Abstract
The work aims to propose a set of water source selection methods for water injection well aiming at inhibiting scaling and corrosion of pipe string, in order to reduce the occurrence of scaling and corrosion and solve the problems in the commonly used evaluation methods for water quality, such as difficulty in measurement and great influence of human experience. Based on analysis results of seven water samples in Bohai oilfield, the sensitivity of each ion component to scaling corrosion phenomenon was studied by grey correlation degree with the scaling and corrosion trend of water quality as reference sequence and the ion concentration of water quality components (HCO3–, Cl–, Ca2+, Na+, K+, Mg2+, SO42–) as comparison sequence. Based of this, the method of water source selection for water injection wells was studied by means of fuzzy matter element method. The optimal influence weights (0.1964, 0.1785, 0.1753, 0.1748, 0.1706, 0.1044) of water quality components (HCO3–, Cl–, Ca2+, Na+, K+, Mg2+, SO42–) on scaling of water injection string were obtained. On this basis, a set of rapid selection method of water sources for water injection wells was formed, and the water quality of three water sources (No.1, No.2 and No.3) of a water injection well in Bohai A oilfield was analyzed by this method. The ranking of the water sources was “No.2 > No.1 > No.3” after calculation. Through SI index measurement experiment and scraper corrosion test, the accuracy of the selection method was verified. This method can be applied to water quality selection of injection wells in Bohai oilfield in the future, and has a good guiding significance for reducing scaling and corrosion of injection pipe string.
Key words
water injection well; water quality components; scaling corrosion; grey correlation analysis method; fuzzy matter-element method
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ZHANG Qi-long, XU Jie, GAO Bin, LI Jin, GONG Ning.
Research and Application of Water Source Selection Method for Water Injection Well Aiming at Inhibiting Scaling and Corrosion of Pipe String[J]. Surface Technology. 2019, 48(11): 290-296
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Funding
Supported by the " Thirteenth Five-Year" Major National Science and Technology Projects (2016ZX05058-002) and National Natural Science Foundation of China (51490652)