):69～72.
[50]董经利.多极子阵列声波测井资料处理及应用[J].测井技术,2009,33(2):115~119.
[51]顿铁军．酒西盆地鸭儿峡地区变质岩储层研究[J].西北地质，1995，16(2)：50～57．
[52]代诗华，罗兴平，王军，等.火山岩储集层测井响应与解释方法[J].新疆石油地质，1998，19(6):465～469.
[53]范宜仁,黄隆基,代诗华.交会图技术在火成岩岩性和裂缝识别中的应用[J].测井技术，1999,23(l):53-56.
[54]付崇清.辽河油田变质岩潜山测井综合评价[J].大庆石油地质与开发，2007,26(5):138～142.
[55]冯雪龙.清西油田下白垩统下沟组测井沉积微相及储层物性参数研究[M].成都：西南石油学院，2005.
[56]高世臣,郑丽辉,刑玉忠.辽河盆地太古界变质岩油气储层特征[J].石油天然气学报，2004.
[57]胡治华,杨申谷,夏锦芬，等.在火山岩相中的测井曲线特征及应用[J].天然气勘探与开发，2007,30（3）.
[58]胡杰,雍静,李建波，等.基于神经网络的间谐波电源对荧光灯闪变影响的研究[J].低压电器，2008.
[59]何宏.气测录井检测评价油气储层技术研究[D].天津：天津大学，2003.
[60]黄布宙，潘保芝.松辽盆地北部深层火成岩测井响应特征及岩性划分[J].石油物探，2001，40(3):42～47.
[61]姜广义.兴隆台油田太古界潜山天然裂缝预测方法研究[M].大庆：东北石油大学，2010.
[62]姜延武,严桂林，等.人工神经网络系统在储层评价中的应用[J].录井技术，2001.
[63]纪荣艺,樊洪海,杨雄文，等.测井曲线自动分层模型设计与实现[J].石油钻探技术，2007.
[64]孔令福.辽河盆地东部凹陷火山岩储层测井评价方法研究[M].大庆:大庆石油学院，2003.
[65]赖福强.应用声电成像测井进行裂缝检测与评价研究[M].北京：中国石油大学，2007.
[66]罗静兰，曲志浩，孙卫，等.风化店火山岩岩相、储集性与油气的关系[J].石油学报，1996，17(1):32～39.
[67]刘斌.冀北水泉沟—后沟偏碱性侵入杂岩体的成矿特征[J].地质与资源，2001.
[68]刘伟.复杂低渗透油气储层测井评价[D].北京：中国石油大学，2009.
[69]刘全稳.测井神经网络技术综述[J].石油地球物理勘探,1996,31(增刊):64～67.
[70]刘为付,孙立新,刘双龙，等.模糊数学识别火山岩岩性[J].特种油气藏.2002,9(1):14～17.
[71]刘为付.模糊数学识别深层潜山碳酸盐岩岩性[J].新疆石油学院学报.2003,15(3):35～39.
[72]刘曙光,李铁军.元素俘获测井(ECS)在辽河太古界潜山地层中的应用[J].内蒙古石油化工，2011,14:120～123.
[73]刘玲,黄玲,张晓东，等.用自组织映射方法进行油气检测[J].石油物探,1994,33(4):56～64.
[74]刘为付，孙立新，刘双龙，等.模糊数学识别火山岩岩性[J].特种油气藏，2002，9(1):14～17.
[75]刘兴周.辽河油田西部及大民屯凹陷潜山储集层识别及储层特征[J].石油地质与工程,2007,21(4):5～8.
[76]李辉.克拉玛依油田三—2区克下组油藏精细描述及剩余油挖潜研究[D].成都：成都理工大学，2010.
[77]李晓光，刘宝鸿，蔡国钢.辽河坳陷变质岩潜山内幕油藏成因分析[J]．特种油气藏，2009，16(4)：1～5．
[78]李洪霞.兴隆台潜山带油藏评价与开发方式研究[M].大庆：东北石油大学，2010.
[79]李宁，陶宏根，刘传平.2009酸性火山岩测井解释理论、方法与应用.北京：石油工业出版社.
[80]李舟波，王祝文.科学钻探中的元素测井技术[J].地学前缘，1998，5(l2):119～130.
