Adaptive interpretation of gas well deliverability tests

20th International Scientific Symposium of Students, Postgraduates and Young Scientists on "Problems of Geology and Subsurface Development"

Sergeev, V.L.^1 ; Phuong, Nguyen Thac Hoai^1 ; Strelnikova, A.B.^1

National Research Tomsk Polytechnic University, 30 Lenina Ave., Tomsk

634050, Russia^1

关键词: Deliverability test;    Field data;    Flow coefficients;    Formation pressure;    Function Optimization;    Gas filtration;    IPR curves;    Steady state filtration;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/43/1/012015/pdf
DOI  :  10.1088/1755-1315/43/1/012015

来源: IOP

【 摘 要 】

The paper considers topical issues of improving accuracy of data obtained from gas well deliverability tests, decreasing the number of test stages and well test time, and reducing gas emissions. The aim of the research is to develop the method of adaptive interpretation of gas well deliverability tests with resulting IPR curve conducted in gas wells with steady-state filtration, which allows obtaining and taking into account additional a priori data on the formation pressure and flow coefficients, setting the number of test stages adequate for efficient well testing and reducing test time. The present research is based on the previous theoretical and practical findings in the spheres of gas well deliverability tests, systems analysis, system identification, function optimization and linear algebra. To test the method, the authors used the field data of deliverability tests run in the Urengoy gas and condensate field, Tyumen Oblast. The authors suggest the method of adaptive interpretation of gas well deliverability tests with resulting IPR curve, which is based on the law for gas filtration with variables dependent on the number of test stage and account of additional a priori data. The suggested method allows defining the estimates of the formation pressure and flow coefficients, optimal in terms of preassigned measures of quality, and setting the adequate number of test stages in the course of well testing. The case study of IPR curve data processing has indicated that adaptive interpretation provides more accurate estimates on the formation pressure and flow coefficients, as well as reduces the number of test stages.