Ali Akbar Rahimi Bahar
Abstract
Accurate estimation of hydrocarbon volume in a reservoir is important due to future development and investment on that reservoir. Estimation of Oil and Gas reservoirs continues from exploration to end of reservoir time life and is usual upstream engineer’s involvements. In this study we tried to make ...
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Accurate estimation of hydrocarbon volume in a reservoir is important due to future development and investment on that reservoir. Estimation of Oil and Gas reservoirs continues from exploration to end of reservoir time life and is usual upstream engineer’s involvements. In this study we tried to make reservoir properties models (porosity and water saturation) and estimate reservoir volume hydrocarbon based on artificial neural network tools, petrophysical and geophysical data. So with gridding the reserve, separate it to same volume cells. Based on porosity and lithology variation in wells, constructed petrophysical zonation in each well and by correlation these zones in wells reservoir has been zoned. Porosity, water saturation and 3D seismic data have been averaged in cells and assigned one value for each cell. At final a three layer perceptron neural network by back propagation error algorithm has been designed and trained by using cells which had petrophysical data; then these parameters have been estimated in other cells and original hydrocarbon in place calculated and compared with results from Mont Carlo method.
Hassan Monsef; Taher Ghomian
Abstract
This paper introduces Artificial Neural Network (ANN) method for measuring voltage in the Optical Voltage Transducer (OVT) using one or more electric field sensors. In order to obtain an accurate voltage measurement with minimum number of sensors, first the locations of sensors are specified by quadrature ...
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This paper introduces Artificial Neural Network (ANN) method for measuring voltage in the Optical Voltage Transducer (OVT) using one or more electric field sensors. In order to obtain an accurate voltage measurement with minimum number of sensors, first the locations of sensors are specified by quadrature method. Then the electric field intensity at these locations is provided to ANN for the calculation of applied voltages. Less number of sensors with no displacement required to obtain high accuracy is the most important advantage of this method. The numerical simulations demonstrate the effectiveness of this technique.
