基于非常快速模拟退火法的页岩岩心双重区域重构方法
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摘要
页岩储层微观结构在储层开发评价和渗流机理研究方面的重要性日益凸显。但是页岩储层具有低孔、特低渗透、强非均质性和各向异性等特征,应用常规物理实验方法在研究微观渗流方面存在明显的局限性。数字岩心技术已成为研究储层微观结构的重要方法之一,重构方法有其较好的准确性和可靠性。以真实页岩岩心扫描电镜二维图像为基础,利用软件对图像进行分析和数据提取,应用传统模拟退火法重构页岩岩心。针对重构中的问题总结出基于非常快速模拟退火法和双重区域的页岩岩心重构方法。通过改进算法,大幅度的提高重构速度;针对页岩孔隙分布特征,对页岩进行分区域重构,使重构结果更加接近真实页岩岩心。
The importance of shale reservoir microstructure on field appraisal and flow mechanism has become increasingly prominent. But microscopic flow of shale reservoir cannot be studied effectively by conventional laboratory experiments and approaches for the unique characteristics of extra-low permeability,low porosity,serious anisotropy and heterogeneity. Digital core technology has become an important method in studying reservoir microstructure. Reconstruction methods have the accuracy and reliability. Shale core has been reconstructed by using traditional simulated annealing method based on the real shale SEM 2D images and data extracted by software. In order to solve the problem in reconstruction,an approach based on dual-region strategy and very fast simulated annealing(VFSA)algorithm is proposed in this paper. Using the new algorithm makes a significant improvement of computing efficiency. The shale is reconstructed in dual-region due to the pore distribution characteristics of shale. The results show that real pore distribution features are characterized better by this new approach.
The importance of shale reservoir microstructure on field appraisal and flow mechanism has become increasingly prominent. But microscopic flow of shale reservoir cannot be studied effectively by conventional laboratory experiments and approaches for the unique characteristics of extra-low permeability,low porosity,serious anisotropy and heterogeneity. Digital core technology has become an important method in studying reservoir microstructure. Reconstruction methods have the accuracy and reliability. Shale core has been reconstructed by using traditional simulated annealing method based on the real shale SEM 2D images and data extracted by software. In order to solve the problem in reconstruction,an approach based on dual-region strategy and very fast simulated annealing(VFSA)algorithm is proposed in this paper. Using the new algorithm makes a significant improvement of computing efficiency. The shale is reconstructed in dual-region due to the pore distribution characteristics of shale. The results show that real pore distribution features are characterized better by this new approach.
引文
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[24]Фren P E,Bakke S.Reconstruction of Berea and stone and porescale modelling of wettability effects[J].Journal of Petroleum Science and Engineering,2003,39(3):177-199.
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[34]王晨晨,姚军,杨永飞,等.碳酸盐岩双孔隙数字岩心结构特征分析[J].中国石油大学学报:自然科学版,2013,37(2):71-74.Wang Chenchen,Yao Jun,Yang Yongfei,et al.Structure characteristics analysis of carbonate dual pore digital rock[J].Journal of China University of Petroleum:Edition of Natural Science,2013,37(2):71-74.
[35]张季如,祝杰,黄丽,等.土壤微观结构定量分析的IPP图像技术研究[J].武汉理工大学学报,2008,30(4):80-83.Zhang Jiru,Zhu Jie,Huang Li,et al.IPP image technique used for quantitative analysis of soil microstructure[J].Journal of Wuhan University of Technology,2008,30(4):80-83.
[36]Sen M K,Stoffa P L.Bayesian inference,Gibbs’sampler and uncertainty estimation in geophysical inversion[J].Geophysical Prospecting,1996,44(2):313-350.
[37]Xin Li.A very fast simulated re-annealing(VFSA)approach for land data assimilation[J].Computer&Geosciences,2004,30(3):239-248.
