Prediction model of critical gas velocities in gas wells based on annular mist flow theory

doi:10.11949/j.issn.0438-1157.20180851

Abstract

Abstract:

Liquid loading, which can reduce the gas rate and even kill the gas well, is a common phenomenon associated with gas well production. Accurate prediction of liquid loading will help operators take measures in time to reduce the hazards, and the critical gas velocity is the key parameter to predict the liquid loading in gas wells. The related researches on the prediction of liquid loading in gas wells are reviewed, and the limitations of the minimum pressure drop model and the liquid droplet model are pointed out. Based on the experimental observations, it is considered that the liquid film model manifests better applicability. Considering the droplet entrainment in gas core and the uneven film distribution along the circumference of the tubing in deviated gas wells, a more practical annular mist flow model is proposed to judge the liquid loading of gas wells with different tubing diameters and inclination angles. The previous indoor experimental and field operating data are used to compare the new model with the six existing prediction models for liquid loading. Considering correctness and prediction error of the model prediction results, it is considered that the new annular mist flow model is better than other models, and can be used to predict liquid loading in gas well accurately and conveniently.

Key words: deviated wells, natural gas, liquid loading, critical gas velocity, prediction, annular mist flow, model

摘要：

井筒积液是伴随气井生产的常见现象，积液会导致气井产量降低，严重时甚至会使得气井停产。精确的积液预测有助于及时采取措施以减少积液带来的危害，而临界气体流速是气井积液预测的关键。回顾了气井积液预测的相关研究，指出了最小压降模型、液滴模型的局限性，基于现有实验观察认为液膜模型有较好的适用性。考虑到斜井中液膜周向不均匀分布及气相核心中液滴夹带，提出了更符合实际的环雾流模型用于不同管径、不同井斜角下的气井积液预测。基于以往室内实验数据和现场生产数据，将新模型与现有6种积液预测模型进行对比评价。综合考虑模型预测结果正确率及预测误差，认为新的环雾流模型较其他模型预测结果更优，可准确方便地对气井积液进行预测。

关键词: 斜井, 天然气, 积液, 临界气体流速, 预测, 环雾流, 模型

CLC Number:

TE 372

Weiwei SHEN, Daoming DENG, Qiaoping LIU, Jing GONG. Prediction model of critical gas velocities in gas wells based on annular mist flow theory[J]. CIESC Journal, 2019, 70(4): 1318-1330.

沈伟伟, 邓道明, 刘乔平, 宫敬. 基于环雾流理论的气井临界流速预测模型[J]. 化工学报, 2019, 70(4): 1318-1330.

Figures/Tables 12

Fig.1 Film distribution in vertical and inclined pipes

Fig.2 Cross section of inclined pipes for uniform and non-uniform circumferential distribution of liquid film

Fig.3 Interfacial shear stress vs non-dimensional film thickness for vertical pipes

Fig.4 Schematic diagram of annular flow model

Fig.5 Fig.5 Comparison between prediction results of each model with Guner and Alsaadi experimental data

Fig.6 Deviation between prediction results of each model with Guner and Alsaadi experimental data

Table 1 Average prediction errors and standard deviation of prediction errors for each model

Model	Average prediction error/%	Standard deviation of prediction error/%
new model	3.23	9.24
Barnea model	-20.12	23.64
Luo model	26.40	19.16
Turner model	-0.68	56.43
Belfroid model	-30.0	9.81
MulFlow(flow regime transition)	2.95	40.87
MulFlow(minimum shear stress)	4.45	33.37

Fig.7 Calculated critical gas velocities vs measured gas velocities for Turner loading wells

Fig.8 Calculated critical gas velocities vs measured gas velocities for Turner unloading wells

Table 2 Correct prediction count of gas well states for Turner data with each model

Model	Correct prediction count of gas well state(loading)	Correct prediction count of gas well state(unloading)	Total correct prediction count of gas well state
new model	32/37	47/53	79/90
Barnea model	37/37	41/53	78/90
Luo model	37/37	38/53	75/90
Turner model	28/37	51/53	79/90
Belfroid model	15/37	52/53	67/90
MulFlow(flow regime transition)	30/37	47/53	77/90
MulFlow(minimum shear stress)	37/37	28/53	65/90

Fig.9 Calculated critical gas velocities vs observed gas velocities for Veeken loading wells

