基于覆盖粗糙集的地震属性约简及其应用
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摘要
在油、气预测中,并非用到的地震属性越多,预测效果就越好。由于计算误差等影响,冗余地震属性反而会使预测的准确率降低。目前地震属性约简较多采用粗糙集的思想优化地震属性。然而,等价关系在有些情况下难以实现,而且连续地震属性经离散化处理后会造成原始数据失真,因此本文提出基于覆盖粗糙集的地震属性约简方法,不仅有效解决了地震属性等价关系和数据失真的问题,还克服了粗糙集理论在地震属性约简中应用的局限性,使粗糙集理论更具一般化。仿真试验和实际应用表明,通过样本地震属性约简,可以提高油、气预测精度。
In oil & gas prediction,it is not always true that the more the index variables of seismic attribute data are,the better effect of prediction is.On the contrary,the classification accuracy will reduce by the redundant index variables because of the calculation error.Nowadays,rough set is mostly applied to optimize seismic attributes in the seismic attribute reduction.However,it is difficult to achieve the equivalence relation in some cases,and the process of discretizing continuous attributes can lead to the distortion of the original data.Therefore,the seismic attribute reduction based on the covering rough set is presented in this paper.This approach not only solves problems mentioned above,but also overcomes limits in rough set application,and makes the rough set theory more generalized.The simulation and actual experiments reveal that the results of the seismic attribute reduction application can improve oil & gas prediction precision.
In oil & gas prediction,it is not always true that the more the index variables of seismic attribute data are,the better effect of prediction is.On the contrary,the classification accuracy will reduce by the redundant index variables because of the calculation error.Nowadays,rough set is mostly applied to optimize seismic attributes in the seismic attribute reduction.However,it is difficult to achieve the equivalence relation in some cases,and the process of discretizing continuous attributes can lead to the distortion of the original data.Therefore,the seismic attribute reduction based on the covering rough set is presented in this paper.This approach not only solves problems mentioned above,but also overcomes limits in rough set application,and makes the rough set theory more generalized.The simulation and actual experiments reveal that the results of the seismic attribute reduction application can improve oil & gas prediction precision.
引文
[1]Eastwood J.Introduction-The attribute explosion.The Leading Edge,2002,21(10):994～995
[2]Satinder C,Kurt J M.Emerging and future trends inseismic attributes.The Leading Edge,2008,27(3):298～318
[3]Jones I F,Levy S.Signal-to-noise ratio enhancement inmultichannel seismic data via the Karhunen-Loevetransform.Geophysical Prospecting,1987,35(1):12～32
[4]丁峰,尹成,徐峰等.一种基于灵敏属性分析的相关聚类属性优化方法.石油地球物理勘探,2008,43(5):568～572Ding Feng,Yin Cheng,Xu Feng et al.An optimizingmethod of correlative cluster attribute based on sensi-tive attribute analysis.OGP,2008,43(5):568～572
[5]张长开,姜秀娣,朱振宇等.基于支持向量机的属性优选和储层预测.石油地球物理勘探,2012,47(2):282～285Zhang Changkai,Jiang Xiudi,Zhu Zhenyu et al.At-tributes selection and reservoir prediction based onsupport vector machine.OGP,2012,47(2):282～285
[6]黄捍东,赵迪,张如伟等.基于灰关联和遗传算法的地震属性优化方法.石油地球物理勘探,2010,45(3):381～383,391Huang Handong,Zhao Di,Zhang Ruwei et al.Seis-mic attribute optimization method based on grey rela-tional analysis and genetic algorithm.OGP,2010,45(3):381～383,391
