scholarly journals A simulation experiment method for HTHP gas well productivity

Author(s):  
Keming Zhou ◽  
Nong Li ◽  
Tingzhi Liu ◽  
Jiahuan He ◽  
Huajie Yu ◽  
...  
2002 ◽  
Author(s):  
F.B. Thomas ◽  
E. Shtepani ◽  
D.B. Bennion ◽  
J. Rushing
Keyword(s):  
Gas Well ◽  

2019 ◽  
Vol 7 (2) ◽  
pp. T423-T435 ◽  
Author(s):  
Shuai Yin ◽  
Yi Wang ◽  
Jingzhou Zhao ◽  
Yan Wang ◽  
Weitao Wu ◽  
...  

Microfractures represent an important rupture type, but current studies on the construction of microscale rupture parameters and their impacts on oil and gas production capacity are relatively weak. Therefore, we constructed the strain energy density ([Formula: see text]) based on 3D finite-element method (FEM) for the tight sandstone reservoir of the Permian He8 segment in the western region of the Sulige gas field, Ordos Basin. It indicated that the [Formula: see text] values of the major production layers are mainly distributed between 0.12 and [Formula: see text]. High-[Formula: see text]-value regions ([Formula: see text]) are mainly distributed in local areas of the western, central, and eastern regions. The [Formula: see text] values are small in the northwestern part of the study area and are usually less than [Formula: see text]. There is a very good exponential correlation between the [Formula: see text] values and gas well productivity (the main controlling factor for the production capacity of the He8 tight sandstone is the gas content, and fracturing, as an engineering factor affecting capacity, has not been taken into account). The distribution of the strain energy densities also matches the low-amplitude tectonic zone well. We have developed the criterion for the discrimination of gas well productivity using the strain energy density. According to this criterion, the conformity rates of type I, type II, and type III wells are 92.3%, 73.0%, and 83.3%, respectively. The areas with [Formula: see text] values greater than [Formula: see text], especially for areas with [Formula: see text] values exceeding [Formula: see text], which should serve as the core exploration targets. The research results can effectively guide tight gas sandstone exploration in low-amplitude tectonic zones and reduce the risk of drilling.


2021 ◽  
Author(s):  
D.A. Samolovov ◽  
R.T. Apasov ◽  
I.V. Perevozkin ◽  
S.V. Kuznetsov

2014 ◽  
Vol 1044-1045 ◽  
pp. 688-691
Author(s):  
Ran Zhang ◽  
Jun Zhou ◽  
Cheng Yong Li

BP neural network has been successfully used in the gas well productivity prediction, but as a result of neural network is sensitive to the number of input parameters, we had to ignore some factors that is less important to the gas well productivity. In addition, the existing various productivity prediction method cannot consider the influence of some important qualitative factors. This article integrated the advantages of fuzzy comprehensive evaluation and BP neural network, fuzzy comprehensive evaluation method is used to construct the BP neural network's input matrix, and BP neural network learning function is used to solve the connection weights, so as to achieve the aim of predicting gas production. This method not only can consider as many factors influence on gas well production, ut also can consider qualitative factors, so the forecast results of the new model are more realistically close to the actual production situation of reservoirs.


2014 ◽  
Vol 962-965 ◽  
pp. 636-641
Author(s):  
Tian Qing ◽  
Peng Cheng Liu ◽  
Zong Yao Qi

During the volcanic gas reservoirs development, stress-sensitivity will result in permeability decline with formation pressure drop, lowering gas production and affecting the whole gas reservoirs development program. On the basis of the stress-sensitivity experiments on volcanic rocks, the characteristic of stress-sensitivity in volcanic reservoirs is analyzed. On this basis, this paper studies the prediction method of gas well productivity in volcanic gas reservoirs with stress-sensitivity, and establishes the mathematical model of constant pressure production in volcanic gas reservoirs. The results show that the permeability of volcanic rocks has an exponential relationship with effective stress. The stronger the stress-sensitivity is, the more the gas well productivity losses under the same conditions. And the reservoir stress-sensitivity will increase the degree of gas well unsteady production decline.


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