Data Analysis of the Real-Time Pressure and Temperature along the Wellbore in Intelligent Well Lei 632 with Commingling Production in LH Oilfield
Journal of Petroleum Science and Engineering(2016)
摘要
Data on reservoir parameters, production rate, and water cut are considered key parameters in the control and matching of production in each layer of intelligent well wellbores. Owing to the complicated conditions in the downhole, no permanent downhole flowmeter is installed in the current simple intelligent well system of onshore oilfields in China. Furthermore, necessary real-time data on reservoir parameters, production rate, and water cut in each producing layer cannot be obtained. On the basis of mass conservation equation, momentum conservation equation, and theories of heat transfer, thermodynamics, and fluid mechanics in porous medium, this study establishes the energy conservation equation of fluids in the tubing and annulus. By using the single-point real-time data of the pressure and temperature in the tubing and annulus, the temperature gradient in each producing layer can be deduced. Moreover, the temperature profile, data on reservoir parameters, production rate, and water cut in each producing layer can be calculated. This approach is used to solve the problem of flow measurement in each producing layer of intelligent well systems without permanent downhole flowmeters in onshore Chinese oilfields. According to the production data of intelligent well Lei 632, the temperature distribution along the wellbore is analyzed, the water yield formation is diagnosed, and the reservoir parameters, production rate, and water cut in each producing layer are calculated. The analytic solution of the method agrees well with that of the conventional production logging, thus indicating the feasibility of the method in realizing the dynamic monitoring of intelligent wells and in solving the actual problem in real time. The proposed method fills in the gaps in theories on intelligent well technology in China.
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关键词
Intelligent well,Commingling production,Steady state flow and heat modeling,Real-time well monitoring
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