Using a hybrid GA-BP model for estimation of total organic carbon from petrophysical data

Authors

1 Department of Geology, Faculty of Natural Science, Tabriz, NW Iran.

2 Department of Mechanical Engineering, University of Tehran, Tehran Iran.

Abstract

Total Organic Carbon (TOC) is the most important parameter to evaluate hydrocarbon generation potential of source rocks. To measure this parameter, expensive and Time-consuming geochemical experiments have been carried out on few samples. Therefore, the main purpose of this study is to estimate the TOC geochemical parameter from petrophysical data that nowadays they are prepared from all wells drilled with low costs. For this purpose, a hybrid system of GA-BP was used. This model is performed using a case study from three wells of the Ahwaz oilfield. The results of this study are compared with genetic algorithm and BP neural network. Results show GA-BP have the higher accuracy and more speed of execution than using them individually. The results of validity of the simulation with this model show that MSE and R2 in testing sample are 0.001299 and 0.973 respectively. This model has good performance and can be generalized to the other development wells.
 
 

Keywords

References

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