[2]苗文培,姜汉桥,葛洪魁,等.页岩气储层蠕变特性及其对页岩气开发的影响[J].油气地质与采收率,2014,21(4):97-100.Miao Wenpei,Jiang Hanqiao,Ge Hongkui,et al.Gas shale creep and its influence on the shale gas development[J].Petroleum Geology and Recovery Efficiency,2014,21(4):97-100.
[3]康毅力,陈强,游利军,等.页岩气藏水相圈闭损害实验研究及控制对策——以四川盆地东部龙马溪组露头页岩为例[J].油气地质与采收率,2014,21(6):87-91.Kang Yili,Chen Qiang,You Lijun,et al.Laboratory investigation of water phase trapping damage in shale gas reservoir-a case of Longmaxi shale in the eastern Sichuan Basin[J].Petroleum Geology and Recovery Efficiency,2014,21(6):87-91.
[4]李海,白云山,王保忠,等.湘鄂西地区下古生界页岩气保存条件[J].油气地质与采收率,2014,21(6):22-25.Li Hai,Bai Yunshan,Wang Baozhong,et al.Preservation conditions research on shale gas in the lower Paleozoic of western Hunan and Hubei area[J].Petroleum Geology and Recovery Efficiency,2014,21(6):22-25.
[5]徐祖新,郭少斌.页岩气成藏机理研究[J].内蒙古石油化工,2011,(6):122-124.Xu Zuxin,Guo Shaobin.Research on accumulation mechanism of shale gas[J].Inner Mongolia Petrochemical Industry,2011,(6):122-124.
[6]李治平,李智锋.页岩气纳米级孔隙渗流动态特征[J].天然气工业,2012,32(4):50-53.Li Zhiping,Li Zhifeng.Dynamic characteristics of shale gas flow in nanoscale pores[J].Nature Gas Industry,2012,32(4):50-53.
[7]Jack Dvorkin,Ayako Kameda,Amos Nur.Real time monitoring of permeability,elastic moduli and strength in sands and shales using digital rock physics[C].SPE 82246,2003.
[8]Fredrich J T,Menendez B,Wong T F.Imaging the pore structure of geomaterials[J].Science,1995,268:276-279.
[9]Tomutsa L,Silin D,Radmilovic V.Analysis of chalk petrophysical properties by means of submicron-scale pore imaging and modeling[J].SPE Reservoir Evaluation&Engineering,2007,10(3):285-293.
[10]Curtis M E,Ambrose R J,Sondergeld C H,et al.Structural characterization of gas shales on the micro-and nano-scales[C].SPE137693,2010.
[11]Pal-Eric Oren,Stig Bakke.Process based reconstruction of sandstone and prediction of transport properties[J].Transport in Porous Media,2002,46(2/3):311-343.
[12]黄保家,黄合庭,吴国瑄,等.北部湾盆地始新统湖相富有机质页岩特征及成因机制[J].石油学报,2012,33(1):25-31.Huang Baojia,Huang Heting,Wu Guoxuan,et al.Geochemical characteristics and formation mechanism of Eocene lacustrine organic-rich shales in the Beibuwan Basin[J].Acta Petrolei Sinica,2012,33(1):25-31.
[13]Joshi M.A class of stochastic models for porous media[D].Kansas:University of Kansas,1974.
[14]Quiblier J A.A new three-dimensional modeling technique for studying porous media[J].Journal of Colloid and Interface Science,1984,98(1):84-102.
[15]Ioannidis M,Kwiecien M,Chatzis I.Computer generation and application of 3-D model porous media from pore-level geostatistics to the estimation of formation factor[C].SPE 30201,1995:185-194.
[16]Hazlett R D.Statistical characterization and stochastic modeling of pore networks in relation to fluid flow[J].Mathematical Geology,1997,29(6):801-822.
[17]Yeong C L Y,Torquato S.Reconstructing random media[J].Physical Review E,1998,57(1):495-505.
[18]Yeong C L Y,Torquato S.Reconstructing random mediaⅡThreedimensional media from two-dimensional cuts[J].Physical Review E,1998,58(1):224-233.
