机器学习和向机器学习
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摘要
机器学习实际上已经存在了几十年或者也可以认为存在了几个世纪。追溯到17世纪,贝叶斯、拉普拉斯关于最小二乘法的推导和马尔可夫链,这些构成了机器学习广泛使用的工具和基础。1950年(艾伦·图灵提议建立一个学习机器)到2000年初(有深度学习的实际应用以及最近的进展,比如2012年的AlexNet),机器学习有了很大的进展。在过去几年中,深度学习在各种应用领域获得巨大的成功,并且随着一些新的应用模式的出现继续开辟新的领域。最近,由于从大数据中提取有经济价值信息的需要、各种类型的神经网络和计算能力获得较大进展,以及易于使用的程序代码的出现,促使机器学习在石油和天然气工业中流行。在本文中,我们将展示机器学习如何帮助地球科学家在更短的时间内完成日常任务。演示地球科学家从机器中学习到的知识,如文档和图像分割、测井相识别、岩石物理测井预测和断层解释,并利用这些技术来检查他们的工作质量,获得细微的洞察力。另一个优点是,这些方法通过提供更精确的训练数据集来优化机器学习工作流程,从而推动模型的持续学习和提高。
引文
AlBinHassan,N.M.,and K.Marfurt,2003,Fault detection using Hough transforms:73rd Annual International Meeting,SEG,Expanded Abstracts,1719-1721,https://doi.org/10.1190/1.1817639.
Bahorich,M.,and S.Farmer,1995,3-D seismic discontinuity for faults and stratigraphic features:The coherence cube:The Leading Edge,14,no.10,1053-1058,https://doi.org/10.1190/1.1437077.
Barnes,A.E.,2006,A filter to improve seismic discontinuity data for fault interpretation:Geophysics,71,no.3,P1-P4,https://doi.org/10.1190/1.2195988.
Bayes,T.,and M.Price,1763,An essay towards solving aproblem in the doctrine of chances:Philosophical Transactions,53,370-418,https://doi.org/10.1098/rstl.1763.0053.
Cohen,I.,and R.R.Coifman,2002,Local discontinuity measures for 3-d seismic data:Geophysics,67,no.6,1933-1945,https://doi.org/10.1190/1.1527094.
Cortes,C.,and V.Vapnik,1995,Support-vector networks:Machine Learning,20,no.3,273-297,https://doi.org/10.1007/BF00994018.
Crevier,D.,1993,AI:The tumultuous search for artificial intelligence:Basic Books.
Deng,J.,W.Dong,R.Socher,L.J.Li,K.Li,and L.FeiFei,2009,ImageNet:A large-scale hierarchical image database:Conference on Computer Vision and Pattern Recognition,IEEE,https://doi.org/10.1109/CVPR.2009.5206848.
Di,H.,and D.Gao,2014,Gray-level transformation and Canny edge detection for 3Dseismic discontinuity enhancement:Computers&Geosciences,72,192-200,https://doi.org/10.1016/j.cageo.2014.07.011.
Di,H.,and D.Gao,2016,Seismic attribute-aided fault detection in petroleum industry:A review,in D.Martin,ed.,Fault detection:Methods,applications and technology:Nova Science Publishers,53-80.
Di,H.,and D.Gao,2017,3Dseismic flexure analysis for subsurface fault detection and fracture chara-cterization:Pure and Applied Geophysics,174,no.3,747-761,https://doi.org/10.1007/s00024-016-1406-9.
Fukushima,K.,1980,Neocognitron:A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position:Biological Cybernetics,36,no.4,193-202,https://doi.org/10.1007/BF00344251.
Gersztenkorn,A.,and K.J.Marfurt,1999,Eigenstructure-based coherence computations as an aid to 3-d structural and stratigraphic mapping:Geophysics,64,no.5,1468-1479,https://doi.org/10.1190/1.1444651.
Goodfellow,I.J.,J.Pouget-Abadie,M.Mirza,B.Xu,D.Warde-Farley,S.Ozair,A.Courville,and Y.Bengio,2014,Generative adversarial networks:Proceedings of the 27th International Conference on Neural Information Processing Systems,2,2672-2680.
Greenspan,H.,B.van Ginneken,and R.M.Summers,2016,Guest editorial deep learning in medical imaging:Overview and future promise of an exciting new technique:Transactions on Medical Imaging,IEEE,35,no.5,1153-1159,https://doi.org/10.1109/TMI.2016.2553401.
