声电成像测井处理解释方法研究及软件实现
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摘要
本文论述了声电成像处理解释各功能模块的基本原理、实现的关键技术及算法改进、应用效果分析。在图像增强上采用直方图规定化算法和组映射规则的直方图匹配方法,消除了传统直方图均衡算法在处理低灰度密集分布图像时具体增强效果不易控制,灰度级的合并使得图像层次感差,丢失图像的细节等不足,改进效果明显;在裂缝参数计算上,基于图像处理技术提供了多种阈值分割方式,满足不同图像处理需求,不仅可计算裂缝参数,而且可实现孔洞计算与统计;在孔隙度频谱分析中阈值分割采用大律法,选取出的阈值理想、效果稳定。基于以上研究开发了一套具有自身技术特色的,可处理STAR、CBIL、FMI、EMI、XRMI、CAST等多种仪器成像测井资料,具有预处理、图像生成、地质构造倾角、层理分析、电阻率刻度、孔隙度频谱分析、图像处理、裂缝孔洞参数自动计算功能的声电成像处理解释软件系统。应用该软件包处理评价了10口井的声电成像测井资料,通过应用研究验证了该软件具有可靠性和实用性,可以在油田推广应用,对适应市场需求、增强对外服务的市场竞争力具有非常大的应用价值。
With the rapid development of imaging logging, micro-resistivity scanning and circumferential borehole acoustic imaging logging combined with conventional logging, dipole shear wave logging, NMR logging datas comprehensive analysis, plays an important role in more and more complex, subtle and unconventional oil and gas reservoirs exploration. It can get a variety of rich information on circumferential and radial directions of bolehole, can be oil and gas exploration and development of effective solution to a problem: fracture identification and evaluation of high resolution thin evaluate, sedimentary environmental analysis, stratigraphic analysis and geological structure within the structure of explanation. In addition, forecasts for gas reservoir storage, to prevent lost circulation, well collapse, perforation location detection, hole density and so provide a basis for engineering applications. To this end, full use of the rich micro-resistivity scanning and circumferential borehole acoustic imaging logging borehole information, geological structure dip calculation , stratification analysis and fracture and vug parameters’automatic calculation has a very large theoretical significance and application value.
In view of the import or self-development image tools, integrating the needs and field experience, learn and analyze the advantages and disadvantages similar software at home and abroad, has developed a imaging processing and interpretation software with its own characteristics, can handle STAR, CBIL, FMI, EMI, XRMI, CAST and other imaging equipment logging data, including preprocessing, image generation, geological dip, stratification analysis, resistivity scale, porosity spectral analysis, image processing and fracture parameters’automatically computing.
This article discusses the interpretation of basic principles of each functional module, the key technology and algorithm improvement, and result evaluation. Schlumberger logging company's Geology and Atlas logging company's eXpress are the basis of algorithm. Preprocessing module includes information on the acceleration correction of the borehole, voltage correction (EMEX correction), deep power button alignment, bad power button correction, equalization, phase correction, bias correction, caliper scale . Image generation module for static and dynamic image enhancement, including RGB calibration, histogram specification, histogram matching. Module using the dip method to solve all the relevant contrast, the best correlation point electrode, then the least square method to fitting the best plane, and the device coordinates into real coordinates, and further request get to level occurrence elements. Resistivity scale module according to GR curve associated contrast, the conventional LLS correction to the image depth of lines; combination of Emex curve, convert the LLS curves corrected into theoretical current CLLS; statistics generated power button mean curves, which match the vertical resolution obtained with LLS (good correlation); calculated by statistical fitting Ave2LLS to CLLS scale relations, while Ave2LLS scale generated Sres, for quality control. Porosity spectrum analysis module will scale the resistivity after the saturation by the classical formula Archie porosity, then a certain window length statistical distribution histogram of porosity, using a large law (OTSU) to determine the primary and secondary pore domain cutoff point and output values of primary and secondary porosity. Fracture and vug parameter calculation module according to cracks, holes reservoir has a "background of high resistivity, low resistivity target" feature, its corresponding histogram data corresponding to the maximum peak of carbonate bedrock, such as sub-peak corresponds to crack need to identify targets. Therefore, select the appropriate threshold value, the crack resistance of target low-out from the image segmentation and image processing algorithms are based on low-resistance target hole fracture area, the percentage of parameters, length, width and other parameters to half of the image quantitative evaluation.
