基于地震反演参数的煤层气储层甜点区预测
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摘要
为实现煤层气甜点区的精准预测,以提高储层开采效率,依据煤层气甜点区的界定条件,充分发挥地震反演参数物理意义明确和在显示维度上的优势,确定以煤层气储层的吨煤含气量、煤厚、埋深、构造应力、裂缝发育密度以及煤体结构类型分布这6类地震反演参数作为煤层气甜点区的预测指标。采用改进的熵权法计算预测指标的权重值,以沿层切片的方式显示目标储层的甜点区预测结果,并对比分析产气井位置的预测值与日均产气量。研究结果表明:X2井的预测值出现错误,其余井的预测值与日均产气量吻合较好,正确率达85%;基于上述6类地震反演参数,利用改进的熵权法进行煤层气甜点区预测具有可行性。
Accurate prediction of CBM sweet spot would improve the reservoir exploration efficiency.In this paper,based on the definition condition for CBM sweet-spot and took advantage of seismic inversion parameters in physical significance and 3 D display,we decided to take the gas content,coal-bed thickness,reservoir depth,tectonic stress,fracture density and coal structure types distribution as the predictors for CBM sweet-spot prediction.By using modified entropy method to calculate the weight of predictors,the prediction result of CBM sweet-spot for target reservoir would be exhibited in layer slice style.The comparative analysis between the prediction values and the daily gas production in whole well position shown that the two values were in good agreement except X2 well with an accuracy rate of 85%.Accordingly,the research result exhibited that the method proposed by modified entropy method based on the six types seismic inversion parameters mentioned above was feasible in CBM sweet spot prediction.
Accurate prediction of CBM sweet spot would improve the reservoir exploration efficiency.In this paper,based on the definition condition for CBM sweet-spot and took advantage of seismic inversion parameters in physical significance and 3 D display,we decided to take the gas content,coal-bed thickness,reservoir depth,tectonic stress,fracture density and coal structure types distribution as the predictors for CBM sweet-spot prediction.By using modified entropy method to calculate the weight of predictors,the prediction result of CBM sweet-spot for target reservoir would be exhibited in layer slice style.The comparative analysis between the prediction values and the daily gas production in whole well position shown that the two values were in good agreement except X2 well with an accuracy rate of 85%.Accordingly,the research result exhibited that the method proposed by modified entropy method based on the six types seismic inversion parameters mentioned above was feasible in CBM sweet spot prediction.
引文
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[15]许亚坤,王昆,张鹏.永城矿区煤层气主控因素分析及含气量预测研究[J].煤炭科学技术,2017,45(5):170-174.XU Yakun,WANG Kun,ZHANG Peng.Study on coalbed methane main control factors and gas content prediction in Yongcheng Mining Area[J].Coal Science and Technology,2017,45(5):170-174.
[16]傅雪海,秦勇,韦重韬.煤层气地质学[M].徐州:中国矿业大学出版社,2007.
[17]李登华,高煖,刘卓亚,等.中美煤层气资源分布特征和开发现状对比及启示[J].煤炭科学技术,2018,46(1):252-261.LI Denghua,GAO Xuan,LIU Zhuoya,et al.Comparison and revelation of coalbed methane resources distribution characteristics and development status between China and America[J].Coal Science and Technology,2018,46(1):252-261.
[18]李英海,周建中.基于改进熵权和Vague集的多目标防洪调度决策方法[J].水电能源科学,2010,28(6):38-41.LI Yinhai,ZHOU Jianzhong.Modified entropy method and Vague set based multi-objective flood control decision making approach[J].Water Resources&Power,2010,28(6):38-41.
[2]CHEN Xinping,HUO Quanming,LIN Jiandong,et al.The inverse correlations between methane content and elastic parameters of coal-bed methane reservoirs[J].Geophysics,2013,78(4):D237-D248.
[3]闫文华,陈宗翠,马喜梅,等.煤层气地震解释技术应用及效果:以沁水盆地郑庄区块三维为例[J].石油地球物理勘探,2012,47(S1):66-71.YAN Wenhua,CHEN Zongcui,MA Ximei,et al.3D seismic interpretation of coalbed methane in Zhengzhuang Block,Qinshui Basin[J].Oil Geophysical Prospecting,2012,47(S1):66-71.
[4]朱正平,雷克辉,潘仁芳.沁水盆地和顺区块基于地震多属性分析的煤层含气量预测[J].石油物探,2015,54(2):226-233.ZHU Zhengping,LEI Kehui,PAN Renfang.Coal seam gas content prediction based on seismic multi-attributes analysis in Heshun Block,Qinshui Basin[J].Geophysical Prospecting for Petroleum,2015,54(2):226-233.
