火山碎屑岩测井评价方法研究
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摘要
本文研究的是海拉尔盆地乌尔逊-贝尔凹陷的火山碎屑岩储层。由于火山碎屑岩储层岩性复杂、测井数据种类繁多以及所研究区域大、层位多等特点,导致火山碎屑岩储层测井参数难于确定,进而对火山碎屑岩储层参数的求取进行了深入研究。
研究中,首先对基础的测井数据进行一系列的预处理,进而开展岩性识别,在准确识别岩性的基础上,先对测井资料进行标准化处理,然后将多元回归方法应用于火山碎屑岩储层参数研究中去,这是本次研究中的创新点。依据孔隙度与中子、密度、声波三者之间的关系,将多元回归思想应用于其中,通过对比找出相关性最好的,然后将其应用到研究区域内,处理研究区内的实际资料,通过对比说明了各种解释方法的效果及适用性,形成了一套适合于研究区内的火山碎屑岩储层的解释方法。
Porosity and permeability of reservoir are the basic and important parameters in the interpretation of well logs. They are very important basis for computation of the reserve of oil-bearing reservoirs. For such complex pyroclastic rock formation, a single old log is not sufficient to calculate the formation parameters. Basing on the prior investigations on the method of calculating reservoir parameters, this paper searches method suitable for calculating formation parameters in pyroclastic reservoirs.
This paper investigates the volcanic clastic reservoirs in the Hailar Basin Wuerxun - Bell Depression. As the pyroclastic rock reservoirs have complex lithology and logs logged by several kinds of logger. Logging data will be standardized so as to control the quality of logging data. This paper attempts to explain the use of traditional methods of interpretation of well logs in pyroclastic rock reservoir, but failed to achieve satisfactory results.
These investigations are held in Hailaer basin of Daqing oil field. Firstly, there is the standardization of processing for logging date.Other floors will be corrected by the standardization of data. The corrections of the logs eliminate the influences of the many factors.After the standardization, the real situation of underground could be more accurately reflected by the logging data.
Generally, logging data standardization on the basis of a region with a layer has the same geological characteristics of geophysical, so different well from the logging data of the same type have own distribution. When the standard layer of the key well have been established after the standard distribution pattern of oilfield, the influences of the many factors will be eliminated by the relevant technical analysis of the wells and a comprehensive analysis of data logging。
The second is skeleton parameters of the martrix.It’s an important part of strike porosity and saturation.This paper is through the frame components to calculate the parameters.
At present, the oil and gas layer of explanation are restricted by the identification of reservoir and lithology in Hailar basin. The complication of ithology and diverse ithology lead to log response character- ristics of clutter and the deterioration of law, and also influenced the rate of interpretation in the water layer.
Finally, there is saturation and penetration of calculation. In formation evaluation and analysis of oil and gas, regional explained the parameters of a reasonable choice is very important.
Porosity reservoir rock is the most important one of the physical parameters; it is mainly used to evaluate a reservoir and the reservoir capacity of the relative size. In accordance with fluid movement in the bay to the situation of freedom of the pore fluid can be divided into the pores and porosity. Free fluid pores are those of mutual connectivity, and in general under the conditions of fluid pressure in that part of which flows pore. The total pore or absolute rock is the sum of all the pore space of the whole, independent of the pore size, shape and porosity channel cross-section, regardless of whether they are closed or not.
Formation permeability is a complex parameter, and calculated by logging data. It is influenced by the porosity of rock, clay content, particle size, separation and other factors affecting quality. The high-impact and credibility of the parameters are porosity. As the reservoir permeability and porosity of the structure is very close, so clastic rock formation penetration may be to some extent reflect the formation pore geometry of the size of the value of the function.
The paper gives the basic principles and implementation approaches of logging data normalization and mathematical statistics. Some interpretation models were eliminated by the logging data and core analysis data of this region. Some well logging data were processed and get some basic conclusions on how to select and apply these interpretation models. A relative mature methodology which suited for pyroclastic rock reservoir in this region was gained. The work established an important base on distinguishing oil and water layer for the future.
On the basis of the comparisons above, it can be found that a more precise value of saturation may be obtained.
研究中,首先对基础的测井数据进行一系列的预处理,进而开展岩性识别,在准确识别岩性的基础上,先对测井资料进行标准化处理,然后将多元回归方法应用于火山碎屑岩储层参数研究中去,这是本次研究中的创新点。依据孔隙度与中子、密度、声波三者之间的关系,将多元回归思想应用于其中,通过对比找出相关性最好的,然后将其应用到研究区域内,处理研究区内的实际资料,通过对比说明了各种解释方法的效果及适用性,形成了一套适合于研究区内的火山碎屑岩储层的解释方法。
Porosity and permeability of reservoir are the basic and important parameters in the interpretation of well logs. They are very important basis for computation of the reserve of oil-bearing reservoirs. For such complex pyroclastic rock formation, a single old log is not sufficient to calculate the formation parameters. Basing on the prior investigations on the method of calculating reservoir parameters, this paper searches method suitable for calculating formation parameters in pyroclastic reservoirs.