In addition, in-depth study of image enhancement, segmentation algorithm, used in the image generation, calculation of fracture parameters, the primary and secondary porosity module .the final set on the image enhancement algorithm using histogram specification and the group histogram matching method to achieve the mapping rules, to eliminate the traditional histogram equalization in the treatment of low gray level distribution of image-intensive specific enhancement difficult to control, making the combined gray-scale image layered bad enough losing image details, etc., to improve effect is obvious; the fracture parameters calculation, based on image processing technology to provide a variety of segmentation methods to meet the needs of different image processing, not only calculate the crack density, crack length, crack width and other parameters, and the hole can be realized Calculation and statistics ; porosity, large law spectrum module output of the original segmentation threshold value, secondary porosity, select the threshold of the ideal and effectively.
Evaluated logging data of 10 boleholds by using the developed software, to verify the software of reliability and practicality, can promote the use of oil.
With the rapid development of imaging logging, micro-resistivity scanning and circumferential borehole acoustic imaging logging combined with conventional logging, dipole shear wave logging, NMR logging datas comprehensive analysis, plays an important role in more and more complex, subtle and unconventional oil and gas reservoirs exploration. It can get a variety of rich information on circumferential and radial directions of bolehole, can be oil and gas exploration and development of effective solution to a problem: fracture identification and evaluation of high resolution thin evaluate, sedimentary environmental analysis, stratigraphic analysis and geological structure within the structure of explanation. In addition, forecasts for gas reservoir storage, to prevent lost circulation, well collapse, perforation location detection, hole density and so provide a basis for engineering applications. To this end, full use of the rich micro-resistivity scanning and circumferential borehole acoustic imaging logging borehole information, geological structure dip calculation , stratification analysis and fracture and vug parameters’automatic calculation has a very large theoretical significance and application value.
In view of the import or self-development image tools, integrating the needs and field experience, learn and analyze the advantages and disadvantages similar software at home and abroad, has developed a imaging processing and interpretation software with its own characteristics, can handle STAR, CBIL, FMI, EMI, XRMI, CAST and other imaging equipment logging data, including preprocessing, image generation, geological dip, stratification analysis, resistivity scale, porosity spectral analysis, image processing and fracture parameters’automatically computing.
This article discusses the interpretation of basic principles of each functional module, the key technology and algorithm improvement, and result evaluation. Schlumberger logging company's Geology and Atlas logging company's eXpress are the basis of algorithm. Preprocessing module includes information on the acceleration correction of the borehole, voltage correction (EMEX correction), deep power button alignment, bad power button correction, equalization, phase correction, bias correction, caliper scale . Image generation module for static and dynamic image enhancement, including RGB calibration, histogram specification, histogram matching. Module using the dip method to solve all the relevant contrast, the best correlation point electrode, then the least square method to fitting the best plane, and the device coordinates into real coordinates, and further request get to level occurrence elements. Resistivity scale module according to GR curve associated contrast, the conventional LLS correction to the image depth of lines; combination of Emex curve, convert the LLS curves corrected into theoretical current CLLS; statistics generated power button mean curves, which match the vertical resolution obtained with LLS (good correlation); calculated by statistical fitting Ave2LLS to CLLS scale relations, while Ave2LLS scale generated Sres, for quality control. Porosity spectrum analysis module will scale the resistivity after the saturation by the classical formula Archie porosity, then a certain window length statistical distribution histogram of porosity, using a large law (OTSU) to determine the primary and secondary pore domain cutoff point and output values of primary and secondary porosity. Fracture and vug parameter calculation module according to cracks, holes reservoir has a "background of high resistivity, low resistivity target" feature, its corresponding histogram data corresponding to the maximum peak of carbonate bedrock, such as sub-peak corresponds to crack need to identify targets. Therefore, select the appropriate threshold value, the crack resistance of target low-out from the image segmentation and image processing algorithms are based on low-resistance target hole fracture area, the percentage of parameters, length, width and other parameters to half of the image quantitative evaluation.
In addition, in-depth study of image enhancement, segmentation algorithm, used in the image generation, calculation of fracture parameters, the primary and secondary porosity module .the final set on the image enhancement algorithm using histogram specification and the group histogram matching method to achieve the mapping rules, to eliminate the traditional histogram equalization in the treatment of low gray level distribution of image-intensive specific enhancement difficult to control, making the combined gray-scale image layered bad enough losing image details, etc., to improve effect is obvious; the fracture parameters calculation, based on image processing technology to provide a variety of segmentation methods to meet the needs of different image processing, not only calculate the crack density, crack length, crack width and other parameters, and the hole can be realized Calculation and statistics ; porosity, large law spectrum module output of the original segmentation threshold value, secondary porosity, select the threshold of the ideal and effectively.
