辽河盆地东部凹陷火山岩储层测井评价方法研究
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摘要
辽河盆地火山岩分布广泛，经过近几年的努力勘探，相继发现了许多储量丰富的火山岩油藏，至2002年底，在火山岩储层中已上报探明石油地质储量3169×10~4t，并且在东部凹陷黄沙坨油田建成了年产25×10~4t以上的生产能力，展示了一定的勘探开发前景。因此积极探索火山岩储层勘探新领域，寻找新的储量接替区已成为一个重要的勘探方向。
火山岩储层属特殊岩性裂缝—孔隙型储层，其储层评价在国内外都是一个较难的课题，尽管国内外有关专家作出了不懈的努力，攻克了许多难关，并积累了一定经验，但由于火山岩储层的复杂性及地质状况、技术发展水平等方面不尽相同，因此在地质认识，勘探开发思路和技术方法上虽然有共同点，但也有各自的特点和差异。本文根据辽河盆地东部凹陷火山岩地质资料，学习和借鉴国内外先进的技术方法和经验，在火山岩岩性识别、储层识别、储层分类、巨厚火山岩期次划分、储层参数确定六个方面，开展了测井评价方法研究，总结出了适合地区特点的、可操作性强的火山岩储层测井评价方法。
岩性识别方面：考虑火山岩岩石矿物种类多、变化大，即岩性复杂的特点，从岩矿分析等岩石物理研究入手，通过岩石测井评价机理深入分析，确定了氧化钾(K_2O)含量与自然伽玛(GR)关系法、M—N交会图法、Φ_(CNL)与Rt交会图法、Φ_(CNL)、ρ_b、Δt与GR交会图法四种方法识别火山岩岩性。尤其是根据K_2O含量与GR关系，创立了自然伽玛曲线定量识别玄武岩与粗面岩的方法，精度高，效果显著。并首次用Φ_(CNL)与Rt交会图法定性划分火山岩的蚀变程度，即Ⅰ类未蚀变或轻度蚀变、Ⅱ类中度蚀变、Ⅲ类强度蚀变、Ⅳ类泥化，储层发育在Ⅱ类和Ⅲ类蚀变的火山岩中，为储层评价提供了基础。
储层识别方面：在岩性准确划分基础上，确定粗面岩为有效储集岩类，在储集岩中以岩心的含油性与物性关系分析研究及试油资料为基础，建立了测井信息与储层特征的对应关系，确定以R_t—Δt、ρ_b-Δt、R_t-Φ_(CNL)等测井交会图方法定量识别储层及定性识别储层相结合的方法。特别在利用声、电成像测井新技术识别裂缝，确定孔隙类型的应用方面，通过结合常规测井及岩心资料，研究分析了成像测井的影响因素，已建立了用声、电成像测井识岩石真假裂缝的模式。确定了以3700测井系列储层定量识别与定性识别相结合，辅以成像测井的储层直观识别方法，提高了储层解释符合率。
储层参数确定方面：通过对矿物成份分析，利用测井交会图技术，准确确定了火山岩岩石骨架的Δt、ρ_b、Φ_(CNL)值，确定了用声波时差Δt计算基质孔隙度的有效方法。通过对声、电成像测井从理论、处理解释到应用研究，建立了用声、电成像测井计算裂缝孔隙度方法，解决了储量计算确定裂缝孔隙度的难题。
储层分类评价方面：根据岩心毛管曲线分类及试油试采资料，首次创立了以R_t—Δt交会图方法对火山岩储层进行分类，该方法结合声电成像测井及储层参数解释结果，并考虑岩石的蚀变程度，实际应用效果突出。
火山岩期次划分方面：对巨厚粗面岩建立了首先用自然伽玛曲线划分明显的期次，然后用电阻率、
大庆石油学院硕士研究生论文
中子孔隙度曲线结合声电成像测井划分小的期次的划分力一法。该方法在对黄沙沱油田火山岩油藏期次划
分评价应用中，取得了较好效果，为分期次评价火山岩奠定了基础。
本文所确定的3700测井系列结合成像测井评价火山岩储层的方法，经在黄沙沱油田火山岩储层中
应用，提高了测井解释符合率，效果显著，适合本地区的地质特点，适用性及可操作性强，;仁且可在其
它地区类似的储层中借鉴或推广。
Volcanic rocks were broadly distributed in Liaohe basin. Through years of exploration, many volcanic rocks with abundance reserves have been discovered. By the end of 2002, submitted proved oil in place in such reservoirs was 3169×104t. In Huangshatuo oilfield of eastern sag, established annual capacity is 25 ×104t, showing certain exploration and development future. Therefore, try to discover volcanic reservoirs and find new reserve replacement area have become an important orientation of exploration.
