Robust committee machine for water saturation prediction

A committee machine with empirical formulas for permeability prediction

This study integrates log-derived empirical formulas and the concept of the committee machine to develop an improved model for predicting permeability. A set of three empirical formulas, such as the Wyllie–Rose, Coates–Dumanoir, and porosity models to correlate reservoir well-logging information with measured core permeability, are used as expert members in a committee machine. A committee mach...

simulation and experimental studies for prediction mineral scale formation in oil field during mixing of injection and formation water

abstract: mineral scaling in oil and gas production equipment is one of the most important problem that occurs while water injection and it has been recognized to be a major operational problem. the incompatibility between injected and formation waters may result in inorganic scale precipitation in the equipment and reservoir and then reduction of oil production rate and water injection rate. ...

Water Level Prediction for Disaster Management Using Machine Learning Models

A flood is an overflow of water and becomes the common natural disaster. Prediction of a flood is one of the challenges for disaster management around the world especially in developing countries. Thus, more accurate flood prediction models have been investigated according to the geographical locations. In this paper, we have studied and compared some useful machine learning models such as KNN,...

A Robust Methodology for Prediction of DT Wireline Log

DT log is one of the most frequently used wireline logs to determine compression wave velocity. This log is commonly used to gain insight into the elastic and petrophysical parameters of reservoir rocks. Acquisition of DT log is, however, a very expensive and time consuming task. Thus prediction of this log by any means can be a great help by decreasing the amount of money that needs to be allo...

A Bayesian Committee Machine