Evaluated logging data of 10 boleholds by using the developed software, to verify the software of reliability and practicality, can promote the use of oil.
引文
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[2]Jansen M,Bultheel A.Multiple wavelet threshold estimation by generalized cross validation for images with correlated noise.IEEE Trans. Image Processing, 1999,8(7),947-953.
[3]Gordon L.Moake. An Accelerometer- and Tension-Based Depth Correction Suitable for Image Logs[ C ].SPWLA 49th Annual Logging Symposium, May 25-28, 2008.
[4]D.Torres,R.Strickland,M.Gianzero.A new approach to determ image.Society of Professional Well Log Anaysts,13th Europ Symposium Transactions,Budapest Chapter,Paper JJ,1-16.
[5]M.Atiquazzaman.Mutiresolution Hough Transform-An efficient method of detecting patterns in images.IEEE Transactions on pattern analysis and machine intelligence,1992,14(11).
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[7]原福堂,徐兵,汪浩,伍东,张胜文.声电成像测井解释处理软件的开发与应用[J].测井技术,2005,29(5): 407-409.
[8]吴鹏程,陈一健,杨琳,戢俊文.成像测井技术研究现状及应用[J].天然气勘探与开发(地质勘探),2007(6):36-40.
[9]余春昊,李长文.LEAD测井综合应用平台开发与应用[J].测井技术,2005(10),29(5): 396-398.
[10]祁兴中,刘兴礼,傅海成,张承森,王焕增,刘瑞林,钟广法.电成像测井资料定量处理方法研究及应用[J].天然气工业,2005(6) :32-34.
[11]吴兴能,刘瑞林,雷军,柳建华,信毅,韩能润.电成像测井资料变换为孔隙度分布图像的研究[J].测井技术,2008(2),32(1):53-56.
[12]吴菊仙,张树东.六臂倾角计算与应用[J].测井技术,1996,20(1):32-36.
[13]Michael Bittar,Roland Chemali,Marian Morys, Jim Wilson,Frode Hveding, Shanjun Li, Sergei Knizhnik, Dann M. Halverson.ANALYSIS OF DENSITY IMAGE DIP ANGLE CALCULATIONS[ C ].SPWLA 49th Annual Logging Symposium, May 25-28,2008.
[14]何登春,鲍金平.SHDT地层倾角测井资料处理MSD倾角计算方法[J].测井与射孔,1999(4):1-4.
[15]吴菊仙,张超漠,张占松.求六臂地层倾角测井微电阻率曲线间的最优高程差[J].石油地球物理勘探,30(6),1995(10):797-802.
[16]孙加华,肖洪伟,幺忠文,崔啸龙.声电成像测井技术在储层裂缝识别中的应用[J].大庆石油地质与开发,25(3):100-102.
[17]曹毅民,章成广,杨维英,徐姣莲.裂缝性储层电成像测井孔隙度定量评价方法研究[J].测井技术,2006(6),30( 3)237-239.
[18]祁兴中,刘兴礼,傅海成,张承森,王焕增,刘瑞林,钟广法.电成像测井资料定量处理方法研究及应用[J].天然气工业,2005(6):32-34.
[19]吴树峰,蔡万红.直方图规定化算法的研究[J].科技信息,2008(27):382.
[20]吴铁洲,熊才权.直方图匹配图像增强技术的算法研究与实现[J].湖北工业大学学报,20(2):59-61.
[21]高彦平.图像增强方法的研究与实现[D].山东:山东科技大学,2005.
[22]曹计昌,杨帆.基于图像增强的灰度插值算法[J].计算机辅助工程,2006(12),15(4) :47-49.
[23]黄成,朱幼莲.一种改进的直方图均衡算法[J].江苏技术师范学院学报(自然科学版),第14卷第1期,2008(3):57-61.
[24]刘子平,屈玲,赵中明,杨小兵.STAR微电阻率扫描成像自动增益恢复预处理技术[J].测井技术,2008(12),32(6):574-577.
[25]冯翠菊.用测井资料确定次生孔隙[D] .大庆:大庆石油学院,2005.
[26]柯式镇,许淑霞.井壁电成像测井资料定量评价方法研究[J].天然气工业(地质与勘探版),2006(9):101-103.