[5]陈勇,陈洪德,关达,等.基于主控因素的煤层气富集区地震预测技术应用研究[J].石油物探,2013,52(4):426-431.CHEN Yong,CHEN Hongde,GUAN Da,et al.Application of coalbed methane accumulation zone seismic prediction technology based on main geological controlling factors[J].Geophysical Prospecting for Petroleum,2013,52(4):426-431.
[6]霍丽娜,徐礼贵,邵林海,等.煤层气甜点区地震预测技术及其应用[J].天然气工业,2014,34(8):46-52.HUO Lina,XU Ligui,SHAO Linhai,et al.Seismic prediction technologies of CBM sweet spots and their application[J].Natural Gas Industry,2014,34(8):46-52.
[7]彭苏萍,杜文凤,殷裁云,等.高丰度煤层气富集区地球物理识别[J].煤炭学报,2014,39(8):1398-1403.PENG Suping,DU Wenfeng,YIN Caiyun,et al.Geophysical identification of high abundance coalbed methane rich region[J].Journal of China Coal Society,2014,39(8):1398-1403.
[8]孙斌,杨敏芳,孙霞,等.基于地震AVO属性的煤层气富集区预测[J].天然气工业,2010,30(6):15-18.SUN Bin,YANG Minfang,SUN Xia,et al.Prediction of coalbed methane enrichment zones based on AVO attributes[J].Natural Gas Industry,2010,30(6):15-18.
[9]谢春临,关晓巍,张广颖,等.海拉尔盆地呼和湖凹陷煤层气预测方法[J].石油地球物理勘探,2013,48(1):58-63.XIE Chunlin,GUAN Xiaowei,ZHANG Guangyin,et al.Coalbed methane prediction in Huhehu Depression,Hailar Basin[J].Oil Geophysical Prospecting,2013,48(1):58-63.
[10]QI Xuemei,ZHANG Shaochong.Application of seismic multi-attribute fusion method based on D-S evidence theory in prediction of CBM-enriched area[J].Applied Geophysics,2012,9(1):80-86.
[11]李艳芳,程建远,王成.基于支持向量机的地震属性优选及煤层气预测[J].煤田地质与勘探,2012,40(6):75-78.LI Yanfang,CHENG Jianyun,WANG Cheng.Seismic attribute optimization based on support vector machine and coalbed methane prediction[J].Coal Geology&Exploration,2012,40(6):75-78.
[12]陈贵武,董守华,吴海波,等.高丰度煤层气富集区地球物理定量识别技术研究与应用[J].地球物理学进展,2014,29(5):2151-2156.CHEN Guiwu,DONG Shouhua,WU Haibo,et al.Research and application of quantitative geophysics recognition in high abundance of coalbed methane-rich region[J].Progress in Geophysics,2014,29(5):2151-2156.
[13]张春朋,吴财芳,李腾,等.主成分分析法在煤层气选区评价中的应用[J].煤炭科学技术,2016,44(8):137-142.ZHANG Chunpeng,WU Caifang,Li Teng,et al.Principal component analysis method applied to evaluation on coalbed methane block selection[J].Coal Science and Technology,2016,44(8):137-142.
[14]车向前,张欣欣,边莉.利用改进组合交叉熵实现煤层气储层地震属性约简[J].煤田地质与勘探,2017,45(3):131-135.CHE Xiangqian,ZHANG Xinxin,BIAN Li.Seismic attribute reduction of CBM reservoir using improved combined cross entropy[J].Coal Geology&Exploration,2017,45(3):131-135.
[15]许亚坤,王昆,张鹏.永城矿区煤层气主控因素分析及含气量预测研究[J].煤炭科学技术,2017,45(5):170-174.XU Yakun,WANG Kun,ZHANG Peng.Study on coalbed methane main control factors and gas content prediction in Yongcheng Mining Area[J].Coal Science and Technology,2017,45(5):170-174.
[16]傅雪海,秦勇,韦重韬.煤层气地质学[M].徐州:中国矿业大学出版社,2007.
[17]李登华,高煖,刘卓亚,等.中美煤层气资源分布特征和开发现状对比及启示[J].煤炭科学技术,2018,46(1):252-261.LI Denghua,GAO Xuan,LIU Zhuoya,et al.Comparison and revelation of coalbed methane resources distribution characteristics and development status between China and America[J].Coal Science and Technology,2018,46(1):252-261.
[18]李英海,周建中.基于改进熵权和Vague集的多目标防洪调度决策方法[J].水电能源科学,2010,28(6):38-41.LI Yinhai,ZHOU Jianzhong.Modified entropy method and Vague set based multi-objective flood control decision making approach[J].Water Resources&Power,2010,28(6):38-41.