The success of an Artificial Neural Network (ANN) based data interpretation model depends heavily on the availability and the characteristics of the training data. In the process of developing a reliable well log interpretation model, a log analyst has to spend many hours to perform pre-processing on the training data set. This demands substantial experience and expertise from the analyst. This...

Recently, Neural Networks became a popular method in geosciences in the context of pattern recognition problems. They can be used for classification of well logs, for image processing, for anomaly detection and similar problems. In the past, such problems were mainly solved by statistical approaches. However parametric statistical classification methods suffer from strong assumptions and nonpar...

Ranking from pairwise comparisons is a ubiquitous problem and has been studied in disciplines ranging from statistics to operations research and from theoretical computer science to machine learning. Here we consider a general setting where outcomes of pairwise comparisons between items i and j are drawn probabilistically by flipping a coin with unknown bias Pij , and ask under what conditions ...

The spatial distribution of petrophysical properties within the reservoirs is one of the most important factors in reservoir characterization. Flow units are the continuous body over a specific reservoir volume within which the geological and petrophysical properties are the same. Accordingly, an accurate prediction of flow units is a major task to achieve a reliable petrophysical description o...

A method for 3D modeling and interpretation of log properties from complex seismic attributes (obtained from 3D post stack seismic data) is developed by integrating Principal Component Analysis and Local Linear Modeling. Complex seismic attributes have non-linear relationships with petrophysical properties of rocks. These complicated relationships can be approximated using statistical methods. ...

Well logging is an important tool for the characterization of subsurface rocks, being commonly used in the study of reservoir geology. It is well known that signals obtained as responses from geological media contain noise that can affect their interpretation, and that wavelet transform is more suitable than the Fourier transform to denoise non-stationary signals, as the ones obtained from well...

Extensive work has been done in the recent years involving use of conventional and passive seismic data for fracture characterization. This is particularly the case with unconventional reservoirs such as shale gas, shale oil and geothermal fields. The purpose of our study is to combine the benefits of conventional seismic data that provides relatively higher resolution reservoir characteristics...