[27]李河.基于构件复用的测井解释系统及成像测井图像处理与自动识别技术研究[D].长春:吉林大学,2005.
[28]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.
[29]吴兴能,刘瑞林,雷军,柳建华,信毅,韩能润.电成像测井资料变换为孔隙度分布图像的研究[J].测井技术,2008(2),32(1): 53-56.
[30]周云才,李风珍.边缘提取算法研究及其在FMI图像处理中的应用[J].计算机与数字工程,2007,3(7): 133-134.
[31]田金文,高谦,杜拥军,刘志敏.基于井壁成像测井图像的溶洞自动检测方法[J].江汉石油学院学报,1999(6),21(2): 20-22.
[32]杨绪海,张晓春.利用声成像测井数据实现岩石裂缝特征的自动识别[J].中国海上油气(地质),14(6):429-431.
[33]金燕,张旭.测井裂缝参数估算与储层裂缝评价方法研究[J].天然气工业(地质勘探)2002(5):64-67.
[34]Anil Kuman Tyagi等著,罗景美,李爱华译,赵文杰校.井眼电成像在碳酸盐岩储层孔隙度分析中的应用[J].测井与射孔,2003(2):23-27.
[35]张丽莉,刘瑞林.两种图像分割算法在FMI成像资料中的应用[J].江汉石油学院学报, 1999(12),21(4 ): 88-90.
[36]柯式镇,冯启宁.井壁成像测井资料目标体自动检测方法研究[J].石油大学学报(自然科版),2004,28(4):39-42.
[37]Jonathan Hall , Marco Ponzi , Mauro Gonfalini.Automatic Extraction and Characterisation of Geological Features and Textures from Borehole Images and Core Photographs.SPWLA 37th Annual Logging Symposium,Paper CCC,June 1996,16-19.
[38] Cheung,P.S.,and Heliot D.,1990,Workstation based fracture Evaluation using borehole images and wireline,Ann.Conf.Soc.Petrol. Eng.,Paper 20573.
[39]付建伟,肖立志,张中元.井下声电成像测井仪的现状与发展趋势[J].地球物理学进展, 2004(12),19(4):730-738.
[40] Cheung P ,“Microresistivity and Ultrasonic Imagers:Tool operations and Proeessing Principles with Reference to Commonly Encountered Image Artifacts”,in Borehole Imaging:Applications and Case Histories,Lovel MA,Willimason,G and Harvey P(eds),Geological Soeiety(London) Special Publieation,no.159,1999.
[2]Jansen M,Bultheel A.Multiple wavelet threshold estimation by generalized cross validation for images with correlated noise.IEEE Trans. Image Processing, 1999,8(7),947-953.
[3]Gordon L.Moake. An Accelerometer- and Tension-Based Depth Correction Suitable for Image Logs[ C ].SPWLA 49th Annual Logging Symposium, May 25-28, 2008.
[4]D.Torres,R.Strickland,M.Gianzero.A new approach to determ image.Society of Professional Well Log Anaysts,13th Europ Symposium Transactions,Budapest Chapter,Paper JJ,1-16.
[5]M.Atiquazzaman.Mutiresolution Hough Transform-An efficient method of detecting patterns in images.IEEE Transactions on pattern analysis and machine intelligence,1992,14(11).
[6]Et ris E L,et al.Pet rogrphic Insights into The Rele2vance of Archie’s Equation:Formation Factor Without“m”and“a”[ C ]. The Log Analyst Symposium Transactions. 1989.
[7]原福堂,徐兵,汪浩,伍东,张胜文.声电成像测井解释处理软件的开发与应用[J].测井技术,2005,29(5): 407-409.
[8]吴鹏程,陈一健,杨琳,戢俊文.成像测井技术研究现状及应用[J].天然气勘探与开发(地质勘探),2007(6):36-40.
[9]余春昊,李长文.LEAD测井综合应用平台开发与应用[J].测井技术,2005(10),29(5): 396-398.
[10]祁兴中,刘兴礼,傅海成,张承森,王焕增,刘瑞林,钟广法.电成像测井资料定量处理方法研究及应用[J].天然气工业,2005(6) :32-34.
[11]吴兴能,刘瑞林,雷军,柳建华,信毅,韩能润.电成像测井资料变换为孔隙度分布图像的研究[J].测井技术,2008(2),32(1):53-56.
[12]吴菊仙,张树东.六臂倾角计算与应用[J].测井技术,1996,20(1):32-36.
