US 12,421,839 B2
Multi-objective optimization on modeling and optimizing scaling and corrosion in a wellbore
Da Pang, Beijing (CN); Srinath Madasu, Houston, TX (US); Xinli Jia, Sugar Land, TX (US); and Keshava Prasad Rangarajan, Sugar Land, TX (US)
Assigned to Landmark Graphics Corporation, Houston, TX (US)
Appl. No. 17/279,969
Filed by Landmark Graphics Corporation, Houston, TX (US)
PCT Filed Apr. 13, 2020, PCT No. PCT/US2020/028013
§ 371(c)(1), (2) Date Mar. 25, 2021,
PCT Pub. No. WO2021/211092, PCT Pub. Date Oct. 21, 2021.
Prior Publication US 2022/0112799 A1, Apr. 14, 2022
Int. Cl. E21B 41/02 (2006.01); E21B 37/06 (2006.01); E21B 47/00 (2012.01); E21B 47/07 (2012.01); E21B 47/10 (2012.01); E21B 49/08 (2006.01); G05B 13/02 (2006.01); G05B 13/04 (2006.01)
CPC E21B 47/006 (2020.05) [E21B 37/06 (2013.01); E21B 41/02 (2013.01); E21B 47/07 (2020.05); E21B 47/10 (2013.01); E21B 49/0875 (2020.05); G05B 13/027 (2013.01); G05B 13/041 (2013.01); E21B 2200/20 (2020.05); E21B 2200/22 (2020.05)] 20 Claims
OG exemplary drawing
 
1. A method for optimizing scaling and corrosion in an oil field tubular, comprising:
obtaining a set of input parameters related to a fluid flowing in the oil field tubular;
performing a base calculation procedure to determine a corrosion rate and a scaling index reflecting a tendency of scale to form in the oil field tubular based on the set of input parameters, wherein the base calculation procedure yields a range of values for the corrosion rate and the scaling index along the oil field tubular;
selecting optimization points from the ranges of the corrosion rate and the scaling index obtained from the base calculation procedure, wherein the optimization points are selected at particular depths along the oil field tubular, and wherein at least one of the selected optimization points is selected at a depth that has a maximum value for the corrosion rate or the scaling index;
performing a multi-objective optimization for the selected optimization points of the corrosion rate and the scaling index; and
controlling an alkalinity and flow rate of the fluid based on the multi-objective optimization.