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Analysis of Well log Data Using Detrended Fluctuation Analysis and its Comparison with Other Methods (Multifractal Analysis of Well Log Data)
, M.Sc. Thesis Sharif University of Technology ; Sahimi, Mohammad (Supervisor) ; Massihi, Mohsen (Supervisor) ; Jafari, Gholam Reza (Supervisor)
Abstract
One of the main challenges in characterization and simulation of larg scale porous media is spatial heterogeneity and variability of porous media properties such as porosity, density, and lithology at different scales. These information can be achieved at different scale from coring, well logging or seismic data. Well logs are an efficient way to obtain rock and fluid properties of geological patterns specially water resources and hydrocarbon reservoirs. One of the characteristics of geophysical well logs is their complex behavior which seems to imply a multifractal nature.In this study we investigate multifractality and presence of long range correlations in petrophysical well log data such...
Analysis of cross correlations between well logs of hydrocarbon reservoirs
, Article Transport in Porous Media ; Volume 90, Issue 2 , 2011 , Pages 445-464 ; 01693913 (ISSN) ; Jafari, G. R ; Lai, Z. K ; Masihi, M ; Sahimi, M ; Sharif University of Technology
Abstract
We carry out a series of cross-correlation analysis of raw well-log data, in order to study the possible connection between natural gamma ray (GR) logs and other types of well logs, such as neutron porosity (NPHI), sonic transient time (denoted usually by DT), and bulk density (RHOB) of oil and gas reservoirs. Three distinct, but complementary, methods are used to analyze the cross correlations, namely, the multifractal detrended cross-correlation analysis (MF-DXA), the so-called Qcc(m) test in conjunction with the statistical test-the χ2(m) distribution-and the cross-wavelet transform (XWT) and wavelet coherency. The Qcc(m) test and MF-DXA are used to identify and quantify the strength of...
The estimation of formation permeability in a carbonate reservoir using an artificial neural network
, Article Petroleum Science and Technology ; Vol. 30, issue. 10 , Apr , 2010 , p. 1021-1030 ; ISSN: 10916466 ; Masihi, M ; Fatholah,i S ; Sharif University of Technology
Abstract
Reservoir permeability is an important parameter that its reliable prediction is necessary for reservoir performance assessment and management. Although many empirical formulas are derived regarding permeability and porosity in sandstone reservoirs, these correlations cannot be accurately depicted in carbonate reservoir for the wells that are not cored and for which there are no welltest data. Therefore, having a framework for estimation of these parameters in reservoirs with neither coring samples nor welltest data is crucial. Rock properties are characterized by using different well logs. However, there is no specific petrophysical log for estimating rock permeability; thus, new methods...
The estimation of formation permeability in a carbonate reservoir using an artificial neural network
, Article Petroleum Science and Technology ; Volume 30, Issue 10 , 2012 , Pages 1021-1030 ; 10916466 (ISSN) ; Masihi, M ; Fatholahi, S ; Sharif University of Technology
2012
Abstract
Reservoir permeability is an important parameter that its reliable prediction is necessary for reservoir performance assessment and management. Although many empirical formulas are derived regarding permeability and porosity in sandstone reservoirs, these correlations cannot be accurately depicted in carbonate reservoir for the wells that are not cored and for which there are no welltest data. Therefore, having a framework for estimation of these parameters in reservoirs with neither coring samples nor welltest data is crucial. Rock properties are characterized by using different well logs. However, there is no specific petrophysical log for estimating rock permeability; thus, new methods...
Permeability modeling using ANN and collocated cokriging
, Article 72nd European Association of Geoscientists and Engineers Conference and Exhibition 2010: A New Spring for Geoscience. Incorporating SPE EUROPEC 2010 ; Volume 5 , 2010 , Pages 3939-3943 ; 9781617386671 (ISBN) ; Masihi, M ; Sharif University of Technology
Society of Petroleum Engineers
2010
Abstract
Obtaining a reliable reservoir permeability map that is consistent with all available data is of great important for reservoir engineers. However, there is not enough core from existing wells to estimate the reservoir permeability directly but Well log data are more widely available. This study aims to model permeability within the reservoir while there is no enough data. In particular, we use artificial neural networks to estimate permeability using four input logs of sonic, gravity, porosity and neutron logs in six existing wells. In order to eliminate the correlated data, we have done Principal Component Analysis on selected input logs. Collocated cokriging is considered as a valuable...
Scaling, multifractality, and long-range correlations in well log data of large-scale porous media
, Article Physica A: Statistical Mechanics and its Applications ; Vol. 390, issue. 11 , June , 2011 , p. 2096-2111 ; ISSN: 03784371 ; Jafari, G. R ; Sahimi, M ; Masihi, M ; Sharif University of Technology
Abstract
Three distinct methods, namely, the spectral density, the multifractal random walk approach, and the multifractal detrended fluctuation analysis are utilized to study the properties of four distinct types of well logs from three oil and gas fields, namely, the natural gamma ray emission, neutron porosity, bulk density, and the sonic transient time logs. Such well logs have never been analyzed by the methods that we utilize in the present study. The results indicate that the well logs exhibit multifractal characteristics, and the estimated Hurst exponents by the three methods are close to each other. Using multifractal detrended fluctuation analysis and the shuffled and surrogated data, we...
Scaling, multifractality, and long-range correlations in well log data of large-scale porous media
, Article Physica A: Statistical Mechanics and its Applications ; Volume 390, Issue 11 , 2011 , Pages 2096-2111 ; 03784371 (ISSN) ; Jafari, G. R ; Sahimi, M ; Masihi, M ; Sharif University of Technology
2011
Abstract
Three distinct methods, namely, the spectral density, the multifractal random walk approach, and the multifractal detrended fluctuation analysis are utilized to study the properties of four distinct types of well logs from three oil and gas fields, namely, the natural gamma ray emission, neutron porosity, bulk density, and the sonic transient time logs. Such well logs have never been analyzed by the methods that we utilize in the present study. The results indicate that the well logs exhibit multifractal characteristics, and the estimated Hurst exponents by the three methods are close to each other. Using multifractal detrended fluctuation analysis and the shuffled and surrogated data, we...