Volcanic reservoirs belong to special lithology, fractured-porous reservoirs, and the reservoir evaluation is a difficult subject at home and abroad. Although experts have done much effort, solved a lot of problems, had certain experience, and reached agreement in some issues, they still have different opinions in geological understanding, exploration and development thought, and technical methods due to reservoir complexity, various geological conditions and technical level. According to geological data of volcanic rocks in the eastern sag of Liaohe basin, by learning and referencing advanced technical methods and experience at home and abroad, the study of logging evaluation methods has been conducted in six aspects, including identification of volcanic lithology, reservoir identification, reservoir classification, division of stages of massive volcanics, and reservoir parameter determination. Suitable methods of volcanic reservoir logging evaluation for this area have been summarized.
Lithology identification: Because there are various minerals in volcanic rocks, i.e. the lothology is complicated, starting with petrophysical study like rock mineral analysis, through deep analysis of logging evaluation mechanism, four methods have been defined to identify lithology of volcanics, which are relation of K2O content and GR, M-N crossplot, ΦCNL and Rt crossplot, and ΦCNL, ρb, Δt and GR crossplot. Particularly, according to the relation of K2O content and GR, it is established to quantitatively identify basalt and trachyte by gamma ray curve. This method is precise and effective. ΦCNL and Rt crossplot is firstly used to qualitatively classify the alteration degree of volcanic rocks, i.e. unaltered or slightly altered Class I, medium altered Class II, strongly altered Class III, and pelitic Class IV. Reservoirs developed in volcanic rocks of Class II and III alteration, thus providing basis for reservoir evaluation.
Reservoir identification: On the basis of accurate division of lithology, it is determined that trachyte is an effective reservoir rock. Based on analysis of the relation between oil property and physical property of core and production test data, the corresponding relation of logging information and reservoir characteristics is established. It is determined that quantitatively and qualitatively identify reservoir by Rt- Δt,ρh- Δ t and Rt-Φ CNL logging crossplot. Combining with conventional logging and core data, factors affecting image logging are studied and analyzed, and the mode of identifying true and false fractures by acoustic and electric image logging has been established. Conformance rate of reservoir interpretation has been improved by combining quantitative and qualitative identification by 3700 logging series and with the assistant of visual reservoir image logging.
Determination of reservoir parameters: By analyzing mineral composition and using logging crossplot technique, Δ t, ρ b and Φ CNL value of volcanic matrix has been determined, and it is determined to calculate
matrix porosity by A t. Through theoretical study, processing interpretation and application, it has been established to calculate fracture porosity by acoustic and electric image logging, thus solved the problem of porosity determining in reserve calculation.
