Effect of meteorological data quality control and data adjustment on the reference evapotranspiration: a case study in Jafariye, Iran

2020 ◽  
Vol 141 (1-2) ◽  
pp. 331-342
Author(s):  
Ruhullah Yari ◽  
Abdullah Darzi-Naftchali ◽  
Hossein Dehghanisanij ◽  
Zhiming Qi
2019 ◽  
Vol 2 (3) ◽  
pp. 147-153
Author(s):  
Georgy Loginov ◽  
Anton Duchkov ◽  
Dmitry Litvichenko ◽  
Sergey Alyamkin

The paper considers the use of a convolution neural network for detecting first arrivals for a real set of 3D seismic data with more than 4.5 million traces. Detection of the first breaks for each trace is carried out independently. The error between the original and the predicted first breaks is no more than 3 samples for 95% of the data. Quality control is performed by calculating static corrections and seismic stacks, which showed the effectiveness of the proposed approach.


Author(s):  
Antonella D. Pontoriero ◽  
Giovanna Nordio ◽  
Rubaida Easmin ◽  
Alessio Giacomel ◽  
Barbara Santangelo ◽  
...  

2001 ◽  
Vol 27 (7) ◽  
pp. 867-876 ◽  
Author(s):  
Pankajakshan Thadathil ◽  
Aravind K Ghosh ◽  
J.S Sarupria ◽  
V.V Gopalakrishna

2014 ◽  
Vol 926-930 ◽  
pp. 4254-4257 ◽  
Author(s):  
Jin Xu ◽  
Da Tao Yu ◽  
Zhong Jie Yuan ◽  
Bo Li ◽  
Zi Zhou Xu

Traditional artificial perception quality control methods of marine environment monitoring data have many disadvantages, including high labor costs and mistakes of data review. Based on GIS spatial analysis technology, Marine Environment Monitoring Data Quality Control System is established according to the Bohai Sea monitoring regulation. In the practical application process, it plays the role of improving efficiency of quality control, saving the manpower and financial resources. It also provides an important guarantee for the comprehensive analysis and management of marine environment data.


1980 ◽  
Vol 1 (2) ◽  
pp. 171-172
Author(s):  
M.M. Koretz ◽  
M. Kohler ◽  
E. McGuigan ◽  
J.F. Hannigan ◽  
B.W. Brown

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