Table 3 Prediction error and correct prediction count of gas well states for Veeken data with each model

Model	Average prediction error/%	Standard deviation of prediction error/%	Correct prediction count of gas well state
new model	8.70	26.63	40/67
Barnea model	-4.12	22.10	22/67
Luo model	51.29	37.11	62/67
Turner model	-42.57	14.16	1/67
Belfroid model	-38.69	15.54	1/67
MulFlow(flow regime transition)	-7.56	28.60	17/67
MulFlow(minimum shear stress)	12.21	39.52	38/67

References 39

1	Luo S . Inception of liquid loading in gas wells and possible solutions[D]. Tulsa: The University of Tulsa, 2013.
2	Chen D C , Yao Y , Fu G , et al . A new model for predicting liquid loading in deviated gas wells[J]. Journal of Natural Gas Science and Engineering, 2016, 34: 178-184.
3	Belt R J . On the liquid film in inclined annular flow[D]. Delft: Technische Universiteit Delft, 2007.
4	Yuan G , Pereyra E , Sarica C , et al . An experimental study on liquid loading of vertical and deviated gas wells[C]//SPE Production and Operations Symposium. Oklahoma City, Oklahoma, USA: Society of Petroleum Engineers, 2013: SPE-164516-MS.
5	Fan Y , Pereyra E , Torres C , et al . Experimental study on the onset of intermittent flow and pseudo-slug characteristics in upward inclined pipes[C]//17th International Conference on Multiphase Production Technology. Cannes, France: BHR Group, 2015: BHR-2015-B1.
6	Skopich A , Pereyra E , Sarica C . Pipe-diameter effect on liquid loading in vertical gas wells[J]. SPE Production & Operations, 2015, 30(2): 164-176.
7	Brito R , Pereyra E , Sarica C . Effect of well trajectory on liquid removal in horizontal gas wells[J]. Journal of Petroleum Science and Engineering, 2017, 156: 1-11.
8	Turner R G , Hubbard M G , Dukler A E . Analysis and prediction of minimum flow rate for the continuous removal of liquid from gas wells[J]. Journal of Petroleum Technology, 1969, 21(11): 1475-1482.
9	Coleman S B , Clay H B , Mccurdy D G , et al . A new look at predicting gas-well load-up[J]. Journal of Petroleum Technology, 1991, 43(3): 329-333.
10	Nosseir M A , Darwich T A , Sayyouh M H , et al . A new approach for accurate prediction of loading in gas wells under different flowing conditions[J]. SPE Production & Facilities, 2000, 15(4): 241-246.
11	Guo B Y , Ghalambor A , Xu C . A systematic approach to predicting liquid loading in gas wells[J]. SPE Production and Operations Symposium, 2006, 21(1): 81-88.
12	Fadairo A , Femi-Oyewole D , Falode O A . An improved tool for liquid loading in a gas well[C]//SPE Nigerian Annual International Conference and Exhibition. Lagos, Nigeria: Society of Petroleum Engineers, 2013: SPE-167552-MS.
13	Fadairo A , Olugbenga F , Sylvia N C . A new model for predicting liquid loading in a gas well[J]. Journal of Natural Gas Science and Engineering, 2015, 26: 1530-1541.
14	Zhou D S , Yuan H . A new model for predicting gas-well liquid loading[J]. SPE Production & Operations, 2010, 25(2): 172-181.
15	Li M , Li S L , Sun L T . New view on continuous-removal liquids from gas wells[J]. SPE Production & Facilities, 2002, 17(1): 42-46.
16	Awolusi O S . Resolving discrepancies in predicting critical rates in low pressure stripper gas wells[D]. Lubbock: Texas Tech University, 2005.
17	王毅忠, 刘庆文 . 计算气井最小携液临界流量的新方法[J]. 大庆石油地质与开发, 2007, 26(6): 82-85.
	Wang Y Z , Liu Q W . A new method for calculating the minimum critical flow rate of gas wells[J]. Petroleum Geology & Oilfield Development in Daqing, 2007, 26(6): 82-85.
18	Belfroid S , Schiferli W , Alberts G , et al . Prediction onset and dynamic behaviour of liquid loading gas wells[C]//SPE Annual Technical Conference and Exhibition. Denver, Colorado, USA: Society of Petroleum Engineers, 2008: SPE-115567-MS.
19	杨文明, 王明, 陈亮, 等 . 定向气井连续携液临界产量预测模型[J]. 天然气工业, 2009, 29(5): 82-84.