This paper investigates the volcanic clastic reservoirs in the Hailar Basin Wuerxun - Bell Depression. As the pyroclastic rock reservoirs have complex lithology and logs logged by several kinds of logger. Logging data will be standardized so as to control the quality of logging data. This paper attempts to explain the use of traditional methods of interpretation of well logs in pyroclastic rock reservoir, but failed to achieve satisfactory results.
These investigations are held in Hailaer basin of Daqing oil field. Firstly, there is the standardization of processing for logging date.Other floors will be corrected by the standardization of data. The corrections of the logs eliminate the influences of the many factors.After the standardization, the real situation of underground could be more accurately reflected by the logging data.
Generally, logging data standardization on the basis of a region with a layer has the same geological characteristics of geophysical, so different well from the logging data of the same type have own distribution. When the standard layer of the key well have been established after the standard distribution pattern of oilfield, the influences of the many factors will be eliminated by the relevant technical analysis of the wells and a comprehensive analysis of data logging。
The second is skeleton parameters of the martrix.It’s an important part of strike porosity and saturation.This paper is through the frame components to calculate the parameters.
At present, the oil and gas layer of explanation are restricted by the identification of reservoir and lithology in Hailar basin. The complication of ithology and diverse ithology lead to log response character- ristics of clutter and the deterioration of law, and also influenced the rate of interpretation in the water layer.
Finally, there is saturation and penetration of calculation. In formation evaluation and analysis of oil and gas, regional explained the parameters of a reasonable choice is very important.
Porosity reservoir rock is the most important one of the physical parameters; it is mainly used to evaluate a reservoir and the reservoir capacity of the relative size. In accordance with fluid movement in the bay to the situation of freedom of the pore fluid can be divided into the pores and porosity. Free fluid pores are those of mutual connectivity, and in general under the conditions of fluid pressure in that part of which flows pore. The total pore or absolute rock is the sum of all the pore space of the whole, independent of the pore size, shape and porosity channel cross-section, regardless of whether they are closed or not.
Formation permeability is a complex parameter, and calculated by logging data. It is influenced by the porosity of rock, clay content, particle size, separation and other factors affecting quality. The high-impact and credibility of the parameters are porosity. As the reservoir permeability and porosity of the structure is very close, so clastic rock formation penetration may be to some extent reflect the formation pore geometry of the size of the value of the function.
The paper gives the basic principles and implementation approaches of logging data normalization and mathematical statistics. Some interpretation models were eliminated by the logging data and core analysis data of this region. Some well logging data were processed and get some basic conclusions on how to select and apply these interpretation models. A relative mature methodology which suited for pyroclastic rock reservoir in this region was gained. The work established an important base on distinguishing oil and water layer for the future.
On the basis of the comparisons above, it can be found that a more precise value of saturation may be obtained.
引文
[1]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,第 29 卷第 4 期,2006 年 8 月,P239-243.
[2]王允诚.油层物理[M].北京:石油工业出版社,1993,P189-193.
[3]高瑞祺,萧德铭.松辽及其外围盆地油气勘探新进展[M].石油工业出版社,1995,P173-189.
[4]雍世和,张超谟主编.测井数据处理与综合解释[M].北京:石油工业出版社,2004,P178-181.
[5]赵丽霞.惠民凹陷基山砂岩体储层物性的测井解释[D].中南大学硕士论文,2007,P7-10.
[6]王志章,熊琦华.油藏描述中的测井资料数据标准化方法和程序[J].测井技术,1994,18(6):P402-407.
[7]李周波.地球物理测井数据处理与综合解释[M].吉林大学出版社2003,P58-61.
[8]莫修文等.三水导电模型及其在低阻储层解释中的应用[J].长春科技大学学报,2002 年 1 月,第 31 卷第 1 期,P92-94.
[9] Li Zhoubo, Mo Xiuwen.Study on the electric property of Shaly sand and its interpretation method [J].Journal of Geoscientific Research in Northeast Asia,1999,2(1):110-114.
[10]Archie.The Electrical Resistivity Log as an aid in Determining Some Reservoir Characteristics [M].Trans.AIME, 1942, Vo1.146, P.54.
[11]P.F.Worthington.The Evolution of Shaly-Sand Concepts in Reservoir Evaluation [J].The Log Analyst,1985.P23-40.
[12]Waxman, M.H., Smits,L.J.M..Electrical Conductivities in Oil-bearing Shaly-Sands [J].Soc.Pet.Eng.SPE1683.
[13]Diederix, K.M., 1982.Anomalous Relation-ships Between Resistivity Index and Water Saturation in the Rotligend Sandstone [J].23td SPWLA,X.
[14]莫修文.低阻储层导电模型的建立与测井解释方法研究[D].长春:长春科技大学,1998,P54-58.
[15]朱彬,文政,刘传平.用多矿物双水模型评价海拉尔盆地泥质砂岩储层[J].大庆石油地质与开发,2002 年 12 月:第 21 卷第 6 期,P58-60.
[16]吴庆岩,张爱军.测井解释常用岩石矿物手册[M].北京:石油工业出版社,1991,P116-117.
