Petroleum Reservoir Evaluation and Development >
2020 , Vol. 10 >Issue 4: 107 - 112
DOI: https://doi.org/10.13809/j.cnki.cn32-1825/te.2020.04.017
Dew point pressure prediction model of condensate gas reservoir based on alternating conditional expectation transform
Received date: 2019-05-13
Online published: 2020-08-07
The efficient development of condensate gas reservoirs requires accurate fluid phase properties data, among which accurate prediction of dew point pressure is an important issue in the development of condensate gas reservoirs. In order to solve the problem of low accuracy of traditional prediction methods for dew point pressure of condensate gas reservoirs, based on optimization theory and applied statistical analysis, and by fitting measured data, a non-parametric regression model determined by alternating conditional expectation transformation(ACE) is proposed, and an explicit correlation of dew point pressure with statistical significance is obtained. Based on Pearson correlation analysis, the independent variables of the model are gas reservoir temperature, mole fraction of (C1, C2-C6, C7+), and molecular weight and relative density of C7+. The potential function relation between independent and dependent variables is analyzed by 27 sets of experimental data for published dew point pressure, and 9 groups of measured dew point pressure data of TLM oilfields are predicted. The results show that the model has high precision and good generalization ability. The average absolute relative deviation(AARD) of model regression is 2.16 %, and the predicted AARD is only 4.8 %. The maximum absolute relative deviation(ARD) is 9.21 % and the minimum is 0.34 %. This study provides a reference method for dew point pressure prediction of condensate gas reservoirs.
Bowen SUN , Ping GUO , Yiming WU , Zhouhua WANG , Daiyu ZHOU , Zhiliang LIU . Dew point pressure prediction model of condensate gas reservoir based on alternating conditional expectation transform[J]. Petroleum Reservoir Evaluation and Development, 2020 , 10(4) : 107 -112 . DOI: 10.13809/j.cnki.cn32-1825/te.2020.04.017
[1] | 崔书姮, 汤勇, 赵曜 , 等. 高温高压凝析气藏石蜡沉积条件预测研究[J]. 油气藏评价与开发, 2017,7(3):55-58. |
[1] | CUI S H, TANG Y, ZHAO Y , et al. Study on prediction of wax deposition conditions in high temperature and high pressure condensate gas reservoir[J]. Reservoir Evaluation and Development, 2017,7(3):55-58. |
[2] | 李建奇, 杨志伦, 张春雨 , 等. 反凝析作用对苏里格气田上古生界气藏开发的影响[J]. 天然气工业, 2015,35(4):45-51. |
[2] | LI J Q, YANG Z L, ZHANG C Y , et al. Impacts of retrograde condensation on the development of Upper Paleozoic gas reservoirs in the Sulige Gasfield, Ordos Basin[J]. Natural Gas Industry, 2015,35(4):45-51. |
[3] | 彭松 . 致密砂岩凝析气藏反凝析伤害机理及合理开发方式研究[D]. 成都:西南石油大学, 2015. |
[3] | PENG S . Research on mechanism of condensate damage and reasonable development method in tight sand gas-condensate reservoirs[D]. Chengdu: Southwest Petroleum University, 2015. |
[4] | 中国石油勘探开发研究院. 油气藏流体物性分析方法: GB/T 26981-2011[S]. 北京: 中国标准出版社, 2012. |
[4] | Research Institute of Petroleum Exploration and Development. Test method for reservoir fluid physical properties: GB/T 26981-2011[S]. Beijing: Standards Press of China, 2012. |
[5] | VALIOLLAHI S, KAVIANPOUR B, RAEISSI S , et al. A new Peng-Robinson modification to enhance dew point estimations of natural gases[J]. Journal of Natural Gas Science and Engineering, 2016,34:1137-1147. |
[6] | HAJI-SAVAMERI M, MENAD N A, NOROUZI-APOURVARI S , et al. Modeling dew point pressure of gas condensate reservoirs: Comparison of hybrid soft computing approaches, correlations, and thermodynamic models[J]. Journal of Petroleum Science and Engineering, 2020,184:1-18. |
[7] | ZHONG ZHI, LIU SIYAN, KAZEMI M , et al. Dew point pressure prediction based on mixed-kernels-function support vector machine in gas-condensate reservoir[J]. Fuel, 2018,232:600-609. |
[8] | 张可, 李实, 廉黎明 , 等. 交替条件期望变换确定油气最小混相压力新方法[J]. 油气藏评价与开发, 2012,2(1):23-28. |
[8] | ZHANG K, LI S, LIAN L M , et al. The new method to determine the minimum miscibility pressure of oil and gas by using alternating conditional expectation transform[J]. Reservoir Evaluation and Development, 2012,2(1):23-28. |
[9] | 江安, 雷少飞 . 基于交换条件数学期望的CO2最小混相压力预测模型[J]. 中国科技论文, 2016,11(17):2029-2034. |
[9] | JIANG A, LEI S F . The use of alternating conditional expectation to predict CO2 minimum miscibility pressure[J]. China Sciencepaper, 2016,11(17):2029-2034. |
[10] | FENG Q H, ZHANG J Y, ZHANG X M , et al. The use of alternating conditional expectation to predict methane sorption capacity on coal[J]. International Journal of Coal Geology, 2014,121:137-147. |
[11] | 陶德硕, 侯健, 魏翠华 . 基于交替条件期望的油藏井间连通性定量表征[J]. 科学技术与工程, 2014,14(31):55-60. |
[11] | TAO D S, HOU J, WEI C H . Quantitative characterization of dynamic connectivity of reservoir well based on alternating conditional expectation[J]. Science Technology and Engineering, 2014,14(31):55-60. |
[12] | FENG Q H, ZHANG J Y, ZHANG X M , et al. Proximate analysis based prediction of gross calorific value of coals: A comparison of support vector machine, alternating conditional expectation and artificial neural network[J]. Fuel Processing Technology, 2015,129:120-129. |
[13] | 蒙园, 张建华, 龙日尚 . 基于交替条件期望的短期负荷概率密度预测[J]. 华北电力大学学报(自然科学版), 2018,45(1):58-65. |
[13] | MENG Y, ZHANG J H, LONG R S . Short-term load probability density forecasting based on alternating conditional expectation. Journal of North China Electric Power University(Natural Science Edition), 2018,45(1):58-65. |
[14] | 孙志道, 胡永乐, 李云娟 , 等. 凝析气藏早期开发气藏工程研究[M]. 北京: 石油工业出版社, 2003. |
[14] | SUN Z D, HU Y L, LI Y J , et al. Gas reservoir engineering study of prophase condensate reservoir development[M]. Beijing: Petroleum Industry Press, 2003. |
[15] | 杨帆, 冯翔, 阮羚 , 等. 基于皮尔逊相关系数法的水树枝与超低频介损的相关性研究[J]. 高压电器, 2014,50(6):21-25. |
[15] | YANG F, FENG X, RUAN L , et al. Correlation study of water tree and VLF tanδ based on pearson correlation coefficient[J]. High Voltage Apparatus, 2014,50(6):21-25. |
[16] | 陈丽群, 刘敏, 张建业 , 等. 新露点压力预测模型的建立与对比分析[C]// 2017年全国天然气学术年会论文集.杭州:中国石油学会天然气专业委员会, 2017: 912-921. |
[16] | CHEN L Q, LIU M, ZHANG J Y , et al. Establishment and comparison of new dew point pressure prediction model[C]// 2017 National Natural Gas Academic Annual Conference. Gas Committee of CPS, Hangzhou, 2017: 912-921. |
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