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1	Determining Mineralogy from Traditional Well Log Data Kurtz, Aaron D. 27 April 2013 (has links) No description available. Petroleum Engineering Petroleum Geology Dual Water Theory Density mineral composition formation evaluation quartz shale effective porosity porosity gamma ray software
2	Prediction of reservoir properties of the N-sand, vermilion block 50, Gulf of Mexico, from multivariate seismic attributes Jaradat, Rasheed Abdelkareem 29 August 2005 (has links) The quantitative estimation of reservoir properties directly from seismic data is a major goal of reservoir characterization. Integrated reservoir characterization makes use of different varieties of well and seismic data to construct detailed spatial estimates of petrophysical and fluid reservoir properties. The advantage of data integration is the generation of consistent and accurate reservoir models that can be used for reservoir optimization, management and development. This is particularly valuable in mature field settings where hydrocarbons are known to exist but their exact location, pay, lateral variations and other properties are poorly defined. Recent approaches of reservoir characterization make use of individual seismic attributes to estimate inter-well reservoir properties. However, these attributes share a considerable amount of information among them and can lead to spurious correlations. An alternative approach is to evaluate reservoir properties using multiple seismic attributes. This study reports the results of an investigation of the use of multivariate seismic attributes to predict lateral reservoir properties of gross thickness, net thickness, gross effective porosity, net-to-gross ratio and net reservoir porosity thickness product. This approach uses principal component analysis and principal factor analysis to transform eighteen relatively correlated original seismic attributes into a set of mutually orthogonal or independent PC??s and PF??s which are designated as multivariate seismic attributes. Data from the N-sand interval of Vermilion Block 50 field, Gulf of Mexico, was used in this study. Multivariate analyses produced eighteen PC??s and three PF??s grid maps. A collocated cokriging geostaistical technique was used to estimate the spatial distribution of reservoir properties of eighteen wells penetrating the N-sand interval. Reservoir property maps generated by using multivariate seismic attributes yield highly accurate predictions of reservoir properties when compared to predictions produced with original individual seismic attributes. To the contrary of the original seismic attribute results, predicted reservoir properties of the multivariate seismic attributes honor the lateral geological heterogeneities imbedded within seismic data and strongly maintain the proposed geological model of the N-sand interval. Results suggest that multivariate seismic attribute technique can be used to predict various reservoir properties and can be applied to a wide variety of geological and geophysical settings. Integrated reservoir characterization Reservoir property mapping Seismic attributes Multiple seismic attributes Multivariate seismic attributes Principal component analysis Principal factor analysis Gross thickness Net thickness Gross effective porosity Net-to-gross ratio Net reservoir porosity thickness product Gulf Of Mexico Vermilion Block 50 Miocene.
3	Prediction of reservoir properties of the N-sand, vermilion block 50, Gulf of Mexico, from multivariate seismic attributes Jaradat, Rasheed Abdelkareem 29 August 2005 (has links) The quantitative estimation of reservoir properties directly from seismic data is a major goal of reservoir characterization. Integrated reservoir characterization makes use of different varieties of well and seismic data to construct detailed spatial estimates of petrophysical and fluid reservoir properties. The advantage of data integration is the generation of consistent and accurate reservoir models that can be used for reservoir optimization, management and development. This is particularly valuable in mature field settings where hydrocarbons are known to exist but their exact location, pay, lateral variations and other properties are poorly defined. Recent approaches of reservoir characterization make use of individual seismic attributes to estimate inter-well reservoir properties. However, these attributes share a considerable amount of information among them and can lead to spurious correlations. An alternative approach is to evaluate reservoir properties using multiple seismic attributes. This study reports the results of an investigation of the use of multivariate seismic attributes to predict lateral reservoir properties of gross thickness, net thickness, gross effective porosity, net-to-gross ratio and net reservoir porosity thickness product. This approach uses principal component analysis and principal factor analysis to transform eighteen relatively correlated original seismic attributes into a set of mutually orthogonal or independent PC??s and PF??s which are designated as multivariate seismic attributes. Data from the N-sand interval of Vermilion Block 50 field, Gulf of Mexico, was used in this study. Multivariate analyses produced eighteen PC??s and three PF??s grid maps. A collocated cokriging geostaistical technique was used to estimate the spatial distribution of reservoir properties of eighteen wells penetrating the N-sand interval. Reservoir property maps generated by using multivariate seismic attributes yield highly accurate predictions of reservoir properties when compared to predictions produced with original individual seismic attributes. To the contrary of the original seismic attribute results, predicted reservoir properties of the multivariate seismic attributes honor the lateral geological heterogeneities imbedded within seismic data and strongly maintain the proposed geological model of the N-sand interval. Results suggest that multivariate seismic attribute technique can be used to predict various reservoir properties and can be applied to a wide variety of geological and geophysical settings. Integrated reservoir characterization Reservoir property mapping Seismic attributes Multiple seismic attributes Multivariate seismic attributes Principal component analysis Principal factor analysis Gross thickness Net thickness Gross effective porosity Net-to-gross ratio Net reservoir porosity thickness product Gulf Of Mexico Vermilion Block 50 Miocene.