Hale,D.,2013,Methods to compute fault images,extract fault surfaces,and estimate fault throws from 3Dseismic images:Geophysics,78,no.2,O33-O43,https://doi.org/10.1190/geo2012-0331.1.
Ho,T.K.,1995,Random decision forests:Proceedings of the 3rd International Conference on Document Analysis and Recognition,IEEE,278-282https://doi.org/10.1109/ICDAR.1995.598994.
Hochreiter,S.,and J.Schmidhuber,1997,Long short-term memory:Neural Computation,9,no.8,1735-1780,https://doi.org/10.1162/neco.1997.9.8.1735.
Hopfield,J.J.,1982,Neural networks and physical systems with emergent collective computational abilities:Proceedings of the National Academy of Sciences of the United States of America,79,no.8,2554-2558,https://doi.org/10.1073/pnas.79.8.2554.
Infante-Paez,L.,L.F.Cardona,B.McCullough,and R.Slatt,2017,Seismic analysis of paleotopography and stratigraphic controls on total organic carbon:Rich sweet spot distribution in the Woodford Shale,Oklahoma,USA:Interpretation,5,no.1,T33-T47,https://doi.org/10.1190/INT-2015-0151.1.
Jones,K.S.,1973,Index term weighting:Information Storage and Retrieval,9,no.11,619-633,https://doi.org/10.1016/0020-0271(73)90043-0.
Krizhevsky,A.,I.Sutskever,and G.E.Hinton,2012,ImageNet classification with deep convolutional neural networks:Proceedings of the 25th International Conference on Neural Information Processing Systems,1097-1105.
Laplace,P.,1812,Théorie analytique des probabilités:Courcier.
LeCun,Y.,C.Cortes,and C.Burges,2018,The MNIST database of handwritten digits,http://yann.lecun.com/exdb/mnist/,accessed 8October 2018.
Legendre,A.M.,1805,Nouvelles méthodes pour la détermination des orbites des comètes:Firmin Didot.
Linnainmaa,S.,1970,The representation of the cumulative rounding error of an algorithm as a Taylor expansion of the local rounding errors:M.S.thesis,University of Helsinki.
Luo,Y.,W.Higgs,and W.Kowalik,1996,Edge detection and stratigraphic analysis using 3Dseismic data:66th Annual International Meeting,SEG,Expanded Abstracts,324-327,https://doi.org/10.1190/1.1826632.
Marfurt,K.J.,R.L.Kirlin,S.L.Farmer,and M.S.Bahorich,1998,3-D seismic attributes using a semblance-based coherency algorithm:Geophysics,63,no.4,1150-1165,https://doi.org/10.1190/1.1444415.
Markov,A.A.,1906,Extension of the law of large numbers to dependent quantities[in Russian]:Izvestiya Fiziko-Matematicheskikh Obschestva Kazan University,15,135-156.
McCarthy,J.,and E.Feigenbaum,1990,Arthur Samuel:Pioneer in machine learning:AI Magazine,11,no.3,10-11.
Nunn,J.A.,2012,Burial and thermal history of the Haynesville Shale:Implications for overpressure,gas generation,and natural hydrofracture:GCAGS,1,81-96.
Pedersen,S.I.,T.Randen,L.Sonneland,and.Steen,2002,Automatic fault extraction using artificial ants:72nd Annual International Meeting,SEG,Expanded Abstracts,512-515.
Qi,X.,and K.Marfurt,2017,Volumetric aberrancy to map subtle faults and flexures:87th Annual International Meeting,SEG,Expanded Abstracts,3443-3447,https://doi.org/10.1190/segam2017-17632807.1.
Roberts,A.,2001,Curvature attributes and their application to 3Dinterpreted horizons:First Break,19,no.2,85-100,https://doi.org/10.1046/j.0263-5046.2001.00142.x.
Rosenblatt,F.,1958,The perceptron:A probabilistic model for information storage and organization in the brain:Psychological Review,65,no.6,386-408,https://doi.org/10.1037/h0042519.
Rumelhart,D.,G.Hinton,and R.Williams,1986,Learning representations by back-propagating errors:Nature,323,533-536,https://doi.org/10.1038/323533a0.
Tingdahl,K.M.,and M.De Rooij,2005,Semiautomatic detection of faults in 3D seismic data:Geophysical Prospecting,53,no.4,533-542,https://doi.org/10.1111/j.1365-2478.2005.00489.x.
Tovaglieri,F.,and A.George,2012,Sedimentology and image-log analysis of the Jurassic Deltaic Plover Formation,Browse Basin,Australian North West Shelf:Presented at Annual Convention and Exhibition,AAPG.