[81]李善军，肖承文，汪涵明，等.裂缝的双侧向测井响应的数学模型及裂缝孔隙度的定量解释[J].地球物理学报，1996，39(6):845～852.
[82]潘保芝，闻桂京，昊海波.对应分析确定松辽盆地北部深层火成岩岩性[J].大庆石油地质与开发，2003，22(1):7～9.
[83]潘保芝.裂缝性火成岩储层测井评价的理论与方法研究[D].长春:吉林大学，2002.
[84]彭敦陆,徐士进，等.神经网络专家系统在预测单井日产量上的应用研究[J].石油实验地质，1999.
[85]乔德新.成像测井资料定量计算方法研究及软件开发[D].北京：中国地质大学,2005.
[86]宋子齐，李伟峰，唐长久，等.利用自然电位与自然伽马测井曲线划分沉积相带及储层分布[J].地球物理学进展，2009，24(2):651-656.
[87]孙娜.辽河盆地兴马太古界潜山的岩性识别与储层划分[J].石油地质与工程,2007,21(4):20～26.
[88]孙立勋.兴古潜山变质岩油藏储层特征研究[J].长江大学学报（自然科学版），2011.
[89]舒萍,曲延明等.松辽盆地火山岩储层裂缝地质特征与地球物理识别[J].吉林大学学报（地球科学报），2007.
[90]苏培东.贵州赤水地区二、三叠系储层构造解析及裂缝预测研究[M].成都：西南石油大学,2004.
[91]苏培东,秦启荣,黄润秋.储层裂缝预测研究现状与展望[J].西南石油学院院报，2005.
[92]童亨茂.储层裂缝描述与预测研究进展[J].新疆石油学院学报,2004,16(2):9～13.
[93]王岫岩,许少华,王贵文.模糊模式识别在复杂岩性划分中的应用[J].大庆石油地质与开发.1998,17(2):17～51.
[94]王岩楼.葡西地区特低渗透油藏流体识别技术综合研究[D].杭州：浙江大学，2007.
[95]王振杰.声电成像测井在裂缝性储层中的定量解释应用研究[D].北京：中国石油大学，2010.
[96]王敏.基于二维成像测井的裂缝性储层测井评价方法研究[D].北京：中国石油大学，2010.
[97]吴琼,林冬萍,于春燕，等.新立油田低渗透油层裂缝测井识别方法[J].大庆石油地质与开发,2007,26(2):112~115.
[98]吴海燕,朱留方.成像、核磁共振测井在埕北裂缝性储层评价中的应用[J].石油与天然气地质，2002.
[99]薛林福,潘保芝.自组织神经网络自动识别岩相[J].长春科技大学学报,1999,29(2):144～147.
[100]许风光,邓少贵,范宜仁等.火成岩储层测井评价进展综述[J].勘探地球物理进展,2006,29(4):239～243.
[101]尤桂彬.东胜堡西侧低潜山太古界变质岩储层研究[N].科技创新导报，2010（5）.
[102]阎新民.应用计算机进行准噶尔盆地火山岩裂缝识别[J].石油地球物理勘探，1994，29(增刊2):139～143.
[103]叶义平,盛云霞，等.横向测井资料的孔隙度测井解释方法研究[J].石油天然气学报，2005.
[104]杨宇,康毅力,康志宏.多矿物测井解释模型及其在砂泥岩地层测井解释中的应用[J].新疆地质,2006,24(4):441~446.
[105]于景才,原福堂,邱辉丽，等.测井新技术在复杂岩性地层中的地质应用[J].石油天然气学报,2005.
[106]原福堂,徐兵,汪浩,伍东，等.声电成像测井解释处理软件的开发与应用[J].测井技术，2005.
[107]岳暐.辽河太古界潜山储层测井评价研究[M].北京：中国石油大学，2011.
[108]袁爱武,郑晓松,于洪波.应用人工神经网络预测油田注采比[J].大庆石油地质与开发，2005.
[109]赵建，高福红.测井资料交会图法在火山岩岩性识别中的应用[J].世界地质，2003，22(2):136～140.
[110]赵为永，苟迎春，严焕德.应用地层倾角测井进行裂缝识别研究[J].青海石油，2009,27（3）：5～8.
