Single well production dynamic prediction method based on long and short term memory deep neural network
The invention discloses a single well production dynamic prediction method based on a long and short term memory deep neural network. The method comprises the following steps: acquiring an input historical data set X and an output historical data set Y; respectively extracting an input training set...
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| creator | LI MENG ZHAO HUAWEI ZHANG WENBIAO LI LINDI DUAN TAIZHONG LIU YANFENG LIAN PEIQING LI MIAO LU WENMING MA QIQI |
| description | The invention discloses a single well production dynamic prediction method based on a long and short term memory deep neural network. The method comprises the following steps: acquiring an input historical data set X and an output historical data set Y; respectively extracting an input training set X1 and an input test set X2 from the input historical data set X, and obtaining a production dynamic prediction model and an output test prediction set Y2 by applying a long-short term memory deep neural network; screening out a production dynamic prediction model meeting an expected effect through a root-mean-square error function; obtaining single-well production parameters and single-well production parameter constraint conditions, and generating a plurality of injection-production schemes by applying an optimization algorithm; and for each injection-production scheme, acquiring historical production dynamic data corresponding to each injection-production scheme, and sequentially applying the production dynamic |
| format | Patent |
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The method comprises the following steps: acquiring an input historical data set X and an output historical data set Y; respectively extracting an input training set X1 and an input test set X2 from the input historical data set X, and obtaining a production dynamic prediction model and an output test prediction set Y2 by applying a long-short term memory deep neural network; screening out a production dynamic prediction model meeting an expected effect through a root-mean-square error function; obtaining single-well production parameters and single-well production parameter constraint conditions, and generating a plurality of injection-production schemes by applying an optimization algorithm; and for each injection-production scheme, acquiring historical production dynamic data corresponding to each injection-production scheme, and sequentially applying the production dynamic</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Single well production dynamic prediction method based on long and short term memory deep neural network |
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