[7]Liu H J,Feng B Q,Li W.An approach to minimumattribute reduction.Proceedings of the IEEE Inter-national Conference on Automation and Logistics,Qingdao,China,2008,1589～1593
[8]王永刚,乐友喜,张军华.地震属性分析技术.山东东营:中国石油大学出版社,2007
[9]Liu H J,Feng B Q,Wei J J.The method of the leastreduction in oil reservoir based on rough set particleswarm.Information Technology Journal,2007,6(6):865～871
[10]刘宏杰,冯博琴,李文捷等.粗糙集属性约简判别分析方法及其应用.西安交大学报,2007,41(8):939～943Liu Hongjie,Feng Boqin,Li Wenjie et al.Discrimina-tion method of rough set attribute reduction and itsapplications.Journal of Xi’an Jiaotong University,2007,41(8):939～943
[11]印兴耀,周静毅.地震属性优化方法综述.石油地球物理勘探,2005,40(4):482～489Yin Xingyao,Zhou Jingyi.Summary of optimummethods of seismic attributes.OGP,2005,40(4):482～489
[12]Pawlak Z.Rough sets.International Journal ofComputer and Information Sciences,1982,11(5):341～356
[13]Pawlak Z.Rough Sets-Theoretical Aspects of Rea-soning about Data.Kluwer Academic Publishers,Boston,1991
[14]Puntip P,Nick C.Integrating rough set theory andmedical.Applied Mathematics Letters,2008,21(4):400～403
[15]Cui Y Q,Shi K Q.Function S-rough sets and its ap-plications.Journal of Systems Engineering and E-lectronics,2006,17(2):331～338
[16]刘少辉,盛秋戬,吴斌等.Rough集高效算法的研究.计算机学报,2003,26(5):524～529Liu Shaohui,Sheng Qiujian,Wu Bin et al.Researchon efficient algorithms for rough set methods.Chi-nese Journal of Computers,2003,26(5):524～529
[17]Zhao S Y,Eric C C T.On fuzzy approximation opera-tors in attribute reduction with fuzzy rough sets.In-formation Sciences,2008,178(16):3163～3176
[18]Liu M,Shao M W,Zhang W X et al.Reduction meth-od for concept lattices based on rough set theory andits application.Computers&Mathematics with Ap-plications,2007,53(9):1390～1410
[19]Zhu W,Wang F Y.On three types of covering-basedrough sets.IEEE Transactions on Knowledge andData Engineering,2007,19(8):1131～1144
[20]胡军,王国胤.覆盖粒度空间的层次模型.南京大学学报(自然科学),2008,44(5):551～558Hu Jun,Wang Guoyin.Hierarchical model of cover-ing granular space.Journal of Nanjing University(Natural Sciences),2008,44(5):551～558
[21]Zakowski E.Approximations in the space(U,Ⅱ).Demonstration Mathematica,1983,16(40):761～769
[22]Zhu W,Wang F Y.Reduction and axiomization ofcovering generalized rough sets.Information Sci-ences,2003,152(1):217～230
[23]Chen D G,Wang C Z,Hu Q H.A new approach toattribute reduction of consistent and inconsistent cov-ering decision systems with covering rough sets.In-formation Sciences,2007,177(17):3500～3518
[24]Hu Q H,Yu D R,Liu J F et al.Neighborhood roughset based heterogeneous feature subset selection.In-formation Sciences,2008,178(18):3577～3594
[25]Hu Q H,Yu D R,Xie Z X.Neighborhood classifiers.Expert systems with Applications,2008,34(2):866～876
[2]Satinder C,Kurt J M.Emerging and future trends inseismic attributes.The Leading Edge,2008,27(3):298～318
[3]Jones I F,Levy S.Signal-to-noise ratio enhancement inmultichannel seismic data via the Karhunen-Loevetransform.Geophysical Prospecting,1987,35(1):12～32
[4]丁峰,尹成,徐峰等.一种基于灵敏属性分析的相关聚类属性优化方法.石油地球物理勘探,2008,43(5):568～572Ding Feng,Yin Cheng,Xu Feng et al.An optimizingmethod of correlative cluster attribute based on sensi-tive attribute analysis.OGP,2008,43(5):568～572