[111]张振城,孙建孟,施振飞，等.测井资料评价次生孔隙的方法、原理及实例[J].沉积学报，2005,4（23）：613～618.
[112]张治国,杨毅恒,夏立显.自组织特征映射神经网络在测井岩性识别中的应用[J].地球物理学进展，2005，20(2):332-336.
[113]张庆国，卢颖忠.风化店火山岩有藏裂缝识别研究[J].西北大学学报(自然版)，1995，25(6):693～696.
[114]张以明.冀中饶阳凹陷下第三系沙河街组第三段砂岩次生孔隙形成机制.石油与天然气地质,1994,15(3):208～215.
[115]张琴,钟大康,朱筱敏，等.东营凹陷下第三系碎屑岩储层孔隙演化与次生孔隙成因.石油与天然气地质,2003,24(3):281～285.
[116]张明禄,石玉江.复杂孔隙结构砂岩储层岩电参数研究[J].测井技术,2005,29(5):446~448.
[117]张福功.辽河坳陷西部凹陷兴马潜山储层研究[M].大庆石油学院，2008.
[118]张广杰,刘明新,武若霞.神经网络在油田动态预测方面的应用[J].石油学报，1997.
[119]周波,李舟波,潘保芝.火山岩岩性识别方法研究[J].吉林大学学报(地球科学版)，2005，35(3):394～397.
[120]朱爱丽，吴伯福，武江.火成岩的测井评价—大港油田枣北地区应用实例[J].测井技术，1997，21(5):345～350.
[121]朱留方,吴海燕,翟勇.太古界变质岩储集层测井资料综合评价[J].地质与勘探,2005,25(11):39～42.
[122]朱怡翔,廖明书,刘明高，等.地球物理测井的裂缝评价方法[J].国外测井技术,2000.
[123]卓壮.兴隆台太古界变质岩潜山储层测井评价研究〔硕士论文〕[M].大庆：东北石油大学，2010.
[124]邹长春，严成信，李学文.神经网络在枣北地区火成岩储层测井解释中的应用[J].石油地球物理勘探，1997，32(增刊2):27～33.
[125]钟大康,朱筱敏,蔡进功，等.沾化凹陷下第三系次生孔隙纵向分布规律.石油与天然气地质,2003,24(3):286～290.
[2] A M Sibbit, O Faivre,1985,The Dual Laterolog Response in Fracture rocks, SPWLA26th Symposium.
[3] BRIE A，ENDO T，et a1.Quantitative formation permeability,evaluation from Stoneley waves[C].SPEReservoir Eval＆Eng．2000．
[4] Bill Kenyon. Nuclear Magnetic Resonance Imaging Technology for the21stCentury[J]. OilfieldReview，Autumn1995:19～33.
[5] Benoit W R, Sethi D K, Fertl W H. Geothermal well log analysis at Desert Peak,Neaada[J].Transactions of SPWAL21stAnnual Lagging Symposium,1980,AA.
[6] B R, Marie Odile.The Zagor structural investigation for deep petroleum traps. Geology Arabia,2000,Vol5,(1):59～60.
[7] Davies，D．，et al．“Azimuthal Resistivity Imaging：A New Generation Laterolog，”SPE FormationEvaluation，(Sept1994)165～174.
[8] Delhomme，J P, Bedford, J etc.Permeability and porosity upscaling in the near-wellbore domain thecontribution of borehole electrical images. Society of Petroleum Engineers,1996，21(1):89～101.
[9] Ehrenberg-S-N. Factors controlling porosity in the Upper Carboniferous–Lower Permian carbonatestrata of the Barents Sea.AAPGBulletni.2004，88(12):1653～1676.
[10] ENDO T，BRIE A，et a1．Fracture and permeability evaluation in a fault zone from sonic waveformdata[C]．SPWLA38thAnnual Logging Symposium，1997．
[11] Hornby B.E.，Luthi S.M.，An integrated interpretation of fracture apertures computed from electricalborehole scans and reflected Stoneley waves，Geological Society Special Publication，1992，（65）:185～198.
[12] Hindle A D. Petroleum migration pathways and charge concentration：A three-dimensionalmodel[J].AAPG Bulletin，1997，81(9)：1451～1481.
