致密砂岩泥质含量计算及泥质分布形式评价方法研究
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摘要
Z区为传统的煤炭及煤层气探采区,生产实际中上古生界的砂岩往往有较好的气测显示。为了更好地服务区块致密砂岩气的勘探开发,需要精确地进行岩性识别。通过录井资料分析,岩性较为致密的岩石往往物性条件较差,所以传统的泥质含量解释方法在研究区的预测效果较差,加之测井资料以煤田测井资料为主,有必要结合研究区现有的资料测试测井资料,建立泥质含量评价模型,从而更好地指导生产实际。基于粒度分析、矿物含量统计等方法得到Z-1井的泥质含量,基于多元回归建立泥质含量的预测模型,针对测井系列较全的Z-1井,利用Class测井解释程序求取不同形式的泥质含量,建立泥质分布形式的预测模型,提高了泥质含量的预测精度,最终评价基于常规煤田测井的致密砂岩储层泥质含量与泥质分布形式,经检验能够较好地满足实际需要。
Area Z is a traditional exploration area for coal and coalbed methane.In actual production,sandstones in Upper Paleozoic often have good gas-measurement show.In order to have better exploration and develop-ment of the tight sandstone gas in the area,lithology should be identified accurately.According to the analysis of logging data,the rocks with relatively dense lithology has relatively poor physical property,so the traditional shale content interpretation method can′ t predict well in the study area.In addition,logging data are mainly on coalfield.It is necessary to test logging data in combination with the existing data in the study area and establish shale content evaluation model to better guide the production practice.The shale content of Well Z-1 was obtained based on particle size analysis,mineral content statistics and other methods,and the forecast model of shale content was proposed based on multiple regression.For the Well Z-1 with complete logging se-ries,Class logging interpretation program was applied to calculating the shale content with different forms,and then forecast model of the shale distribution form was proposed,which provides higher forecasting precision of the shale content.Finally,the shale content and shale distribution forms of the tight sandstone reservoir based on the conventional coalfield logging were evaluated.It is proved that it can meet the actual demands.
Area Z is a traditional exploration area for coal and coalbed methane.In actual production,sandstones in Upper Paleozoic often have good gas-measurement show.In order to have better exploration and develop-ment of the tight sandstone gas in the area,lithology should be identified accurately.According to the analysis of logging data,the rocks with relatively dense lithology has relatively poor physical property,so the traditional shale content interpretation method can′ t predict well in the study area.In addition,logging data are mainly on coalfield.It is necessary to test logging data in combination with the existing data in the study area and establish shale content evaluation model to better guide the production practice.The shale content of Well Z-1 was obtained based on particle size analysis,mineral content statistics and other methods,and the forecast model of shale content was proposed based on multiple regression.For the Well Z-1 with complete logging se-ries,Class logging interpretation program was applied to calculating the shale content with different forms,and then forecast model of the shale distribution form was proposed,which provides higher forecasting precision of the shale content.Finally,the shale content and shale distribution forms of the tight sandstone reservoir based on the conventional coalfield logging were evaluated.It is proved that it can meet the actual demands.
引文
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[24]徐同台,等.中国含油气盆地黏土矿物[M].北京,石油工业出版社,2003.
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[26]沈建国.用密度声波时差和自然伽马测井曲线计算分散泥质结构泥质含量[J].地球物理测井,1989,13(2):13-17.
[27]韩保清,布志虹,王宏宇.胡状集地区泥质分布形式对储层测井响应的实验研究[J].江汉石油学院学报,2003,25(3):65-66.
[2]赵靖舟.天然气地质学[M].北京:石油工业出版社,2013.
[3]李舟波.地球物理测井数据处理与综合解释[M].北京:地质出版社,2018.
[4]雍世和,张超谟.测井数据处理与综合解释[M].东营:石油大学出版社,2002.
[5]车卓吾.测井资料分析手册[M].北京:石油工业出版社,1995.
[6]王建功,吴刚,陈燕,等.一种复杂砂岩储层泥质含量计算方法[J].石油钻采工艺,2009,31(增2):48-50.
[7]刘行军,杨双定,南力亚,等.陕北地区延长组长6段高伽马砂岩储层参数确定方法[J].中国石油勘探开发,2014,19(2):55-66.
[8]朱筱敏.沉积岩石学[M].北京:石油工业出版社,2008.
[9]康志勇.辽河盆地第三纪地层泥质含量测井解释方法研究[J].测井技术,1997,21(4):276-279.
[10]李光军.高精度碳氧比测井在泌阳凹陷的应用[J].测井技术,2015,39(2):217-220.
[11]徐延勇,薛乾坤.泥质含量求取方法综述[J].煤矿安全,2014,45(8)228-230.
[12]沈华.文安斜坡泥质含量计算方法研究[J].石油天然气学报,2010,32(6):410-412.
[13]王栋,谢俊,王金凯,等.金湖凹陷龙岗地区戴南组测井解释模型[J].西部探矿工程,2018,30(11):16-19.
[14]杨晓辉,王祝文,王文华,等.BP神经网络算法在火成岩泥质含量计算值的应用[J].世界地质,2015,34(4):1120-1124.
[15]袁东义,张金功,刘玉林,等.因子分析法在陆相致密砂岩及泥页岩储层泥质含量预测中的应用[J].矿物岩石,2017,37(4):110-116.
[16]安鹏,曹丹平.深度学习法在泥质含量预测中的应用[C]//CPS/SEG北京2018国际地球物理会议暨展览.北京,2018:1534-1537.
[17]司马立强,罗兴,张凤生,等.基于曲线重构的高伽马地层泥质含量计算方法[J].测井技术,2013,37(3):244-248.
[18]张儒.自然伽马能谱测井在神木双山区块的地质应用[J].国外测井技术,2018,39(2):44-48.
[19]赵军龙.测井方法原理[M].西安:陕西人民教育出版社,2008.
[20]程国华,袁祖贵,刘宁.用地层元素测井资料确定储层黏土含量[J].石油大学学报:自然科学版,2004,28(2):28-30.
[21]徐振明,陈嵘.泥质分布形式对储层产能的影响及计算方法初探[J].石油工业计算机应用,2011,72:37-40.
[22]谭廷栋.测井解释黏土矿物[J].石油钻采工艺,1987,6:25-32.
[23]赵杏媛,等.塔里木盆地粘人矿物[M].武汉:中国地质大学出版社,2001.
[24]徐同台,等.中国含油气盆地黏土矿物[M].北京,石油工业出版社,2003.
[25]徐杰,刘刚,展转盈,等.三塘湖盆地山西组低孔低渗储层特征及物性控制因素[J].非常规油气,2018,5(2):24-30.
[26]沈建国.用密度声波时差和自然伽马测井曲线计算分散泥质结构泥质含量[J].地球物理测井,1989,13(2):13-17.
[27]韩保清,布志虹,王宏宇.胡状集地区泥质分布形式对储层测井响应的实验研究[J].江汉石油学院学报,2003,25(3):65-66.