[13]Michael Bittar,Roland Chemali,Marian Morys, Jim Wilson,Frode Hveding, Shanjun Li, Sergei Knizhnik, Dann M. Halverson.ANALYSIS OF DENSITY IMAGE DIP ANGLE CALCULATIONS[ C ].SPWLA 49th Annual Logging Symposium, May 25-28,2008.
[14]何登春,鲍金平.SHDT地层倾角测井资料处理MSD倾角计算方法[J].测井与射孔,1999(4):1-4.
[15]吴菊仙,张超漠,张占松.求六臂地层倾角测井微电阻率曲线间的最优高程差[J].石油地球物理勘探,30(6),1995(10):797-802.
[16]孙加华,肖洪伟,幺忠文,崔啸龙.声电成像测井技术在储层裂缝识别中的应用[J].大庆石油地质与开发,25(3):100-102.
[17]曹毅民,章成广,杨维英,徐姣莲.裂缝性储层电成像测井孔隙度定量评价方法研究[J].测井技术,2006(6),30( 3)237-239.
[18]祁兴中,刘兴礼,傅海成,张承森,王焕增,刘瑞林,钟广法.电成像测井资料定量处理方法研究及应用[J].天然气工业,2005(6):32-34.
[19]吴树峰,蔡万红.直方图规定化算法的研究[J].科技信息,2008(27):382.
[20]吴铁洲,熊才权.直方图匹配图像增强技术的算法研究与实现[J].湖北工业大学学报,20(2):59-61.
[21]高彦平.图像增强方法的研究与实现[D].山东:山东科技大学,2005.
[22]曹计昌,杨帆.基于图像增强的灰度插值算法[J].计算机辅助工程,2006(12),15(4) :47-49.
[23]黄成,朱幼莲.一种改进的直方图均衡算法[J].江苏技术师范学院学报(自然科学版),第14卷第1期,2008(3):57-61.
[24]刘子平,屈玲,赵中明,杨小兵.STAR微电阻率扫描成像自动增益恢复预处理技术[J].测井技术,2008(12),32(6):574-577.
[25]冯翠菊.用测井资料确定次生孔隙[D] .大庆:大庆石油学院,2005.
[26]柯式镇,许淑霞.井壁电成像测井资料定量评价方法研究[J].天然气工业(地质与勘探版),2006(9):101-103.
[27]李河.基于构件复用的测井解释系统及成像测井图像处理与自动识别技术研究[D].长春:吉林大学,2005.
[28]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.
[29]吴兴能,刘瑞林,雷军,柳建华,信毅,韩能润.电成像测井资料变换为孔隙度分布图像的研究[J].测井技术,2008(2),32(1): 53-56.
[30]周云才,李风珍.边缘提取算法研究及其在FMI图像处理中的应用[J].计算机与数字工程,2007,3(7): 133-134.
[31]田金文,高谦,杜拥军,刘志敏.基于井壁成像测井图像的溶洞自动检测方法[J].江汉石油学院学报,1999(6),21(2): 20-22.
[32]杨绪海,张晓春.利用声成像测井数据实现岩石裂缝特征的自动识别[J].中国海上油气(地质),14(6):429-431.
[33]金燕,张旭.测井裂缝参数估算与储层裂缝评价方法研究[J].天然气工业(地质勘探)2002(5):64-67.
[34]Anil Kuman Tyagi等著,罗景美,李爱华译,赵文杰校.井眼电成像在碳酸盐岩储层孔隙度分析中的应用[J].测井与射孔,2003(2):23-27.
[35]张丽莉,刘瑞林.两种图像分割算法在FMI成像资料中的应用[J].江汉石油学院学报, 1999(12),21(4 ): 88-90.
[36]柯式镇,冯启宁.井壁成像测井资料目标体自动检测方法研究[J].石油大学学报(自然科版),2004,28(4):39-42.
[37]Jonathan Hall , Marco Ponzi , Mauro Gonfalini.Automatic Extraction and Characterisation of Geological Features and Textures from Borehole Images and Core Photographs.SPWLA 37th Annual Logging Symposium,Paper CCC,June 1996,16-19.
[38] Cheung,P.S.,and Heliot D.,1990,Workstation based fracture Evaluation using borehole images and wireline,Ann.Conf.Soc.Petrol. Eng.,Paper 20573.
[39]付建伟,肖立志,张中元.井下声电成像测井仪的现状与发展趋势[J].地球物理学进展, 2004(12),19(4):730-738.
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