Turing,A.,1950,Computing machinery and intelligence:Mind,59,433-460.
Wang,S.,S.Yuan,B.Yan,Y.He,and W.Sun,2016,Directional complex-valued coherence attributes for discontinuous edge detection:Journal of Applied Geophysics,129,1-7,https://doi.org/10.1016/jj.appgeo.2016.03.016.
Wang,Z.,Z.Long,G.AlRegib,A.Asjad,and M.A.Deriche,2014,Automatic fault tracking across seismic volumes via tracking vectors:International Conference on Image Processing,IEEE,5851-5855.
Watkins,C.J.,1989,Learning from delayed rewards:Ph.D.thesis,University of Cambridge.
Bahorich,M.,and S.Farmer,1995,3-D seismic discontinuity for faults and stratigraphic features:The coherence cube:The Leading Edge,14,no.10,1053-1058,https://doi.org/10.1190/1.1437077.
Barnes,A.E.,2006,A filter to improve seismic discontinuity data for fault interpretation:Geophysics,71,no.3,P1-P4,https://doi.org/10.1190/1.2195988.
Bayes,T.,and M.Price,1763,An essay towards solving aproblem in the doctrine of chances:Philosophical Transactions,53,370-418,https://doi.org/10.1098/rstl.1763.0053.
Cohen,I.,and R.R.Coifman,2002,Local discontinuity measures for 3-d seismic data:Geophysics,67,no.6,1933-1945,https://doi.org/10.1190/1.1527094.
Cortes,C.,and V.Vapnik,1995,Support-vector networks:Machine Learning,20,no.3,273-297,https://doi.org/10.1007/BF00994018.
Crevier,D.,1993,AI:The tumultuous search for artificial intelligence:Basic Books.
Deng,J.,W.Dong,R.Socher,L.J.Li,K.Li,and L.FeiFei,2009,ImageNet:A large-scale hierarchical image database:Conference on Computer Vision and Pattern Recognition,IEEE,https://doi.org/10.1109/CVPR.2009.5206848.
Di,H.,and D.Gao,2014,Gray-level transformation and Canny edge detection for 3Dseismic discontinuity enhancement:Computers&Geosciences,72,192-200,https://doi.org/10.1016/j.cageo.2014.07.011.
Di,H.,and D.Gao,2016,Seismic attribute-aided fault detection in petroleum industry:A review,in D.Martin,ed.,Fault detection:Methods,applications and technology:Nova Science Publishers,53-80.
Di,H.,and D.Gao,2017,3Dseismic flexure analysis for subsurface fault detection and fracture chara-cterization:Pure and Applied Geophysics,174,no.3,747-761,https://doi.org/10.1007/s00024-016-1406-9.
Fukushima,K.,1980,Neocognitron:A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position:Biological Cybernetics,36,no.4,193-202,https://doi.org/10.1007/BF00344251.
Gersztenkorn,A.,and K.J.Marfurt,1999,Eigenstructure-based coherence computations as an aid to 3-d structural and stratigraphic mapping:Geophysics,64,no.5,1468-1479,https://doi.org/10.1190/1.1444651.
Goodfellow,I.J.,J.Pouget-Abadie,M.Mirza,B.Xu,D.Warde-Farley,S.Ozair,A.Courville,and Y.Bengio,2014,Generative adversarial networks:Proceedings of the 27th International Conference on Neural Information Processing Systems,2,2672-2680.
Greenspan,H.,B.van Ginneken,and R.M.Summers,2016,Guest editorial deep learning in medical imaging:Overview and future promise of an exciting new technique:Transactions on Medical Imaging,IEEE,35,no.5,1153-1159,https://doi.org/10.1109/TMI.2016.2553401.
Hale,D.,2013,Methods to compute fault images,extract fault surfaces,and estimate fault throws from 3Dseismic images:Geophysics,78,no.2,O33-O43,https://doi.org/10.1190/geo2012-0331.1.
Ho,T.K.,1995,Random decision forests:Proceedings of the 3rd International Conference on Document Analysis and Recognition,IEEE,278-282https://doi.org/10.1109/ICDAR.1995.598994.
Hochreiter,S.,and J.Schmidhuber,1997,Long short-term memory:Neural Computation,9,no.8,1735-1780,https://doi.org/10.1162/neco.1997.9.8.1735.
Hopfield,J.J.,1982,Neural networks and physical systems with emergent collective computational abilities:Proceedings of the National Academy of Sciences of the United States of America,79,no.8,2554-2558,https://doi.org/10.1073/pnas.79.8.2554.