Reservoir classification and evaluation: According to classification of core capillary curves and data of production test, it has been first established to classify volcanic reservoirs by R,- A t crossplot. This method combines acoustic and electri
火山岩储层属特殊岩性裂缝—孔隙型储层，其储层评价在国内外都是一个较难的课题，尽管国内外有关专家作出了不懈的努力，攻克了许多难关，并积累了一定经验，但由于火山岩储层的复杂性及地质状况、技术发展水平等方面不尽相同，因此在地质认识，勘探开发思路和技术方法上虽然有共同点，但也有各自的特点和差异。本文根据辽河盆地东部凹陷火山岩地质资料，学习和借鉴国内外先进的技术方法和经验，在火山岩岩性识别、储层识别、储层分类、巨厚火山岩期次划分、储层参数确定六个方面，开展了测井评价方法研究，总结出了适合地区特点的、可操作性强的火山岩储层测井评价方法。
岩性识别方面：考虑火山岩岩石矿物种类多、变化大，即岩性复杂的特点，从岩矿分析等岩石物理研究入手，通过岩石测井评价机理深入分析，确定了氧化钾(K_2O)含量与自然伽玛(GR)关系法、M—N交会图法、Φ_(CNL)与Rt交会图法、Φ_(CNL)、ρ_b、Δt与GR交会图法四种方法识别火山岩岩性。尤其是根据K_2O含量与GR关系，创立了自然伽玛曲线定量识别玄武岩与粗面岩的方法，精度高，效果显著。并首次用Φ_(CNL)与Rt交会图法定性划分火山岩的蚀变程度，即Ⅰ类未蚀变或轻度蚀变、Ⅱ类中度蚀变、Ⅲ类强度蚀变、Ⅳ类泥化，储层发育在Ⅱ类和Ⅲ类蚀变的火山岩中，为储层评价提供了基础。
储层识别方面：在岩性准确划分基础上，确定粗面岩为有效储集岩类，在储集岩中以岩心的含油性与物性关系分析研究及试油资料为基础，建立了测井信息与储层特征的对应关系，确定以R_t—Δt、ρ_b-Δt、R_t-Φ_(CNL)等测井交会图方法定量识别储层及定性识别储层相结合的方法。特别在利用声、电成像测井新技术识别裂缝，确定孔隙类型的应用方面，通过结合常规测井及岩心资料，研究分析了成像测井的影响因素，已建立了用声、电成像测井识岩石真假裂缝的模式。确定了以3700测井系列储层定量识别与定性识别相结合，辅以成像测井的储层直观识别方法，提高了储层解释符合率。
储层参数确定方面：通过对矿物成份分析，利用测井交会图技术，准确确定了火山岩岩石骨架的Δt、ρ_b、Φ_(CNL)值，确定了用声波时差Δt计算基质孔隙度的有效方法。通过对声、电成像测井从理论、处理解释到应用研究，建立了用声、电成像测井计算裂缝孔隙度方法，解决了储量计算确定裂缝孔隙度的难题。
储层分类评价方面：根据岩心毛管曲线分类及试油试采资料，首次创立了以R_t—Δt交会图方法对火山岩储层进行分类，该方法结合声电成像测井及储层参数解释结果，并考虑岩石的蚀变程度，实际应用效果突出。
火山岩期次划分方面：对巨厚粗面岩建立了首先用自然伽玛曲线划分明显的期次，然后用电阻率、
大庆石油学院硕士研究生论文
中子孔隙度曲线结合声电成像测井划分小的期次的划分力一法。该方法在对黄沙沱油田火山岩油藏期次划
分评价应用中，取得了较好效果，为分期次评价火山岩奠定了基础。
本文所确定的3700测井系列结合成像测井评价火山岩储层的方法，经在黄沙沱油田火山岩储层中
应用，提高了测井解释符合率，效果显著，适合本地区的地质特点，适用性及可操作性强，;仁且可在其
它地区类似的储层中借鉴或推广。
Volcanic rocks were broadly distributed in Liaohe basin. Through years of exploration, many volcanic rocks with abundance reserves have been discovered. By the end of 2002, submitted proved oil in place in such reservoirs was 3169×104t. In Huangshatuo oilfield of eastern sag, established annual capacity is 25 ×104t, showing certain exploration and development future. Therefore, try to discover volcanic reservoirs and find new reserve replacement area have become an important orientation of exploration.
