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Total Organic Carbon Prediction In Barnett Shale Gas Reservoir Using The Multilayer Perceptron Neural Network
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, ECMOR XVI - 16th European Conference on the Mathematics of Oil Recovery, Sep 2018, Volume 2018, p.1 - 14
Abstract
Summary
In this paper, we predict the Total Organic Carbon from raw well-logs data recorded in two horizontal wells drilled in the Lower Barnett shale formation using the Multilayer Perceptron neural network machine. A comparative study between the Levenberg-Marquardt and the Conjugate Gradient learning algorithms shows the power of the Levenberg-Marquardt to predict the Total Organic Carbon in case of lake in the measurement of the Bulk density log, this can help to resolve the lake of the Schmoker’s method which requires continuous measurement of the bulk density log
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