Infante-Paez,L.,L.F.Cardona,B.McCullough,and R.Slatt,2017,Seismic analysis of paleotopography and stratigraphic controls on total organic carbon:Rich sweet spot distribution in the Woodford Shale,Oklahoma,USA:Interpretation,5,no.1,T33-T47,https://doi.org/10.1190/INT-2015-0151.1.
Jones,K.S.,1973,Index term weighting:Information Storage and Retrieval,9,no.11,619-633,https://doi.org/10.1016/0020-0271(73)90043-0.
Krizhevsky,A.,I.Sutskever,and G.E.Hinton,2012,ImageNet classification with deep convolutional neural networks:Proceedings of the 25th International Conference on Neural Information Processing Systems,1097-1105.
Laplace,P.,1812,Théorie analytique des probabilités:Courcier.
LeCun,Y.,C.Cortes,and C.Burges,2018,The MNIST database of handwritten digits,http://yann.lecun.com/exdb/mnist/,accessed 8October 2018.
Legendre,A.M.,1805,Nouvelles méthodes pour la détermination des orbites des comètes:Firmin Didot.
Linnainmaa,S.,1970,The representation of the cumulative rounding error of an algorithm as a Taylor expansion of the local rounding errors:M.S.thesis,University of Helsinki.
Luo,Y.,W.Higgs,and W.Kowalik,1996,Edge detection and stratigraphic analysis using 3Dseismic data:66th Annual International Meeting,SEG,Expanded Abstracts,324-327,https://doi.org/10.1190/1.1826632.
Marfurt,K.J.,R.L.Kirlin,S.L.Farmer,and M.S.Bahorich,1998,3-D seismic attributes using a semblance-based coherency algorithm:Geophysics,63,no.4,1150-1165,https://doi.org/10.1190/1.1444415.
Markov,A.A.,1906,Extension of the law of large numbers to dependent quantities[in Russian]:Izvestiya Fiziko-Matematicheskikh Obschestva Kazan University,15,135-156.
McCarthy,J.,and E.Feigenbaum,1990,Arthur Samuel:Pioneer in machine learning:AI Magazine,11,no.3,10-11.
Nunn,J.A.,2012,Burial and thermal history of the Haynesville Shale:Implications for overpressure,gas generation,and natural hydrofracture:GCAGS,1,81-96.
Pedersen,S.I.,T.Randen,L.Sonneland,and.Steen,2002,Automatic fault extraction using artificial ants:72nd Annual International Meeting,SEG,Expanded Abstracts,512-515.
Qi,X.,and K.Marfurt,2017,Volumetric aberrancy to map subtle faults and flexures:87th Annual International Meeting,SEG,Expanded Abstracts,3443-3447,https://doi.org/10.1190/segam2017-17632807.1.
Roberts,A.,2001,Curvature attributes and their application to 3Dinterpreted horizons:First Break,19,no.2,85-100,https://doi.org/10.1046/j.0263-5046.2001.00142.x.
Rosenblatt,F.,1958,The perceptron:A probabilistic model for information storage and organization in the brain:Psychological Review,65,no.6,386-408,https://doi.org/10.1037/h0042519.
Rumelhart,D.,G.Hinton,and R.Williams,1986,Learning representations by back-propagating errors:Nature,323,533-536,https://doi.org/10.1038/323533a0.
Tingdahl,K.M.,and M.De Rooij,2005,Semiautomatic detection of faults in 3D seismic data:Geophysical Prospecting,53,no.4,533-542,https://doi.org/10.1111/j.1365-2478.2005.00489.x.
Tovaglieri,F.,and A.George,2012,Sedimentology and image-log analysis of the Jurassic Deltaic Plover Formation,Browse Basin,Australian North West Shelf:Presented at Annual Convention and Exhibition,AAPG.
Turing,A.,1950,Computing machinery and intelligence:Mind,59,433-460.
Wang,S.,S.Yuan,B.Yan,Y.He,and W.Sun,2016,Directional complex-valued coherence attributes for discontinuous edge detection:Journal of Applied Geophysics,129,1-7,https://doi.org/10.1016/jj.appgeo.2016.03.016.
Wang,Z.,Z.Long,G.AlRegib,A.Asjad,and M.A.Deriche,2014,Automatic fault tracking across seismic volumes via tracking vectors:International Conference on Image Processing,IEEE,5851-5855.
Watkins,C.J.,1989,Learning from delayed rewards:Ph.D.thesis,University of Cambridge.