全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

泥质砂岩液相渗透率计算新方法

DOI: 10.6038/cjg20151033, PP. 3837-3844

Keywords: 液相渗透率,阳离子交换容量,溶液矿化度,泥质砂岩

Full-Text   Cite this paper   Add to My Lib

Abstract:

液相渗透率描述了岩石的渗流特性,是评价储层与预测油气产能的重要参数.液相渗透率是指盐水溶液在岩石孔隙中流动且与岩石孔隙表面黏土矿物发生物理化学作用时所测得的渗透率;液相渗透率的实验测量条件更加接近实际地层泥质砂岩的条件,使得液相渗透率更能反映地层条件下泥质砂岩的渗流特性;然而,现有的液相渗透率评价模型较少,且模型未能揭示液相渗透率与溶液矿化度之间的关系.基于此,开展了液相渗透模型推导与计算方法研究;文中首先将岩石等效为毛管束模型,推导建立了液相渗透率与比表面、喉道曲折度、总孔隙度、黏土束缚水孔隙度等参数之间的关系;其次,根据岩石物理体积模型,推导建立了黏土束缚水孔隙度与阳离子交换容量、溶液矿化度等参数的关系;最终,将黏土束缚水孔隙度引入液相渗透率计算公式,建立了基于总孔隙度、阳离子交换容量、溶液矿化度、比表面、喉道曲折度等参数的液相渗透率理论计算模型.液相渗透率计算模型与两组实验数据均表明,液相渗透率随阳离子交换容量的增大而降低,随溶液矿化度的增大而增大.然而,液相渗透率理论计算模型的实际应用中喉道曲折度、比表面等参数求取困难,直接利用理论模型计算液相渗透率受到限制.在分析液相渗透率与孔隙渗透率模型的基础上,建立了液相渗透率与空气渗透率之间的转换模型,形成了利用转化模型计算液相渗透率的新方法.为进一步验证液相渗透率与空气渗透率转化模型的准确性,基于两组实验数据,利用转换模型计算了液相渗透率;液相渗透率计算结果与岩心测量液相渗透率实验结果对比显示,液相渗透率计算结果与实际岩心测量结果吻合较好,文中建立的液相渗透率与空气渗透率转化模型合理可靠.