[13] Horby，B.E，Luthi，s m. An integrated interpretation of fracture aperture computed from electricalborehole scans and reflected stoneley waves[J].an integration interpretation the log Analyst，1992，33（1）：158～159.
[14] J Durhuus，B S Aadnoy.In situ stress from inversion of fracturing data from oil wells and boreholeimage logs[J].Journal of Petroleum Science and Engineering,2003,38:121～130．
[15] J.L.Arroyo Franco, M.A.Mercado Ortiz. Sonic Investigations In and Around the Borehole[J]. OilfieldReview, Spring2006:14～33.
[16] Jakob B.U, Haldorsen，David Linton Johnson. Borehole Acoustic Waves[J]. Oilfield Review，Spring2006:34～43.
[17] Kennedy-M-C. Solutions to some Problems in the analysis of well logs in carbonate rocks. AAPGMethods in Exploration Series，13:2002.
[18] Kuland B R. Dean S. L. Ward B. J. Fractured Core Analysis: Interpretation Logging and use ofNatural and induced fractures in core. AAPG Methods in exploration series, No.8Tulsa, Oklahoma,1990.
[19] Khoshbakht F, Memarian H and Mohammadnia M.2009.Comparison of Norwegian formation'sfractures, derived from image log [J].Journal of Petroleum Science and Engineering,67:65～74.
[20] Kohonen T. The Self-organizing map[J]. Proceedings of the IE，1990，78(9):1464～1480.
[21] Khatchikian A. Log Evaluation of Oil-Bearing Igneous Rocks[J].Transactions of SPWLA23th Annuallagging Symposium，1982，AA.
[22] Landes K.K. et al. Petroleum Resource in Basement Bocks.Bull Of A.A.P.G.1960,Vol44,NO.10:1682～1691.
[23] Luthi S M, Souhaite P. Fracture apertures from electrical borehole scans[J]. Geophysics,1990,55(3)：821～833.
[24] Masanori Ienaga, Lisa C. McNeill etc.Borehole image analysis of the Nankai Accretionary Wedge，ODP Leg196，Structural and stress studies[J].Tectonophysics，2006，426：207～220．
[25] Mahmood Akbar, et al. A Snapshot of Carbonate Reservoir Evaluation [J].Oilfield Review,2001,21.
[26] Martin Brudy, Halvor, Kjorholt. Stress orientation on the Norwegian continental shelf Derived fromborehole failures observed in high-resolution borehole imaging logs[J].Tectonophysics,2001,337:65～84.
[27] Ian Bryant, et al. Understanding Uncertainty [J].Oilfield Review,2002,2.
[28] Pollard, D. D&Aydin.A Progress in Understanding Jointing over the Past Century. GSA Bulletin.1988,100(6):1181～12041.
[29] Powers S, Reflected Buried Hills and Their Importance in Petroleum Geology. EconomicGeology，1922，17（4）：23～259.
[30] Pete Hegeman，Jacques Pelissier. Production Logging for Reservoir Testing[J].Oilfield Review，Summer1997:16～20.
[31] Pan B Z，Xue L F, Huang B Z. Evaluation volcanic reservoirs with“QAPM mineral model”usinggenetic algorithm[J].Applied Geophysics，2008，5(1):1～8.
[32] Ramamoorthy R. A look at Spectroscopy [J].Formation Evaluation Review,2001,2(6):1～3.
[33] Rigby F A. Fracture identification in an igneous geothermal reservoir Surprise Valley，California[J].Transactions of SPWLA21stAnnual Lagging Symposium，1980，Z.
[34] Sait Ismail Ozkaya.Fractures length estimation from borehole image logs[J].Mathematical Geology，2003，35(6)：737～753．
[35] Suan HL, Michael MH. Application of Nuclear Spectroscopy Logs to Derivation of Formation MatrixDensity (A).41stAnnual Logging Symposium of the Society of Professional Well Log Analysts〔C〕.Dallas, Texas: Society of Professional Well Log Analysis,2000,1～12.
[36] Sanyal S K，Juprasert S，Jusbasche M. An evaluation of rhyolite-basalt-volcanic ash sequence fromwell logs[J].Transactions of SPWLA21stAnnual lagging Symposium,1979，TT.