Volcanic reservoirs belong to special lithology, fractured-porous reservoirs, and the reservoir evaluation is a difficult subject at home and abroad. Although experts have done much effort, solved a lot of problems, had certain experience, and reached agreement in some issues, they still have different opinions in geological understanding, exploration and development thought, and technical methods due to reservoir complexity, various geological conditions and technical level. According to geological data of volcanic rocks in the eastern sag of Liaohe basin, by learning and referencing advanced technical methods and experience at home and abroad, the study of logging evaluation methods has been conducted in six aspects, including identification of volcanic lithology, reservoir identification, reservoir classification, division of stages of massive volcanics, and reservoir parameter determination. Suitable methods of volcanic reservoir logging evaluation for this area have been summarized.
Lithology identification: Because there are various minerals in volcanic rocks, i.e. the lothology is complicated, starting with petrophysical study like rock mineral analysis, through deep analysis of logging evaluation mechanism, four methods have been defined to identify lithology of volcanics, which are relation of K2O content and GR, M-N crossplot, ΦCNL and Rt crossplot, and ΦCNL, ρb, Δt and GR crossplot. Particularly, according to the relation of K2O content and GR, it is established to quantitatively identify basalt and trachyte by gamma ray curve. This method is precise and effective. ΦCNL and Rt crossplot is firstly used to qualitatively classify the alteration degree of volcanic rocks, i.e. unaltered or slightly altered Class I, medium altered Class II, strongly altered Class III, and pelitic Class IV. Reservoirs developed in volcanic rocks of Class II and III alteration, thus providing basis for reservoir evaluation.
Reservoir identification: On the basis of accurate division of lithology, it is determined that trachyte is an effective reservoir rock. Based on analysis of the relation between oil property and physical property of core and production test data, the corresponding relation of logging information and reservoir characteristics is established. It is determined that quantitatively and qualitatively identify reservoir by Rt- Δt,ρh- Δ t and Rt-Φ CNL logging crossplot. Combining with conventional logging and core data, factors affecting image logging are studied and analyzed, and the mode of identifying true and false fractures by acoustic and electric image logging has been established. Conformance rate of reservoir interpretation has been improved by combining quantitative and qualitative identification by 3700 logging series and with the assistant of visual reservoir image logging.
Determination of reservoir parameters: By analyzing mineral composition and using logging crossplot technique, Δ t, ρ b and Φ CNL value of volcanic matrix has been determined, and it is determined to calculate
matrix porosity by A t. Through theoretical study, processing interpretation and application, it has been established to calculate fracture porosity by acoustic and electric image logging, thus solved the problem of porosity determining in reserve calculation.
Reservoir classification and evaluation: According to classification of core capillary curves and data of production test, it has been first established to classify volcanic reservoirs by R,- A t crossplot. This method combines acoustic and electri
引文
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[40] 斯仑贝谢测井公司．测井解释常用岩石矿物手册．吴庆岩 张爱军译，石油工业出版社，1998．
[41] 张守谦等．成像测井技术及应用．石油工业出版社，1997．
[42] 石油测井情报协作组．测井新技术应用．石油工业出版社，1998．
[43] 袁明生等．低渗透裂缝性油藏勘探．石油工业出版社，2000．
[44] 陆大卫等．核磁共振测井理论与应用．石油工业出版社，1998．
