Well Test Analysis of Infrequent Behavior of Fractured Wells in Oil and Gas Reservoirs

2012 ◽  
Author(s):  
Aram Amin
Keyword(s):  
Oil And Gas ◽  
Well Test ◽  
Gas Reservoirs ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Oil And Gas Reservoirs

Study of Homogeneous Reservoir Pressure Inversion Model Based on Permeability Mechanics and Interpretation Software Design

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhongshuai Chen ◽  
Hongjian Ni ◽  
Zhiqi Sun ◽  
Shiping Zhang ◽  
Qisong Wang
Keyword(s):  
Oil And Gas ◽  
Inversion Method ◽  
Reservoir Pressure ◽  
Well Test ◽  
Inversion Algorithm ◽  
Characteristic Parameters ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Inversion Model ◽  
Wellbore Pressure

Well test analysis is required during the extraction of oil and gas wells. The information on formation parameters can be inverted by measuring the change in wellbore pressure at production start-up or after well shutdown. In order to calculate the characteristic parameters of the well, this paper creates a well test interpretation model for homogeneous reservoirs based on the theory of seepage mechanics, uses the Stehfest–Laplace inversion numerical inversion algorithm, and builds the Gringarten–Bourdet logarithmic curves model. The model can be used to evaluate the homogeneous reservoir. We use this model to design the pressure inversion interpretation software to implement a pressure inversion method based on permeability mechanics theory by using computer. The software can obtain the reservoir characteristic parameters such as permeability ( K ), skin coefficient ( S ), and wellbore storage coefficient ( C ). The homogeneous formation Gringarten–Bourdet curves data are available at https://github.com/JXLiaoHIT/Study-of-homogeneous-reservoir-pressure-inversion-model.

PRESSURE RATE DECONVOLUTION METHODS FOR WELL TEST ANALYSIS

2009 ◽  
Vol 23 (08) ◽  
pp. 1027-1051 ◽  
Author(s):  
M. ANDRECUT
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Well Test ◽  
Krylov Methods ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Gas Industry ◽  
Deconvolution Problem ◽  
Important Addition ◽  
Made In

The deconvolution method has received much attention recently, and is becoming one of the major tools for well test and production data analysis in oil and gas industry. Here, we present a new deconvolution approach, which we believe is relevant and can be an important addition to the existing efforts made in this field. We show that the solution of the deconvolution problem can be successfully represented as a linear combination of non-orthogonal exponential functions. Also, we present three deconvolution algorithms. The first two algorithms are based on regularization concepts borrowed from the well-known Tikhonov and Krylov methods, while the third algorithm is based on the stochastic Monte Carlo method.

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