Abstract:Monitoring and forecasting oil and gas (O\&G) production is essential to extend the life of a well and increase reservoirs' productivity. Popular models for O\&G time series are ARIMA and LSTM recurrent networks, and tipically several lags are forecasted at once. LSTM models can deploy the recursive prediction strategy, which uses one prediction to make the next, or the multiple outputs (MO) strategy, which predicts a sequence of values in a single shot. This work assesses ARIMA and LSTM models for the… Show more
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