[5]张长开,姜秀娣,朱振宇等.基于支持向量机的属性优选和储层预测.石油地球物理勘探,2012,47(2):282～285Zhang Changkai,Jiang Xiudi,Zhu Zhenyu et al.At-tributes selection and reservoir prediction based onsupport vector machine.OGP,2012,47(2):282～285
[6]黄捍东,赵迪,张如伟等.基于灰关联和遗传算法的地震属性优化方法.石油地球物理勘探,2010,45(3):381～383,391Huang Handong,Zhao Di,Zhang Ruwei et al.Seis-mic attribute optimization method based on grey rela-tional analysis and genetic algorithm.OGP,2010,45(3):381～383,391
[7]Liu H J,Feng B Q,Li W.An approach to minimumattribute reduction.Proceedings of the IEEE Inter-national Conference on Automation and Logistics,Qingdao,China,2008,1589～1593
[8]王永刚,乐友喜,张军华.地震属性分析技术.山东东营:中国石油大学出版社,2007
[9]Liu H J,Feng B Q,Wei J J.The method of the leastreduction in oil reservoir based on rough set particleswarm.Information Technology Journal,2007,6(6):865～871
[10]刘宏杰,冯博琴,李文捷等.粗糙集属性约简判别分析方法及其应用.西安交大学报,2007,41(8):939～943Liu Hongjie,Feng Boqin,Li Wenjie et al.Discrimina-tion method of rough set attribute reduction and itsapplications.Journal of Xi’an Jiaotong University,2007,41(8):939～943
[11]印兴耀,周静毅.地震属性优化方法综述.石油地球物理勘探,2005,40(4):482～489Yin Xingyao,Zhou Jingyi.Summary of optimummethods of seismic attributes.OGP,2005,40(4):482～489
[12]Pawlak Z.Rough sets.International Journal ofComputer and Information Sciences,1982,11(5):341～356
[13]Pawlak Z.Rough Sets-Theoretical Aspects of Rea-soning about Data.Kluwer Academic Publishers,Boston,1991
[14]Puntip P,Nick C.Integrating rough set theory andmedical.Applied Mathematics Letters,2008,21(4):400～403
[15]Cui Y Q,Shi K Q.Function S-rough sets and its ap-plications.Journal of Systems Engineering and E-lectronics,2006,17(2):331～338
[16]刘少辉,盛秋戬,吴斌等.Rough集高效算法的研究.计算机学报,2003,26(5):524～529Liu Shaohui,Sheng Qiujian,Wu Bin et al.Researchon efficient algorithms for rough set methods.Chi-nese Journal of Computers,2003,26(5):524～529
[17]Zhao S Y,Eric C C T.On fuzzy approximation opera-tors in attribute reduction with fuzzy rough sets.In-formation Sciences,2008,178(16):3163～3176
[18]Liu M,Shao M W,Zhang W X et al.Reduction meth-od for concept lattices based on rough set theory andits application.Computers&Mathematics with Ap-plications,2007,53(9):1390～1410
[19]Zhu W,Wang F Y.On three types of covering-basedrough sets.IEEE Transactions on Knowledge andData Engineering,2007,19(8):1131～1144
[20]胡军,王国胤.覆盖粒度空间的层次模型.南京大学学报(自然科学),2008,44(5):551～558Hu Jun,Wang Guoyin.Hierarchical model of cover-ing granular space.Journal of Nanjing University(Natural Sciences),2008,44(5):551～558
[21]Zakowski E.Approximations in the space(U,Ⅱ).Demonstration Mathematica,1983,16(40):761～769
[22]Zhu W,Wang F Y.Reduction and axiomization ofcovering generalized rough sets.Information Sci-ences,2003,152(1):217～230
[23]Chen D G,Wang C Z,Hu Q H.A new approach toattribute reduction of consistent and inconsistent cov-ering decision systems with covering rough sets.In-formation Sciences,2007,177(17):3500～3518
[24]Hu Q H,Yu D R,Liu J F et al.Neighborhood roughset based heterogeneous feature subset selection.In-formation Sciences,2008,178(18):3577～3594
[25]Hu Q H,Yu D R,Xie Z X.Neighborhood classifiers.Expert systems with Applications,2008,34(2):866～876
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