[45] 张莹等．火山岩油气藏特征及勘探技术信息调研．辽河油田勘探开发研究院内部文献，2000．
[46] 魏喜等．东部凹陷中段沙河街组火山岩储层特征．辽河油田勘探开发研究院内部研究报告，2001．
[47] 中国石油天然气总公司勘探局．测井新技术与油气层评价进展．石油工业出版社，1997．
[48] Corbellern A., Application of the magnetic resonance logging in San Jorge basin (Argentina), SPWLA 37th Ann. Log. Symp., VV 1～12, 1996.06. 16
[49] Xiangchun Yuan, Zhengyan Xing, Effective Evaluation and Development of Diabase & Contactite Fractured Reservoir in Luo 151 Area, SPE 64460
[50] A. Corbelleri,D. Lenge, J. Ortea, and E. Breda, Application of magnetic resonance logging in San Jorge basin (Argentina),SPWLA 37th Annual Logging Symposium, June 16-19,1996
[51] Unm Komarudin Djoko Sunaryo Ron Prayitno Steve Hansen, Evaluation of geothermal igneous reservoirs, IPA 92-26.01
[52] Douglas R. Schmitt Fracture statistics derived from digital ultrasonic televiewer logging PAPER NO. CIM/AOSTRA 91-64
[53] Maghsood Abbaszadeh,,Chip Corbett, Roetz broetz, James Wang, development of an integrated reservoir model for a naturally fractured volcanic reservoir in China, SPE 59439
[54] Lu Fenggen, Zhao Wenjie, Wu Jingli, NMR logging Studies of lgneous Reservoir by the Aid of Core Analysis in Linpan Area Shengli Oilfield, SPE 50936
[55] M.M. Khalil and J. Pigaht, Suez, Petrophsical Application to Description of a Producing Fractured Basement Reservoir, SPE 21444
[56] Bourima All Belgasem, New synergetic approach for granite reservoir evaluation by means of well logging, May 5-7,1993
[57] Bourima All Belgasem, An evaluation of an oil-bearing granite reservoir from well logs.
[10] Weimer B．A．火成岩油藏中测井曲线的解释方法 AAPG Bull，1987，71(2)
[58] Serra O，根据多种测井资料确定岩性：实例研究，SPWLA 26th Ann．Log．Sym．；P631．843，1985．06．17
[59] BREWER T S. HARVEY, Borehole images of the ocean crust: Case histories from the ocean drilling program, Borehole imaging:applications and case histories [Geol soc London SPEC Publication No 159] PP 283-294,1999
[60] Reichhardt. D Application of neural networks to borehole geophysical log interpretations, MS Thesis, Montana Tech, Butte, MT, 1996(AO)
[61] Lime W, S. pinho G C. DE Gasperi, Igneous rocks identification on Well-Log data:An interpretation tool, 5TH Brazil Geophys Soc Int Congr Expanded Abstr V 1,1997(AO).
[62] Frias D G Garcia C R Rodriguez N Millan F, Log evation of oil-bearing volcanic-sedimentary rocks in the pina oil field, in central cuba, 2nd Petrobras Sci Appl To Oil Eng Workshop Proc Pp 27-366 nov 1997.
[63] Lu Fzhao W wu J wang W liu Wsun D li, Nmr Logging Studies Of Igneous Reservoir By The Aid Of Core Analysis In Linpan Area, Shengli Oilfield, 6th Spe Oil & Gas Int Conf In China pp557-567 1998
[64] Kato O doi N sakagawa Y. akazawa, Characteristics of Factures Based on FMI(Formation Microimager) Logs and cores In well WD-1 In the kakkonda geothermal field,Japan, Annu Geotherm Resources Counc Mtg, Trans V 19 pp317-322,1995.
[65] Akihisa K. ishida H. ebato T, Development of statistical well log analysis system-case studies of complex lithology formations, 2nd SPWLA Well Logging Symp of Japan, Proc Pap No
B, 1996.
[66]Rodriquez N, Analysis of well logging methods in volcanic and volcand sedimentary rocks form Pina Petroleum Field, Gcags(AAPG)MT6 Pap;AAPG Bull V 80, No 9 1996(AO).
[67]Belgasem G. A, New synergetic approach for granite reservoir evaluation by means of well logging, 15th SPWLA Europe Formation Evaluation SYMP Trans Pap No, 1993
[68]Komarudin U. sunaryo D prayitno, Evaluation of Geothermal Igneous Reservoirs 21th Annu Indon Petrol Ass Cony, Proc V 1, pp 607-630,1992
[69]Ali Belgasem B, An Evaluation Of An Oil-bearing Granite Reservoir From Well Logs, 13th Cwls Formation Evaluation Symp Trans Pap Nok, 1991
[70]Straub A gros Y krueckel U, Structural Description By Electrical Imaging Of A Borehole In Granite, 13th Spwla Et Al Europe Formation Evaluation Symp Trans Pap No L1,1990.