	Yang W M , Wang M , Chen L , et al . A prediction model on calculation of continuous liquid carrying critical production of directional gas wells[J]. Natural Gas Industry, 2009, 29(5): 82-84.
20	于继飞, 管虹翔, 顾纯巍, 等 . 海上定向气井临界流量预测方法[J]. 特种油气藏, 2011, 18(6): 117-119.
	Yu J F , Guan H X , Gu C W , et al . Prediction of critical flow rate for offshore directional gas wells[J]. Special Oil & Gas Reservoirs, 2011, 18(6): 117-119.
21	李丽, 张磊, 杨波, 等 . 天然气斜井携液临界流量预测方法[J]. 石油与天然气地质, 2012, 33(4): 650-654.
	Li L , Zhang L , Yang B , et al . Prediction method of critical liquid carrying flow rate for directional gas wells[J]. Oil & Gas Geology, 2012, 33(4): 650-654.
22	王琦 . 水平井井筒气液两相流动模拟实验研究[D]. 成都: 西南石油大学, 2014.
	Wang Q . Experimental study on gas-liquid flowing in the wellbore of horizontal well[D]. Chengdu: Southwest Petroleum University, 2014.
23	Keuning A . The onset of liquid loading in inclined tubes[D]. Eindhoven: Eindhoven University of Technology, 1998.
24	van t Westende J M C . Droplets in annular-dispersed gas-liquid pipe-flows[D]. Delft: Technische Universiteit Delft, 2008.
25	Veeken K , Hu B , Schiferli W . Gas-well liquid loading field data analysis and multiphase flow modeling[J]. SPE Production & Operations, 2010, 25(3): 275-284.
26	Zabaras G , Dukler A E , Moalem-Maron D . Vertical upward cocurrent gas‐liquid annular flow[J]. AIChE Journal, 1986, 32(5): 829-843.
27	Zhang H Q , Wang Q , Sarica C , et al . Unified model for gas-liquid pipe flow via slug dynamics(1): Model development[J]. Journal of Energy Resources Technology, 2003, 125(4): 266-273.
28	Zhang H Q , Wang Q , Sarica C , et al . Unified model for gas-liquid pipe flow via slug dynamics(2): Model validation[J]. Journal of Energy Resources Technology, 2003, 125(4): 811-820.
29	Barnea D , Shoham O , Taitel Y , et al . Gas-liquid flow in inclined tubes: flow pattern transitions for upward flow[J]. Chemical Engineering Science, 1985, 40(1): 131-136.
30	Barnea D . A unified model for predicting flow-pattern transitions for the whole range of pipe inclinations[J]. International Journal of Multiphase Flow, 1987, 13(1): 1-12.
31	Fore L B , Beus S G , Bauer R C . Interfacial friction in gas-liquid annular flow: analogies to full and transition roughness[J]. International Journal of Multiphase Flow, 2000, 26(11): 1755-1769.
32	Li J , Almudairis F , Zhang H . Prediction of critical gas velocity of liquid unloading for entire well deviation[C]//International Petroleum Technology Conference. Kuala Lumpur, Malaysia, 2014: IPTC-17846-MS.
33	Gurner M , Pereyra E , Sarica C , et al . An experimental study of low liquid loading in inclined pipes from 90° to 45°[C]//SPE Production and Operations Symposium. Oklahoma City, Oklahoma, USA: Society of Petroleum Engineers, 2015: SPE-173631-MS.
34	Alsaadi Y , Pereyra E , Torres C , et al . Liquid loading of highly deviated gas wells from 60° to 88°[C]//SPE Annual Technical Conference and Exhibition. Houston, Texas, USA: Society of Petroleum Engineers, 2015: SPE-174852-MS.
35	Andritsos N , Hanratty T J . Influence of interfacial waves in stratified gas-liquid flows[J]. AIChE Journal, 1987, 33(3): 444-454.
36	Shekhar S , Kelkar M , Hearn W J , et al . Improved prediction of liquid loading in gas wells[J]. SPE Production & Operations, 2017, 32(4): 539-550.
37	Paz R J , Shoham O . Film-thickness distribution for annular flow in directional wells: horizontal to vertical[J]. SPE Production & Operations, 1999, 4(2): 83-91.
38	Barnea D . Transition from annular flow and from dispersed bubble flow—unified models for the whole range of pipe inclinations[J]. International Journal of Multiphase Flow, 1986, 12(5): 733-744.
39	Wallis G B . One-dimensional Two-phase Flow[M]. New York: McGraw-Hill, 1969: 315-367.

