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Production prediction at ultra-high water cut stage via Recurrent Neural Network
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WANG Hongliang,MU Longxin,SHI Fugeng,DOU Hongen
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Table 3 Predicted production of two other oilfields by LSTM model.
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Time | Monthly oil output of oilfield 1 | Monthly oil output of oilfield 2 | Actual output/t | Predicted output/t | Relative error/% | Actual output/t | Predicted output/t | Relative error/% | January 2018 | 359 499 | 348 874 | 2.96 | 7964 | 7961 | 0.04 | February 2018 | 320 816 | 321 998 | 0.37 | 7137 | 7821 | 9.58 | March 2018 | 345 256 | 344 530 | 0.21 | 7529 | 7893 | 4.83 | April 2018 | 331 233 | 335 417 | 1.26 | 7462 | 7868 | 5.44 | May 2018 | 342 588 | 339 255 | 0.97 | 8173 | 7965 | 2.54 | June 2018 | 338 639 | 334 328 | 1.27 | 8020 | 7840 | 2.24 | July 2018 | 348 521 | 340 717 | 2.24 | 8000 | 7876 | 1.55 | August 2018 | 346 023 | 341 975 | 1.17 | 7968 | 7779 | 2.37 | September 2018 | 330 353 | 334 579 | 1.28 | 7315 | 7795 | 6.56 | October 2018 | 342 760 | 340 823 | 0.57 | 6988 | 7918 | 13.31 | November 2018 | 329 982 | 333 913 | 1.19 | 6928 | 7712 | 11.32 | December 2018 | 338 437 | 336 907 | 0.45 | 7481 | 7787 | 4.09 |
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