[71]Khal I1 M M pigaht J, Petrophysical Approach To Description Of A Producing Fractured Basement Reservoir, 7th Spe Middle East Oil Show Conf Proc Pp903-914,1991
[72]Schmitt D R, Fracture Statistics Derived From Digital Ultrasonic Televiewer Logging, CimPetrol Soc & Aostra Tech Conf Preprints V 2, Pap No 91-64,1991
[73]Straub A gros Y krueckel U, Borehole Electrical Imaging And structural Analysis In A Granitic Environment, Geophys J Int V 106, No 3, Pp635-646, Sept 1991
[2] 周超，董庆勇 龙湾筒凹陷九佛堂组火山岩储层特征研究，特种油气藏，Vol 6(1)，1999
[3] 徐守余 火成岩油藏测井评价及应用，石油实验地质Vol 21(增刊)，1999
[4] 刘汉之，张坤辽河坳陷热河台--欧利坨子火山岩成藏条件，复式油气田，Vol(4)，1999
[5] 刘呈冰，李俊国 全面评价低孔裂缝／孔洞型碳酸岩及火成岩储层，测井技术，Vol 23(6)，1999
[6] 严成信，邹长春 孔南火成岩测井评价方法探讨，测井技术，Vol 22(2)，1998
[7] 罗利，任兴国 花岗岩储层裂缝评价及其横向预测，测井技术，Vol 22(3)，1998
[8] 运华云 商741井区裂缝性火成岩储集层测井评价，复式油气田，Vol(4)，1998
[9] 杜贤越，肖焕钦 渤海湾盆地火成岩油气藏勘探研究进展，复式油气田，Vol(4)，1998
[10] 代诗华，罗兴平 火山岩储集层测井响应与解释方法，新疆石油地质，Vol 19(6)，1998
[11] 范宜仁，黄隆基 交汇图技术在火山岩岩性与裂缝识别中的应用，测井技术，Vol 23(1)，1999
[12] 邹长春，严成信 神经网络在枣北地区火成岩储层测井解释中的应用，石油地质物理勘探，Vol 32(增刊2)，1997
[13] 黄隆基，范宜仁 火山岩测井评价的地质和地球物理基础(Ⅰ)，测井技术，Vol 21(5)，1997
[14] 朱爱丽，吴伯福 火成岩的测井评价—大港油田枣北地区应用实例，测井技术，Vol 21(5)，1997
[15] 张庆国，曲表浩 风化店火山岩油藏描述研究，测井技术，Vol 21(6)，1997
[16] 张庆国，徐冬燕 风化店火山岩油藏测井解释方法研究，测井技术，Vol 20(4)，1996
[17] 代诗华，姜淑云 准噶尔盆地石西油田火山岩储集层的测井描述，新疆石油地质，Vol 18(2)，1997
[18] 魏涛，田洪 CBIL测井在火成岩地层中的应用，测井技术，Vol 21(1)，1997
[19] 张美兰 风化店构造安山储层电关系及油层参数研究，大港油田科技论文集，Vol 4，1994
[20] 洪雁，向勇 含油火成岩的测井评价，天然气勘探与开发，Vol 16(4)，1994
[21] 李争，余芳权 江汉盆地火山岩及其储层测井评价，江汉石油科技，Vol 4(3)，1994
[22] 阎新民 应用计算机进行准咯尔盆地火山岩裂缝识别，石油地球物理勘探，Vol 29(增刊)，1994
[23] 史倬晖，代诗华 地层倾角测井在新疆油田的地质应用效果，地层倾角测井技术与应用 pd 9，1993
[24] 张凤霞 地层倾角测井资料在安山岩油藏中的应用效果，地层倾角测井技术与应用，pd 9，1993
[25] 张萍 用地层倾角测井判断闵桥构造火山岩储层裂缝分布规律及其与油气的关系，地层倾角测井技术与应用，pd 9，1993
[26] 魏涛，李先鹏 用岩心资料刻度测井响应的确定裂缝孔隙度，测井技术，Vol 17(4)，1993
[27] 郭振彬，王秉刚 用地层倾角测井资料研究储层裂缝分布规律，地球物理测井，Vol 15(6)，1991
[28] 刑志贵，于宝成 辽河断陷太古界岩性与测井曲线关系研究，辽河石油勘探与开发，Vol(2)2，1992
[29] 匡立春 克拉玛依油田5-8区二叠系佳木河组火成岩岩性识别，石油与天然气地质，Vol 11(2)，1990
[30] 张国杰 阿尔善地区火成岩解释方法探讨，石油学会第四界测井年会，pd 9，1989
[31] 王景花 锦州20-2凝析气火山岩测井响应特征，石油学会第四界测井年会，pd 7，1989
[32] 衡志 应用数学测井信息探讨安山岩裂缝性储集层的特征，第二界测井年会论文选集，pd 8，1988