[19]Hidajat I,Rastogi A,Singh M,et al.Transport properties of porous media from thin sections[C].SPE 69623,2002.
[20]Talukdar M S,Torsaeter O,Ioannidis M A.Stochastic reconstruction of particulate media from two-dimensional images[J].Journal of Colloid and Interface Science,2002,248(2):419-428.
[21]Talukdar M S,Torsaeter O,Howard J J.Stochastic reconstruction of chalk sample containing vuggy porosity using a conditional simulated annealing technique[J].Transport in Porous Media,2004,57(1):1-15.
[22]C?apek P,Hejtmánek V,Brabec L,et al.Stochastic reconstruction of particulate media using simulated annealing:improving pore connectivity[J].Transport in Porous Media,2009,76(2):179-198.
[23]Bakke S,Oren P E.3D pore-scale modelling of sandstones and flow simulations in the pore networks[J].SPE Journal,1997,2:136-149.
[24]Фren P E,Bakke S.Reconstruction of Berea and stone and porescale modelling of wettability effects[J].Journal of Petroleum Science and Engineering,2003,39(3):177-199.
[25]Strebelle S.Sequential simulation drawing structures from training images[D].Palo Alto:Stanford University,2000.
[26]Strebelle S.Conditional simulation of complex geological structures using multiple-point statistics[J].Mathematical Geology,2002,34(1):1-22.
[27]Strebelle S,Journel A G.Reservoir modeling using multiple-point statistics[C].SPE 71324,2001.
[28]Strebelle S,Payrazyan K,Caers J.Modeling of a deepwater turbidite reservoir conditional to seismic data using principal component analysis and multiple-point geostatistics[C].SPE 85962,2003.
[29]Okabe H,Blunt M J.Prediction of permeability for porous media reconstructed using multiple-point statistics[J].Physical Review E,2004,70(6):066135(1-10).
[30]Okabe H,Blunt M J.Pore space reconstruction using multiplepoint statistics[J].Journal of Petroleum Science and Engineering,2005,46(1):121-137.
[31]张挺,李道伦,卢德唐,等.基于多点地质统计法的多孔介质重构研究[J].中国科学G辑:物理学力学天文学,2009,39(9):1 348-1 360.Zhang Ting,Li Daolun,Lu Detang,et al.Research on reconstruction method of porous media using multiple-point geostatistics[J].Science in China:Series G Physics,Mechanics&Astronomy,2009,39(9):1 348-1 360.
[32]Wu Kejian,Naoise Nunan,John W Crawford,et al.An efficient markov chain model for the simulation of heterogeneous soil structure[J].Soil Science Society of American,2004,68(2):346-351.
[33]Wu Kejian,Van Dijke,Marinus I J,et al.3D stochastic modelling of heterogeneous porouos media-applications to reservoir rocks[J].Transport in Porous Media,2006,65(3):443-467.
[34]王晨晨,姚军,杨永飞,等.碳酸盐岩双孔隙数字岩心结构特征分析[J].中国石油大学学报:自然科学版,2013,37(2):71-74.Wang Chenchen,Yao Jun,Yang Yongfei,et al.Structure characteristics analysis of carbonate dual pore digital rock[J].Journal of China University of Petroleum:Edition of Natural Science,2013,37(2):71-74.
[35]张季如,祝杰,黄丽,等.土壤微观结构定量分析的IPP图像技术研究[J].武汉理工大学学报,2008,30(4):80-83.Zhang Jiru,Zhu Jie,Huang Li,et al.IPP image technique used for quantitative analysis of soil microstructure[J].Journal of Wuhan University of Technology,2008,30(4):80-83.
[36]Sen M K,Stoffa P L.Bayesian inference,Gibbs’sampler and uncertainty estimation in geophysical inversion[J].Geophysical Prospecting,1996,44(2):313-350.
[37]Xin Li.A very fast simulated re-annealing(VFSA)approach for land data assimilation[J].Computer&Geosciences,2004,30(3):239-248.