[37] Tang, XM. Predictive Processing of Array Acoustic Waveform Data[J].Geophysics,1997,62:1710～1714.
[38] Tokhmchi B, Memarian H, Rezaee M R.2010.Estimation of the fracture density in fractured zonesusing petrophysical logs[J].Journal of Petroleum Science and Engineering,(in press),doi:10.1016/j.petrol.2010.03.018.
[39] Vernik L, Zoback M D.Estimation of the maximum horizontal principal stress magnitude from stressinduced well bore breakout in the Cajon pass scientific research borehole[J]． Journal ofGeophysical Research,1992,97(b4):5109～5119．
[40] ZIOLKOWSKIS A． A method for calculating the output pressure waveform from anair-gun[J].Geophys J R Astr Soc,1970,21(2):137～161.
[41]曹鉴华.塔河油田奥陶系复杂碳酸盐岩储层测井解释与评价方法研究[M].成都：西南石油学院，2004.
[42]常书豪.太古界潜山地层岩性识别方法[J].科技信息，2011.
[43]程华国，袁祖贵.用地层元素测井(ECS)资料评价复杂地层岩性变化[J].核电子学与探测技术，2005，25(3):233～238.
[44]陈钢花,范宜仁,代诗华.火山岩储层测井评价技术[J].中国海上油气(地质)，2004，14(6):422～428.
[45]陈钢花,吴文圣,毛克文.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.
[46]崔晓娟.大民屯凹陷太古界潜山储层测井评价方法研究[J].石油地质与工程，2008,22（4）：45～48.
[47]崔云江.渤海锦州25_1南油田太古界潜山储层测井评价技术[M].东营：中国石油大学（华东），2008.
[48]崔秀梅，王建瑞，李清，等.冀中坳陷新河凸起变质岩油气藏成藏条件探讨[J].特质油气藏,2011.
[49]丁秀春.测井响应在火成岩储层研究中的应用[J].特种油气藏，2003，10(1):69～72.
[50]董经利.多极子阵列声波测井资料处理及应用[J].测井技术,2009,33(2):115~119.
[51]顿铁军．酒西盆地鸭儿峡地区变质岩储层研究[J].西北地质，1995，16(2)：50～57．
[52]代诗华，罗兴平，王军，等.火山岩储集层测井响应与解释方法[J].新疆石油地质，1998，19(6):465～469.
[53]范宜仁,黄隆基,代诗华.交会图技术在火成岩岩性和裂缝识别中的应用[J].测井技术，1999,23(l):53-56.
[54]付崇清.辽河油田变质岩潜山测井综合评价[J].大庆石油地质与开发，2007,26(5):138～142.
[55]冯雪龙.清西油田下白垩统下沟组测井沉积微相及储层物性参数研究[M].成都：西南石油学院，2005.
[56]高世臣,郑丽辉,刑玉忠.辽河盆地太古界变质岩油气储层特征[J].石油天然气学报，2004.
[57]胡治华,杨申谷,夏锦芬，等.在火山岩相中的测井曲线特征及应用[J].天然气勘探与开发，2007,30（3）.
[58]胡杰,雍静,李建波，等.基于神经网络的间谐波电源对荧光灯闪变影响的研究[J].低压电器，2008.
[59]何宏.气测录井检测评价油气储层技术研究[D].天津：天津大学，2003.
[60]黄布宙，潘保芝.松辽盆地北部深层火成岩测井响应特征及岩性划分[J].石油物探，2001，40(3):42～47.
[61]姜广义.兴隆台油田太古界潜山天然裂缝预测方法研究[M].大庆：东北石油大学，2010.
[62]姜延武,严桂林，等.人工神经网络系统在储层评价中的应用[J].录井技术，2001.
[63]纪荣艺,樊洪海,杨雄文，等.测井曲线自动分层模型设计与实现[J].石油钻探技术，2007.
[64]孔令福.辽河盆地东部凹陷火山岩储层测井评价方法研究[M].大庆:大庆石油学院，2003.
[65]赖福强.应用声电成像测井进行裂缝检测与评价研究[M].北京：中国石油大学，2007.
[66]罗静兰，曲志浩，孙卫，等.风化店火山岩岩相、储集性与油气的关系[J].石油学报，1996，17(1):32～39.
