Analysis of Prediction of Pressure Data in Oil Wells Using Artificial Neural Networks

We present a methodology that integrates an artificial intelligent technology called Artificial Neural Networks (ANN's) to develop and build a forecasting system that determines the behavior of the pressure of an oil reservoir, from its behavior, considered as reference in relation to four neighboring wells, which are producing at the same stratum. 356 data records were taken (a period of one year). During that period, it was observed that pressure curves show a decrease, which describes the behavior of the reservoir. It was also considered as an additional parameter the average pressure of the reservoir, whose information was obtained from the curves, describing the behavior of bottom pressure in the same stratum during the given period. Finally, we present the results of the predictions of pressure data, compared with the actual values of the reservoirs known, to discuss and assess the accuracy of the prediction of the proposed system.