Adaptive interpretation of gas well deliverability tests with generating data of the IPR curve

International Conference on Information Technologies in Business and Industry 2016

计算机科学;经济学;工业技术

Sergeev, V.L.^1 ; Phuong, Nguyen T.H.^1 ; Krainov, A.I.^1

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

634050, Russia^1

关键词: Deliverability test;    Emissions into the atmosphere;    Estimated parameter;    Flow coefficients;    Formation pressure;    Function Optimization;    Priori information;    Reducing gas;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/803/1/012136/pdf
DOI  :  10.1088/1742-6596/803/1/012136

来源: IOP

【 摘 要 】

The paper considers topical issues of improving accuracy of estimated parameters given by data obtained from gas well deliverability tests, decreasing test time, and reducing gas emissions into the atmosphere. The aim of the research is to develop the method of adaptive interpretation of gas well deliverability tests with a resulting IPR curve and using a technique of generating data, which allows taking into account additional a priori information, improving accuracy of determining formation pressure and flow coefficients, 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 of two wells, run in the Urengoy gas and condensate field, Tyumen Oblast. The authors suggest the method of adaptive interpretation of gas well deliverability tests with the resulting IPR curve and the possibility of generating data of bottomhole pressure and a flow rate at different test stages. 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.