[17]Givens W W. Formation resistivity index and related Equationsbased upon a conductive rock matrix model (CRMM) [J].27th SPWLA Paper, 1986.
[18]于志钧.石油数学地质[M].石油工业出版社,1985,P41-48.
[19]何更生.油层物理[M].石油工业出版社,2001 年 8 月:第一版,58-70.
[20]莫修文,李舟波,范晓敏.岩石导电模型研究与油气饱和度评价[C].中国地球物理.2003——中国地球物理学会第十九届年会论文集, 2003,P75.
[21]汪中浩,章成广.低渗砂岩储层测井评价方法[M].石油工业出版社,2004 年,P12-14.
[22]王行信,周书欣等.砂岩储层粘土矿物与油层保护[M].地质出版社,北京,1992,p100-110.
[23]曾文冲.油气藏储层测井评价技术[M].北京:石油工业出版社,1991.314-323.
[24]尚作源,黄隆基.测井与解释技术[M].北京:石油工业出版社,1991.296-297.
[25]孙建孟,刘荣.青海柴西地区常规测井裂缝识别方法[J].测井技术,1999,23(4):268-272.
[26]谭廷栋,王志信,牛超群,等.测井学[M].北京:石油工业出版社,1998 年,P485-493.
[27]乐昌硕.岩石学[M].北京:地质出版社,1984,(6),p256-270.
[28]陈建文等.徐家围子端陷火山岩岩性的测井识别技术[J].特种油气藏,2003,(2),P56-59.
[2]王允诚.油层物理[M].北京:石油工业出版社,1993,P189-193.
[3]高瑞祺,萧德铭.松辽及其外围盆地油气勘探新进展[M].石油工业出版社,1995,P173-189.
[4]雍世和,张超谟主编.测井数据处理与综合解释[M].北京:石油工业出版社,2004,P178-181.
[5]赵丽霞.惠民凹陷基山砂岩体储层物性的测井解释[D].中南大学硕士论文,2007,P7-10.
[6]王志章,熊琦华.油藏描述中的测井资料数据标准化方法和程序[J].测井技术,1994,18(6):P402-407.
[7]李周波.地球物理测井数据处理与综合解释[M].吉林大学出版社2003,P58-61.
[8]莫修文等.三水导电模型及其在低阻储层解释中的应用[J].长春科技大学学报,2002 年 1 月,第 31 卷第 1 期,P92-94.
[9] Li Zhoubo, Mo Xiuwen.Study on the electric property of Shaly sand and its interpretation method [J].Journal of Geoscientific Research in Northeast Asia,1999,2(1):110-114.
[10]Archie.The Electrical Resistivity Log as an aid in Determining Some Reservoir Characteristics [M].Trans.AIME, 1942, Vo1.146, P.54.
[11]P.F.Worthington.The Evolution of Shaly-Sand Concepts in Reservoir Evaluation [J].The Log Analyst,1985.P23-40.
[12]Waxman, M.H., Smits,L.J.M..Electrical Conductivities in Oil-bearing Shaly-Sands [J].Soc.Pet.Eng.SPE1683.
[13]Diederix, K.M., 1982.Anomalous Relation-ships Between Resistivity Index and Water Saturation in the Rotligend Sandstone [J].23td SPWLA,X.
[14]莫修文.低阻储层导电模型的建立与测井解释方法研究[D].长春:长春科技大学,1998,P54-58.
[15]朱彬,文政,刘传平.用多矿物双水模型评价海拉尔盆地泥质砂岩储层[J].大庆石油地质与开发,2002 年 12 月:第 21 卷第 6 期,P58-60.
[16]吴庆岩,张爱军.测井解释常用岩石矿物手册[M].北京:石油工业出版社,1991,P116-117.
[17]Givens W W. Formation resistivity index and related Equationsbased upon a conductive rock matrix model (CRMM) [J].27th SPWLA Paper, 1986.
[18]于志钧.石油数学地质[M].石油工业出版社,1985,P41-48.
[19]何更生.油层物理[M].石油工业出版社,2001 年 8 月:第一版,58-70.
[20]莫修文,李舟波,范晓敏.岩石导电模型研究与油气饱和度评价[C].中国地球物理.2003——中国地球物理学会第十九届年会论文集, 2003,P75.
[21]汪中浩,章成广.低渗砂岩储层测井评价方法[M].石油工业出版社,2004 年,P12-14.
[22]王行信,周书欣等.砂岩储层粘土矿物与油层保护[M].地质出版社,北京,1992,p100-110.
[23]曾文冲.油气藏储层测井评价技术[M].北京:石油工业出版社,1991.314-323.
[24]尚作源,黄隆基.测井与解释技术[M].北京:石油工业出版社,1991.296-297.
[25]孙建孟,刘荣.青海柴西地区常规测井裂缝识别方法[J].测井技术,1999,23(4):268-272.
[26]谭廷栋,王志信,牛超群,等.测井学[M].北京:石油工业出版社,1998 年,P485-493.
[27]乐昌硕.岩石学[M].北京:地质出版社,1984,(6),p256-270.
[28]陈建文等.徐家围子端陷火山岩岩性的测井识别技术[J].特种油气藏,2003,(2),P56-59.