Electrification of Gas Well Production System Reduces Operational Costs in Saudi Aramco Gas Field

2000 ◽  
Author(s):  
Mark Rivenbark ◽  
Sami Khater ◽  
Steven Barnes ◽  
Roy MacKenzie
2013 ◽  
Vol 295-298 ◽  
pp. 3298-3301
Author(s):  
Zuo Chen Li

This article studies Wangjiatun field gas well production situation, analysis to find out the law of diminishing gas, determine the decline type. According to the gas well decline rule, guide to establish the corresponding production system, but also the production of gas well according to the actual situation, to Wangjiatun gas well production performance is forecasted, make Wangjiatun gas well can highly effective and reasonable, sustainable development.


2013 ◽  
Author(s):  
Tejo Sukotrihadiyono ◽  
Aldani Malau ◽  
Ganes Sugi Pulunggono ◽  
Aliefiyan Nursanda Muklas

2013 ◽  
Vol 868 ◽  
pp. 692-695
Author(s):  
Hong Lian Li ◽  
Rui Dai ◽  
Xiao Lu Wang ◽  
Ji Feng Qu

Sebei NO.2 gas field I-1 layer group is shallow-buried with comparatively lower formation energy. In the process of developing, the formation pressure drops and the total energy consumption of the gas-liquid two phase pipe flowing increases gradually, which leads wellbore to produce accumulated fluid that greatly reduces gas well productivity. This paper is based on the mastery of gas field reservoir characteristics and production dynamics, analyzing the changes of gas well production performance before and after gas wells with accumulated fluid. A wellbore liquid loading identification model of Sebei NO.2 gas field is established in terms of the liquid removing capacity calculations, wellhead characteristic observation method, the pressure gradient method. In the aspect of liquid loading volume, the study based on the theory of wellbore gas-liquid two phase flow, using four classical pressure distribution models to construct a combined model that is more suitable for single wells, analyzed the features of fluid gas well distribution with structural characteristics and other aspects. Practical application shows that the analysis results are reliable and highly practical, and deepening the understanding of the phenomenon of gas liquid loading.


2012 ◽  
Vol 204-208 ◽  
pp. 297-302
Author(s):  
Kui Zhang ◽  
Hai Tao Li ◽  
Yang Fan Zhou ◽  
Ai Hua Li

Low permeability, low abundance, water-bearing gas reservoirs are widely distributed in China, and their reserves constitute 85% of all kinds of reservoirs in current. It has important realistic meanings to develop them. Determining of reasonable gas well production is the prerequisite to achieving long-term high productivity and stable production. This paper takes Shanggu gas field at Sulige Gas Field for example, respectively from the dynamic data analogy methods, the pressure drop rate statistical methods, gas curve methods, production system nodal analysis methods, and studied the reasonable capacity of the low permeability gas reservoir. Through comprehensive analysis,the comprehensive technical indexes about single well reasonable production was determined.


2015 ◽  
Vol 125 ◽  
pp. 234-246 ◽  
Author(s):  
Fanliao Wang ◽  
Xiangfang Li ◽  
Gary Couples ◽  
Juntai Shi ◽  
Jinfen Zhang ◽  
...  

2020 ◽  
Vol 39 (6) ◽  
pp. 8823-8830
Author(s):  
Jiafeng Li ◽  
Hui Hu ◽  
Xiang Li ◽  
Qian Jin ◽  
Tianhao Huang

Under the influence of COVID-19, the economic benefits of shale gas development are greatly affected. With the large-scale development and utilization of shale gas in China, it is increasingly important to assess the economic impact of shale gas development. Therefore, this paper proposes a method for predicting the production of shale gas reservoirs, and uses back propagation (BP) neural network to nonlinearly fit reservoir reconstruction data to obtain shale gas well production forecasting models. Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods


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