Influence of Bound and Mobile Water on Gas Well Production in a Low-Permeability Sandstone Gas Reservoir

2017 ◽  
Vol 53 (2) ◽  
pp. 263-273 ◽  
Author(s):  
Li Qi ◽  
Ye Liyou ◽  
Gai Zhaohe ◽  
Li Yong
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.


2014 ◽  
Vol 962-965 ◽  
pp. 570-573
Author(s):  
Jian Yan ◽  
Xiao Bing Liang ◽  
Qian Wu ◽  
Qing Guo

Because of the gas slippage, the testing methods of stress sensitivity for gas reservoir should be different from that for oil reservoir. This text adopts the method that imposing back pressure on the outlet of testing core to weaken the gas slippage effect and tests the stress sensitivity of low permeability gas reservoirs, then analyzes the influence of permeability and water saturation on stress sensitivity. The results show that: low permeable and water-bearing gas reservoirs have strong stress sensitivity; the testing permeability has the power function relationship with net stress, compared to the exponential function, the fitting correlation coefficient is larger and more suited to the actual; the lower the permeability is and the higher water saturation is, the stronger the stress sensitivity is. The production of gas well is affected when considering the stress sensitivity, so the pressure dropping rate should be reasonable when low permeable gas reservoirs are developed. The results provide theoretical references for analyzing the well production and numerical simulation.


2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Xiaoliang Huang ◽  
Xiao Guo ◽  
Xiang Zhou ◽  
Xinqian Lu ◽  
Chen Shen ◽  
...  

The development process of a dipping gas reservoir with an aquifer considering stress sensitivity is complex. With gas development, formation pressure decreases, stress-sensitive effect decreases permeability and porosity, and formation water could flow into the development gas well and gather in the wellbore. The accumulation of water may lead to a lower gas rate. Simultaneously, the gravity action of fluid caused by formation dip angle affects gas well productivity. However, few studies have investigated a deliverability model for a water-producing gas well with a dipping gas reservoir considering stress sensitivity. For this reason, it is important to determine the relationships between gas well productivity and stress sensitivity, formation angle, and water production. In this research, a new mathematical model of deliverability was developed for a water-producing gas well with a dipping gas reservoir considering stress sensitivity. Additionally, a new equation was developed for gas well productivity. By analyzing a typical dipping gas reservoir with an aquifer, the level of influence on gas well productivity was determined for stress sensitivity, formation angle, and water–gas ratio (WGR). The work defined the relationships between gas well productivity and stress sensitivity, formation angle, and WGR. The results indicate that deliverability increases with an increase in formation angle, and growth rate hits its limit at an angle of 40 deg. Due to the influence of formation angle, fluid gravity leads to production pressure differences in gas wells. When bottom-hole flow pressure equaled formation pressure, gas well production was not 0 × 104 m3/d, the angle was large, and gas well production was greater. Deliverability and stress sensitivity hold a linear relationship: the stronger the stress sensitivity, the lower the deliverability of the gas well, with the stress sensitivity index from 0 to 0.06 MPa−1 and the deliverability decrease rate at 37.2%. Deliverability and WGR hold an exponential relationship: when WGR increased from 0.5 to 15.0 m3/104 m3, the deliverability decrease rate was 71.8%. The model and the equations can be used to predict gas deliverability in a dipping gas reservoir with an aquifer considering stress sensitivity. It can also be used to guide the development process for a dipping gas reservoir with an aquifer.


2012 ◽  
Vol 524-527 ◽  
pp. 1647-1650
Author(s):  
Deng Sheng Lei ◽  
Zhi Lin Qi

The rational proration is the prerequisite condition of realizing the high gas production and steady production of gas reservoir. Especially to the tight gas reservoir, due to the very low permeability, there are many low yield and low pressure gas wells. Because low yield and low pressure, the gas well is easily effected by the liquid loading and the change of working system, which cause the degree of reserve recovery decrease, more seriously make the gas stop producing directly. Based on the seepage rule in tight gas reservoir and analyzing the every factors influencing the production of low yield and pressure gas well, the low yield and pressure gas well have been classified to several types. And the gas well yields of different type have been optimized.


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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