[67]刘斌.冀北水泉沟—后沟偏碱性侵入杂岩体的成矿特征[J].地质与资源，2001.
[68]刘伟.复杂低渗透油气储层测井评价[D].北京：中国石油大学，2009.
[69]刘全稳.测井神经网络技术综述[J].石油地球物理勘探,1996,31(增刊):64～67.
[70]刘为付,孙立新,刘双龙，等.模糊数学识别火山岩岩性[J].特种油气藏.2002,9(1):14～17.
[71]刘为付.模糊数学识别深层潜山碳酸盐岩岩性[J].新疆石油学院学报.2003,15(3):35～39.
[72]刘曙光,李铁军.元素俘获测井(ECS)在辽河太古界潜山地层中的应用[J].内蒙古石油化工，2011,14:120～123.
[73]刘玲,黄玲,张晓东，等.用自组织映射方法进行油气检测[J].石油物探,1994,33(4):56～64.
[74]刘为付，孙立新，刘双龙，等.模糊数学识别火山岩岩性[J].特种油气藏，2002，9(1):14～17.
[75]刘兴周.辽河油田西部及大民屯凹陷潜山储集层识别及储层特征[J].石油地质与工程,2007,21(4):5～8.
[76]李辉.克拉玛依油田三—2区克下组油藏精细描述及剩余油挖潜研究[D].成都：成都理工大学，2010.
[77]李晓光，刘宝鸿，蔡国钢.辽河坳陷变质岩潜山内幕油藏成因分析[J]．特种油气藏，2009，16(4)：1～5．
[78]李洪霞.兴隆台潜山带油藏评价与开发方式研究[M].大庆：东北石油大学，2010.
[79]李宁，陶宏根，刘传平.2009酸性火山岩测井解释理论、方法与应用.北京：石油工业出版社.
[80]李舟波，王祝文.科学钻探中的元素测井技术[J].地学前缘，1998，5(l2):119～130.
[81]李善军，肖承文，汪涵明，等.裂缝的双侧向测井响应的数学模型及裂缝孔隙度的定量解释[J].地球物理学报，1996，39(6):845～852.
[82]潘保芝，闻桂京，昊海波.对应分析确定松辽盆地北部深层火成岩岩性[J].大庆石油地质与开发，2003，22(1):7～9.
[83]潘保芝.裂缝性火成岩储层测井评价的理论与方法研究[D].长春:吉林大学，2002.
[84]彭敦陆,徐士进，等.神经网络专家系统在预测单井日产量上的应用研究[J].石油实验地质，1999.
[85]乔德新.成像测井资料定量计算方法研究及软件开发[D].北京：中国地质大学,2005.
[86]宋子齐，李伟峰，唐长久，等.利用自然电位与自然伽马测井曲线划分沉积相带及储层分布[J].地球物理学进展，2009，24(2):651-656.
[87]孙娜.辽河盆地兴马太古界潜山的岩性识别与储层划分[J].石油地质与工程,2007,21(4):20～26.
[88]孙立勋.兴古潜山变质岩油藏储层特征研究[J].长江大学学报（自然科学版），2011.
[89]舒萍,曲延明等.松辽盆地火山岩储层裂缝地质特征与地球物理识别[J].吉林大学学报（地球科学报），2007.
[90]苏培东.贵州赤水地区二、三叠系储层构造解析及裂缝预测研究[M].成都：西南石油大学,2004.
[91]苏培东,秦启荣,黄润秋.储层裂缝预测研究现状与展望[J].西南石油学院院报，2005.
[92]童亨茂.储层裂缝描述与预测研究进展[J].新疆石油学院学报,2004,16(2):9～13.
[93]王岫岩,许少华,王贵文.模糊模式识别在复杂岩性划分中的应用[J].大庆石油地质与开发.1998,17(2):17～51.
[94]王岩楼.葡西地区特低渗透油藏流体识别技术综合研究[D].杭州：浙江大学，2007.
[95]王振杰.声电成像测井在裂缝性储层中的定量解释应用研究[D].北京：中国石油大学，2010.
[96]王敏.基于二维成像测井的裂缝性储层测井评价方法研究[D].北京：中国石油大学，2010.