[33] 赖维民 高分辨率火成岩测井评价技术研究，石油勘探开发研究院(报告)，pd 1987
[34] 陈鑫堂 自然伽玛能谱测井资料的地质解释，测井技术，Vol 10(4)，1986
[35] 张国杰 二连盆地测井解释方法，二连盆地石油地质研究成果汇编，pd 1985
[36] 壅世和(译) 应用双侧向测井资料计算硬碳酸盐岩层的裂缝孔隙度，测井译丛，Vol(1)，1985
[37] 张爱卿 含油火成岩的测井评价，石油地质情报，Vol(3)，1985
[38] 邱家骧等．岩浆岩岩石学．北京：地质出版社，1985．
[39] O．塞拉(法)．测井解释基础与数据采集．石油工业出版社，1992．
[40] 斯仑贝谢测井公司．测井解释常用岩石矿物手册．吴庆岩 张爱军译，石油工业出版社，1998．
[41] 张守谦等．成像测井技术及应用．石油工业出版社，1997．
[42] 石油测井情报协作组．测井新技术应用．石油工业出版社，1998．
[43] 袁明生等．低渗透裂缝性油藏勘探．石油工业出版社，2000．
[44] 陆大卫等．核磁共振测井理论与应用．石油工业出版社，1998．
[45] 张莹等．火山岩油气藏特征及勘探技术信息调研．辽河油田勘探开发研究院内部文献，2000．
[46] 魏喜等．东部凹陷中段沙河街组火山岩储层特征．辽河油田勘探开发研究院内部研究报告，2001．
[47] 中国石油天然气总公司勘探局．测井新技术与油气层评价进展．石油工业出版社，1997．
[48] Corbellern A., Application of the magnetic resonance logging in San Jorge basin (Argentina), SPWLA 37th Ann. Log. Symp., VV 1～12, 1996.06. 16
[49] Xiangchun Yuan, Zhengyan Xing, Effective Evaluation and Development of Diabase & Contactite Fractured Reservoir in Luo 151 Area, SPE 64460
[50] A. Corbelleri,D. Lenge, J. Ortea, and E. Breda, Application of magnetic resonance logging in San Jorge basin (Argentina),SPWLA 37th Annual Logging Symposium, June 16-19,1996
[51] Unm Komarudin Djoko Sunaryo Ron Prayitno Steve Hansen, Evaluation of geothermal igneous reservoirs, IPA 92-26.01
[52] Douglas R. Schmitt Fracture statistics derived from digital ultrasonic televiewer logging PAPER NO. CIM/AOSTRA 91-64
[53] Maghsood Abbaszadeh,,Chip Corbett, Roetz broetz, James Wang, development of an integrated reservoir model for a naturally fractured volcanic reservoir in China, SPE 59439
[54] Lu Fenggen, Zhao Wenjie, Wu Jingli, NMR logging Studies of lgneous Reservoir by the Aid of Core Analysis in Linpan Area Shengli Oilfield, SPE 50936
[55] M.M. Khalil and J. Pigaht, Suez, Petrophsical Application to Description of a Producing Fractured Basement Reservoir, SPE 21444
[56] Bourima All Belgasem, New synergetic approach for granite reservoir evaluation by means of well logging, May 5-7,1993
[57] Bourima All Belgasem, An evaluation of an oil-bearing granite reservoir from well logs.