[1]	Jiahao SONG, Wen WANG. Study on coupling operation characteristics of Stirling engine and high temperature heat pipe [J]. CIESC Journal, 2023, 74(S1): 287-294.
[2]	Mengya LIAN, Yingying TAN, Lin WANG, Feng CHEN, Yifei CAO. Heating performance of air preheated integrated ground water heat pump air-conditioning system [J]. CIESC Journal, 2023, 74(S1): 311-319.
[3]	Zhenghao JIN, Lijie FENG, Shuhong LI. Energy and exergy analysis of a solution cross-type absorption-resorption heat pump using NH₃/H₂O as working fluid [J]. CIESC Journal, 2023, 74(S1): 53-63.
[4]	Hao WANG, Zhenlei WANG. Model simplification strategy of cracking furnace coking based on adaptive spectroscopy method [J]. CIESC Journal, 2023, 74(9): 3855-3864.
[5]	Ke LI, Jian WEN, Biping XIN. Study on influence mechanism of vacuum multi-layer insulation coupled with vapor-cooled shield on self-pressurization process of liquid hydrogen storage tank [J]. CIESC Journal, 2023, 74(9): 3786-3796.
[6]	Xudong YU, Qi LI, Niancu CHEN, Li DU, Siying REN, Ying ZENG. Phase equilibria and calculation of aqueous ternary system KCl + CaCl₂ + H₂O at 298.2, 323.2, and 348.2 K [J]. CIESC Journal, 2023, 74(8): 3256-3265.
[7]	Chengying ZHU, Zhenlei WANG. Operation optimization of ethylene cracking furnace based on improved deep reinforcement learning algorithm [J]. CIESC Journal, 2023, 74(8): 3429-3437.
[8]	Linqi YAN, Zhenlei WANG. Multi-step predictive soft sensor modeling based on STA-BiLSTM-LightGBM combined model [J]. CIESC Journal, 2023, 74(8): 3407-3418.
[9]	Gang YIN, Yihui LI, Fei HE, Wenqi CAO, Min WANG, Feiya YAN, Yu XIANG, Jian LU, Bin LUO, Runting LU. Early warning method of aluminum reduction cell leakage accident based on KPCA and SVM [J]. CIESC Journal, 2023, 74(8): 3419-3428.
[10]	Guoze CHEN, Dong WEI, Qian GUO, Zhiping XIANG. Optimal power point optimization method for aluminum-air batteries under load tracking condition [J]. CIESC Journal, 2023, 74(8): 3533-3542.
[11]	Jintong LI, Shun QIU, Wenshou SUN. Oxalic acid and UV enhanced arsenic leaching from coal in flue gas desulfurization by coal slurry [J]. CIESC Journal, 2023, 74(8): 3522-3532.
[12]	Ruihang ZHANG, Pan CAO, Feng YANG, Kun LI, Peng XIAO, Chun DENG, Bei LIU, Changyu SUN, Guangjin CHEN. Analysis of key parameters affecting product purity of natural gas ethane recovery process via ZIF-8 nanofluid [J]. CIESC Journal, 2023, 74(8): 3386-3393.
[13]	Chunyu LIU, Huanyu ZHOU, Yue MA, Changtao YUE. Drying characteristics and mathematical model of CaO-conditioned oil sludge [J]. CIESC Journal, 2023, 74(7): 3018-3027.
[14]	Yuying GUO, Jiaqiang JING, Wanni HUANG, Ping ZHANG, Jie SUN, Yu ZHU, Junxuan FENG, Hongjiang LU. Water-lubricated drag reduction and pressure drop model modification for heavy oil pipeline [J]. CIESC Journal, 2023, 74(7): 2898-2907.
[15]	Weiming SHAO, Wenxue HAN, Wei SONG, Yong YANG, Can CHEN, Dongya ZHAO. Dynamic soft sensor modeling method based on distributed Bayesian hidden Markov regression [J]. CIESC Journal, 2023, 74(6): 2495-2502.