[97]吴琼,林冬萍,于春燕，等.新立油田低渗透油层裂缝测井识别方法[J].大庆石油地质与开发,2007,26(2):112~115.
[98]吴海燕,朱留方.成像、核磁共振测井在埕北裂缝性储层评价中的应用[J].石油与天然气地质，2002.
[99]薛林福,潘保芝.自组织神经网络自动识别岩相[J].长春科技大学学报,1999,29(2):144～147.
[100]许风光,邓少贵,范宜仁等.火成岩储层测井评价进展综述[J].勘探地球物理进展,2006,29(4):239～243.
[101]尤桂彬.东胜堡西侧低潜山太古界变质岩储层研究[N].科技创新导报，2010（5）.
[102]阎新民.应用计算机进行准噶尔盆地火山岩裂缝识别[J].石油地球物理勘探，1994，29(增刊2):139～143.
[103]叶义平,盛云霞，等.横向测井资料的孔隙度测井解释方法研究[J].石油天然气学报，2005.
[104]杨宇,康毅力,康志宏.多矿物测井解释模型及其在砂泥岩地层测井解释中的应用[J].新疆地质,2006,24(4):441~446.
[105]于景才,原福堂,邱辉丽，等.测井新技术在复杂岩性地层中的地质应用[J].石油天然气学报,2005.
[106]原福堂,徐兵,汪浩,伍东，等.声电成像测井解释处理软件的开发与应用[J].测井技术，2005.
[107]岳暐.辽河太古界潜山储层测井评价研究[M].北京：中国石油大学，2011.
[108]袁爱武,郑晓松,于洪波.应用人工神经网络预测油田注采比[J].大庆石油地质与开发，2005.
[109]赵建，高福红.测井资料交会图法在火山岩岩性识别中的应用[J].世界地质，2003，22(2):136～140.
[110]赵为永，苟迎春，严焕德.应用地层倾角测井进行裂缝识别研究[J].青海石油，2009,27（3）：5～8.
[111]张振城,孙建孟,施振飞，等.测井资料评价次生孔隙的方法、原理及实例[J].沉积学报，2005,4（23）：613～618.
[112]张治国,杨毅恒,夏立显.自组织特征映射神经网络在测井岩性识别中的应用[J].地球物理学进展，2005，20(2):332-336.
[113]张庆国，卢颖忠.风化店火山岩有藏裂缝识别研究[J].西北大学学报(自然版)，1995，25(6):693～696.
[114]张以明.冀中饶阳凹陷下第三系沙河街组第三段砂岩次生孔隙形成机制.石油与天然气地质,1994,15(3):208～215.
[115]张琴,钟大康,朱筱敏，等.东营凹陷下第三系碎屑岩储层孔隙演化与次生孔隙成因.石油与天然气地质,2003,24(3):281～285.
[116]张明禄,石玉江.复杂孔隙结构砂岩储层岩电参数研究[J].测井技术,2005,29(5):446~448.
[117]张福功.辽河坳陷西部凹陷兴马潜山储层研究[M].大庆石油学院，2008.
[118]张广杰,刘明新,武若霞.神经网络在油田动态预测方面的应用[J].石油学报，1997.
[119]周波,李舟波,潘保芝.火山岩岩性识别方法研究[J].吉林大学学报(地球科学版)，2005，35(3):394～397.
[120]朱爱丽，吴伯福，武江.火成岩的测井评价—大港油田枣北地区应用实例[J].测井技术，1997，21(5):345～350.
[121]朱留方,吴海燕,翟勇.太古界变质岩储集层测井资料综合评价[J].地质与勘探,2005,25(11):39～42.
[122]朱怡翔,廖明书,刘明高，等.地球物理测井的裂缝评价方法[J].国外测井技术,2000.
[123]卓壮.兴隆台太古界变质岩潜山储层测井评价研究〔硕士论文〕[M].大庆：东北石油大学，2010.
[124]邹长春，严成信，李学文.神经网络在枣北地区火成岩储层测井解释中的应用[J].石油地球物理勘探，1997，32(增刊2):27～33.
[125]钟大康,朱筱敏,蔡进功，等.沾化凹陷下第三系次生孔隙纵向分布规律.石油与天然气地质,2003,24(3):286～290.