Application of deep learning on well-test interpretation for identifying pressure behavior and characterizing reservoirs

Author(s):  
Peng Dong ◽  
Zhiming Chen ◽  
Xinwei Liao ◽  
Wei Yu
DYNA ◽  
2019 ◽  
Vol 86 (210) ◽  
pp. 108-114
Author(s):  
Freddy Humberto Escobar ◽  
Angela María Palomino ◽  
Alfredo Ghisays Ruiz

Flow behind the casing has normally been identified and quantified using production logging tools. Very few applications of pressure transient analysis, which is much cheaper, have been devoted to determining compromised cemented zones. In this work, a methodology for a well test interpretation for determining conductivity behind the casing is developed. It provided good results with synthetic examples.


2013 ◽  
Vol 295-298 ◽  
pp. 3183-3191
Author(s):  
Xiang Yi Yi ◽  
Zhi Zhang ◽  
Cheng Yong Li ◽  
De Cai Li ◽  
Sheng Bo Wang

Stress-sensitive widely exists in fractured reservoir. In this paper, a mathematical model of flow in stress-sensitive reservoir with horizontal well is established based on experimental data and with process of linearization. By using of Lord Kelvin point-source solution, Bessel function integration and Poisson superimpose formula, the dimensionless pressure response function of horizontal well in infinite stress-sensitive reservoir is obtained. And then the derivative type curve is calculated. Based on the type curve, the characteristics and influencing factors of the fluid flow through porous medium of horizontal well in stress-sensitive gas reservoir are analyzed.


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