Gas Well Production Analysis With Non-Darcy Flow and Real-Gas PVT Behavior

2006 ◽  
Author(s):  
F. Zeng ◽  
G. Zhao
Keyword(s):  
Darcy Flow ◽  
Gas Well ◽  
Real Gas ◽  
Well Production ◽  
Production Analysis ◽  
Pvt Behavior

Gas Well Decline Analysis Incorporating Real-Gas Behavior and Non-Darcy Flow

1986 ◽  
Author(s):  
S.H. Schmidt ◽  
B.H. Caudle ◽  
M.A. Miller
Keyword(s):  
Darcy Flow ◽  
Gas Well ◽  
Real Gas

scholarly journals A Novel Mathematical Model Considering Real Gas PVT Behavior to Estimate Inflow Performance Relationship of Gas Well Production

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3594
Author(s):  
Shuang Zhang ◽  
Huiqing Liu ◽  
Yanwei Wang ◽  
Ke Sun ◽  
Yunfei Guo
Keyword(s):  
Mathematical Model ◽  
High Efficiency ◽  
Stress Sensitivity ◽  
Gas Reservoir ◽  
Gas Field ◽  
Gas Well ◽  
Real Gas ◽  
Pvt Behavior ◽  
Inflow Performance ◽  
Relationship Of

Inflow performance relationship (IPR) is one of the most important methods for the analysis of the dynamic characteristics of gas reservoir production. The objective of this study was to develop a model to improve the accuracy of the IPR for evaluating and predicting the production of gas reservoirs. In this paper, a novel mathematical model, taking into account the real gas PVT behavior, is developed to accurately estimate the inflow performance relationship. By introducing a pseudo-pressure function and a real gas properties database, this model eliminates the error caused by the linearization method and improves the calculation accuracy. The results show that more than 90% of the energy in the flow field is consumed by inertial forces, which leads to significant high-velocity non-Darcy effects in the gas reservoir. The reservoir permeability, original reservoir pressure, stress sensitivity coefficient, and skin factor have a great impact on the inflow performance relationship of gas reservoir production. This model predicts gas IPR curves with excellent accuracy and high efficiency. The high-precision gas well inflow performance relationship lays a solid foundation for dynamic production analysis, rational proration, and intelligent development of the gas field.

Economic benefit of shale gas exploitation based on back propagation neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8823-8830
Author(s):  
Jiafeng Li ◽  
Hui Hu ◽  
Xiang Li ◽  
Qian Jin ◽  
Tianhao Huang
Keyword(s):  
Neural Network ◽  
Shale Gas ◽  
Bp Neural Network ◽  
Large Scale ◽  
Linear Prediction ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Economic Benefits ◽  
Gas Well ◽  
Well Production

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

Analysis and Comparison of Seal Ability of Premium Tubing Connections under Axial Alternating Load

2013 ◽  
Vol 423-426 ◽  
pp. 2035-2039
Author(s):  
Long Cang Huang ◽  
Yin Ping Cao ◽  
Yang Yu ◽  
Yi Hua Dou
Keyword(s):  
Contact Pressure ◽  
Oil And Gas ◽  
Element Analysis ◽  
Gas Well ◽  
Cycle Number ◽  
Compression Load ◽  
Well Production ◽  
Maximum Contact ◽  
Contact Pressures ◽  
Better Than

In the process of oil and gas well production, tubing connection stand the axial alternating load during open well, shut well and fluid flow. In order to know premium connection seal ability under the loading, two types of P110 88.9mmx6.45mm premium tubing connections which called A connection and B connection are performed with finite element analysis, in which contact pressures and their the regularities distribution on sealing surface are analyzed. The results show that with the increasing of cycle number, the maximum contact pressures on sealing surface of both A connection and B connection are decreased. The decreasing of the maximum contact pressures on B connection is greater than those on A connection. With the increasing of cycle number of axial alternating compression load, the maximum contact pressure on sealing surface of A connection is decreased, and the maximum contact pressure on sealing surface of B connection remains constant. Compared the result, it shows that the seal ability of A connection is better than B connection under axial alternating tension load, while the seal ability of B connection is better than type A connection under axial alternating compression load.

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