4	Méthodologie d’analyse des signaux et caractérisation hydrogéologique : application aux chroniques de données obtenues aux laboratoires souterrains du Mont Terri, Tournemire et Meuse/Haute-Marne / Signal analyzis methodology and hydrogeologic characterization : application to time series collected at the underground research laboratories of Mont Terri, Tournemire, and Meuse/Haute-Marne Fatmi, Hassane 29 May 2009 (has links) Ce rapport présente des méthodes de prétraitement, d'analyse statistique et d'interprétation de chroniques hydrogéologiques de massifs peu perméables (argilites) dans le cadre d'études sur le stockage profond de déchets radioactifs. Les séries temporelles analysées sont la pression interstitielle et la pression atmosphérique, en relation avec différents phénomènes (marées terrestres, effet barométrique, évolution de l'excavation des galeries). Les pré-traitements permettent de reconstituer et homogénéiser les chroniques de données en présence de lacunes, aberrations, et pas de temps variables. Les signaux prétraités sont ensuite analysés en vue de caractériser les propriétés hydrauliques du massif peu perméable (emmagasinement spécifique ; porosité effective). Pour cela, on a développé et mis en oeuvre les méthodes d'analyses suivantes (implémentées en Matlab): analyses corrélatoires et spectrales (Fourier) ; analyses ondelettes multirésolution ; enveloppes de signaux aléatoires. Cette méthodologie est appliquée aux données acquises au Laboratoire Souterrain du Consortium International du Mont Terri (Jura Suisse), ainsi qu'à certaines données des Laboratoires Souterrains de Tournemire (Aveyron) et de Meuse / Haute-Marne (ANDRA) / This report presents a set of statistical methods for pre-processing and analyzing multivariate hydrogeologic time series, such as pore pressure and its relation to atmospheric pressure. The goal is to study the hydrogeologic characteristics of low permeability geologic formations (argilite) in the context of deep disposal of radioactive waste. The pressure time series are analyzed in relation with different phenomena, such as earth tides, barometric effects, and the evolution of excavated galleries. The pre-processing is necessary for reconstituting and homogenizing the time series in the presence of data gaps, outliers, and variable time steps. The preprocessed signals are then analyzed with a view to characterizing the hydraulic properties of this type of low permeability formation (specific storativity; effective porosity). For this sake, we have developed and used the following methods (implemented in Matlab): temporal correlation analyses; spectral/Fourier analyses; multiresolution wavelet analyses envelopes of random processes. This methodology is applied to data collected at the URL (Underground Research Laboratory) of the Mont Terri International Consortium (Swiss Jura), as well as some other data collected at the URL of IRSN at Tournemire (Aveyron) and at the URL of ANDRA (Meuse / Haute-Marne) Mont Terri Tournemire Bure Argilite Argiles à Opalines Callovo-Oxfordien Pression interstitielle Chroniques Séries temporelles Traitement des signaux Processus aléatoires Prétraitements Reconstitution Analyse corrélatoire Analyse spectrale Ondelettes multirésolution Marées terrestres Effet barométrique Compressibilité Porosité Emmagasinement spécifique Porosité effective EDZ (Excavation Damaged Zone) Perméabilité Pore pressure Argilite Signal pre-processing Random processes Earth tides Barometric effect Specific storativity Effective porosity Correlation analyses Spectral Fourier analyses Multiresolution wavelet analyses EDZ (Excavation Damaged Zone) Hydrogeology

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