Results 221 to 230 of about 32,628 (309)

Effects of temperature, brine, and inhibitor chemistry on emulsion stability in gas condensate systems under pipeline mixing conditions. [PDF]

Sci Rep
Behnam Motlagh MA, Saeedi Dehaghani AH, Tanhaei H.   +2 more
europepmc   +1 more source

Experimental study on concentration and temperature fields of carbon dioxide leakage under different terrain conditions. [PDF]

PLoS One
Li Y, Xiao F, Ma Z, Dong H, Zhang J, Zhou J, Li P.   +6 more
europepmc   +1 more source

Performance Evaluation of Enhanced Recovery Efficiency for Oxygen-Reducing Air Huff and Puff in Tight Reservoirs. [PDF]

ACS Omega
Liu T, Liu W, Huang X, Fu Y, Chen J.
europepmc   +1 more source

Nondestructive Inspection of Water Pipes: A Review. [PDF]

Sensors (Basel)
Nowroski R, Rizzo P, Byrne L, Ziegler A.
europepmc   +1 more source

Corrosion behavior study and failure time analysis of X65 pipeline steel in near-neutral soil. [PDF]

Sci Rep
Wang Y, Li X, Zhang J, Tu Q.
europepmc   +1 more source

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Leak detection and localization techniques in oil and gas pipeline: A bibliometric and systematic review

Engineering Failure Analysis, 2023
Jianfeng Zheng, Dezhi Zheng, Jie Yuan
exaly   +2 more sources

A methodology for overall consequence assessment in oil and gas pipeline industry

Process Safety Progress, 2019
Quantitative risk assessment (QRA) has been widely used in the oil and gas pipeline industry. QRA mainly includes four steps, namely, hazard identification, probability calculation, consequence assessment, and risk quantification.
Xuefeng Chen, Zongzhi Wu, Shu Wang
exaly   +2 more sources

Analyzing the Innovation Progress in Global Oil and Gas Pipeline Transportation

Journal of Pipeline Systems Engineering and Practice
Minghan Sun
exaly   +2 more sources

A review on welding of high strength oil and gas pipeline steels

Journal of Natural Gas Science and Engineering, 2017
Satish Kumar Sharma, Sachin Maheshwari
exaly   +2 more sources

Estimation of Defect Size and Cross-Sectional Profile for the Oil and Gas Pipeline Using Visual Deep Transfer Learning Neural Network

IEEE Transactions on Instrumentation and Measurement, 2023
The magnetic flux leakage (MFL) defect detection of oil and gas pipelines faces two tasks, defect type identification and defect size and shape estimation.
Min Zhang, Yanbao Guo, Qiuju Xie, Yuansheng Zhang, Deguo Wang, Jinzhong Chen   +5 more
semanticscholar   +1 more source