References

[1]  Yan G L, Sun J M, Liu X F, et al. 2014. Characterization of microscopic pore structure of reservoir rock and its effect on permeability. Well Logging Technology (in Chinese), 38(1): 28-32.
[2]  Amaefule J O, Altunbay M, Tiab D, et al. 1993. Enhanced reservoir description: using core and log data to identify hydraulic (flow) units and predict permeability in uncored intervals/wells. SPE 26436.
[3]  Carmen P C. 1937. Fluid flow through granular beds. Transactions of the Institution of Chemical Engineers, 15: 150-166.
[4]  Chen S Y, Doolen G D. 1998. Lattice Boltzmann method for fluid flows. Annual Review of Fluid Mechanics, 30(1): 329-364.
[5]  Chen G, Pan B Z, Wang C P, et al. 2012. Permeability evaluation method for complex pore structure reservoir. Well Logging Technology (in Chinese), 36(4): 382-386.
[6]  Cheng Z G, Luo S C, Du Z W, et al. 2014. The method to calculate tight sandstone reservoir permeability using pore throat characteristic parameters. Well Logging Technology (in Chinese), 38(2): 185-189.
[7]  Clavier C, Coates G, Dumanoir J. 1984. Theoretical and experimental bases for the dual-water model for interpretation of shaly sands. Society of Petroleum Engineers Journal, 24(2): 153-158.
[8]  Coates G, Denoo S. 1981. The producibility answer product. The Technical Review, 29(2): 54-63.
[9]  Coates R G, Miller M, Gillen M, et al. 1991. An investigation of a new magnetic resonance imaging log.//SPWLA 32nd Annual Logging Symposium. Midland, Texas.
[10]  De Lima O A L. 1995. Water saturation and permeability from resistivity, dielectric, and porosity logs. Geophysics, 60(6): 1756-1764.
[11]  Ge X M, Fan Y Y, Deng S G. 2011. Research on T2 cutoff-value determination method for shaly sand based on experiments. Well Logging Technology (in Chinese), 35(4): 308-313.
[12]  Goode P, Sen P N. 1988. Charge density and permeability in clay-bearing sandstones. Geophysics, 53(12): 1610-1612.
[13]  Grunau D, Chen S Y, Eggert K. 1993. A lattice Boltzmann model for multiphase fluid flows. Phys. Fluids A, 5(10): 2557-2562.
[14]  He X Y, Chen S Y, Zhang R Y. 1999. A lattice Boltzmann scheme for incompressible multiphase flow and its application in simulation of Rayleigh-Taylor instability. Journal of Computational Physics, 152(2): 642-663.
[15]  Herron M M. 1987. Estimating the intrinsic permeability of clastic sediments from geochemical data.//SPWLA 28th Annual Logging Symposium. London, England.
[16]  Hill H J, Millburn J D. 1956. Effect of clay and water salinity on electrochemical behavior of reservoir rocks. AIME Petroleum Transaction, 207(3): 65-72.
[17]  Hill H J, Shirley O J, Klein G E. 1979. Bound water in shaly sands-its relation to Qv and other formation properties. The Log Analyst, 20(3): 13-19.
[18]  Jennings J W Jr, Lucia F J. 2001. Predicting permeability from well logs in carbonates with a link to geology for interwell permeability mapping. Society of Petroleum Engineers Journal, 6(4): 215-225.
[19]  Jiao C H, Xu C H. 2006. An approach to permeability prediction based on flow zone index. Well Logging Technology (in Chinese), 30(4): 317-319.
[20]  Jing C, Song Z Q, Pu C S, et al. 2013. Refined permeability of tight gas reservoir based on petrophysical facies classification — taking the study of tight gas reservoir permeability in the eastern of Sulige for an example. Progress in Geophysics (in Chinese), 28(6): 3222-3230, doi: 10.6038/pg20130649.
[21]  Juhasz I. 1979. The central role of Qv and formation-water salinity in the evaluation of shaly formations. The Log Analyst, 20(4): 3-13.
[22]  Juhasz I. 1986. Conversion of routine air permeability data into stressed brine permeability data.//10th European Formation Evaluation Symposium.
[23]  Kenyon W E, Day P I, Straley C, et al. 1988. A three-part study of NMR longitudinal relaxation properties of water-saturated sandstones. SPE Formation Evaluation, 3(3): 622-636.
[24]  Kenyon W E. 1997. Petrophysical principles of applications of NMR logging. The Log Analyst, 38(2): 21-43.
[25]  Kozeny J. 1927. Vber kapillare leitung des wassers im boden. Sitzungsberichte der Wiener Akademie der Wissenschaften, 136(2a): 271-306.
[26]  Krumbein W C, Monk G D. 1943. Permeability as a function of the size parameters of unconsolidated sand. Transactions of the AIME, 151(1): 153-163.
[27]  Kuang L C, Mao Z Q, Sun Z C. 2002. On the controlling factors of irreducible water saturation in the low resistivity pay zone of cretaceous formation in Lu 9 area, Junggar basin. Well Logging Technology (in Chinese), 26(1): 14-17.
[28]  Lonnes S, Angel G, Holland R. 2003. NMR petrophysical predictions on cores.//SPWLA 44th Annual Logging Symposium.
[29]  Macary S M. 1999. Conversion of air permeability to liquid permeabilities extracts huge source of information for reservoir studies.//Middle East Oil Show and Conference. February, Bahrain: SPE.
[30]  Martin P, Dacy J. 2004. Effective Qv by NMR tests.//SPWLA 45th Annual Logging Symposium. Noordwijk, Netherlands.
[31]  Nooruddin H A, Hossain M E. 2011. Modified Kozeny-Carmen correlation for enhanced hydraulic flow unit characterization. Journal of Petroleum Science and Engineering, 80(1): 107-115.
[32]  Pittman E D. 1992. Relationship of porosity and permeability to various parameters derived from mercury injection capillary pressure curves for sandstones. AAPG Bulletin, 76(2): 191-198.
[33]  Schofield R K. 1947. Calculation of surface areas from measurements of negative adsorption. Nature, 160(4064): 408-410.
[34]  Schowalter T T. 1979. Mechanics of secondary hydrocarbon migration and entrapment. AAPG Bulletin, 63(5): 723-760.
[35]  Sen P N, Straley C, Kenyon W E, et al. 1990. Surface-to-volume ratio, charge density, nuclear magnetic relaxation, and permeability in clay-bearing sandstones. Geophysics, 55(1): 61-69.
[36]  Shan X W, Chen H D. 1993. Lattice Boltzmann model for simulating flows with multiple phases and components. Physical Review E, 47(3): 1815-1819.
[37]  Song N, Liu Z, Zhang J F, et al. 2013. Permeability prediction of heterogeneous sand reservoir based on flow units classification. Science & Technology Review (in Chinese), 31(2): 68-71.
[38]  Sun J M, Yan G L. 2012. Review on absolute permeability model. Well Logging Technology (in Chinese), 36(4): 329-335.
[39]  Swanson B F. 1981. A simple correlation between permeabilities and mercury capillary pressures. Journal of Petroleum Technology, 33(12): 2498-2504.
[40]  Thompson A H, Raschke R A. 1987. Estimation of absolute permeability from capillary pressure measurements.//SPE Annual Technical Conference and Exhibition. Dallas, Texas: SPE.
[41]  Timur A. 1968. An investigation of permeability, porosity, and residual water saturation relationship for sandstone reservoirs. The Log Analyst, 9(4): 8-17.
[42]  Waxman M H, Smits L J M. 1968. Electrical conductivities in oil-bearing shaly sands. Society of Petroleum Engineers Journal, 8(3): 107-122.
[43]  Xie W B, Zhou F M, Si Z W, et al. 2014. New calculation model of permeability in sandstone formation by the mathematical derivation. Well Logging Technology (in Chinese), 38(5): 553-557.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133