[10] Weimer B．A．火成岩油藏中测井曲线的解释方法 AAPG Bull，1987，71(2)
[58] Serra O，根据多种测井资料确定岩性：实例研究，SPWLA 26th Ann．Log．Sym．；P631．843，1985．06．17
[59] BREWER T S. HARVEY, Borehole images of the ocean crust: Case histories from the ocean drilling program, Borehole imaging:applications and case histories [Geol soc London SPEC Publication No 159] PP 283-294,1999
[60] Reichhardt. D Application of neural networks to borehole geophysical log interpretations, MS Thesis, Montana Tech, Butte, MT, 1996(AO)
[61] Lime W, S. pinho G C. DE Gasperi, Igneous rocks identification on Well-Log data:An interpretation tool, 5TH Brazil Geophys Soc Int Congr Expanded Abstr V 1,1997(AO).
[62] Frias D G Garcia C R Rodriguez N Millan F, Log evation of oil-bearing volcanic-sedimentary rocks in the pina oil field, in central cuba, 2nd Petrobras Sci Appl To Oil Eng Workshop Proc Pp 27-366 nov 1997.
[63] Lu Fzhao W wu J wang W liu Wsun D li, Nmr Logging Studies Of Igneous Reservoir By The Aid Of Core Analysis In Linpan Area, Shengli Oilfield, 6th Spe Oil & Gas Int Conf In China pp557-567 1998
[64] Kato O doi N sakagawa Y. akazawa, Characteristics of Factures Based on FMI(Formation Microimager) Logs and cores In well WD-1 In the kakkonda geothermal field,Japan, Annu Geotherm Resources Counc Mtg, Trans V 19 pp317-322,1995.
[65] Akihisa K. ishida H. ebato T, Development of statistical well log analysis system-case studies of complex lithology formations, 2nd SPWLA Well Logging Symp of Japan, Proc Pap No
B, 1996.
[66]Rodriquez N, Analysis of well logging methods in volcanic and volcand sedimentary rocks form Pina Petroleum Field, Gcags(AAPG)MT6 Pap;AAPG Bull V 80, No 9 1996(AO).
[67]Belgasem G. A, New synergetic approach for granite reservoir evaluation by means of well logging, 15th SPWLA Europe Formation Evaluation SYMP Trans Pap No, 1993
[68]Komarudin U. sunaryo D prayitno, Evaluation of Geothermal Igneous Reservoirs 21th Annu Indon Petrol Ass Cony, Proc V 1, pp 607-630,1992
[69]Ali Belgasem B, An Evaluation Of An Oil-bearing Granite Reservoir From Well Logs, 13th Cwls Formation Evaluation Symp Trans Pap Nok, 1991
[70]Straub A gros Y krueckel U, Structural Description By Electrical Imaging Of A Borehole In Granite, 13th Spwla Et Al Europe Formation Evaluation Symp Trans Pap No L1,1990.
[71]Khal I1 M M pigaht J, Petrophysical Approach To Description Of A Producing Fractured Basement Reservoir, 7th Spe Middle East Oil Show Conf Proc Pp903-914,1991
[72]Schmitt D R, Fracture Statistics Derived From Digital Ultrasonic Televiewer Logging, CimPetrol Soc & Aostra Tech Conf Preprints V 2, Pap No 91-64,1991
[73]Straub A gros Y krueckel U, Borehole Electrical Imaging And structural Analysis In A Granitic Environment, Geophys J Int V 106, No 3, Pp635-646, Sept 1991