Konaté2019_Chapter_MineralogyRecognitionFromIn-Si-2.pdf (original) (raw)
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Results in Geophysical Sciences, 2022
Metamorphic rocks are diverse with more compositions, structures, and textures that are complex. Rock type identification and prediction from metamorphic rocks using well log data are difficult tasks. This study shows the use of cross plot technique, Pearson correlation, and factor analysis in metamorphic rocks interpretation using borehole geochemical data from the 4390-5089 m interval depth of the Chinese Continental Scientific Drilling Main hole. Lithological identification abilities, correlation between geochemical and geophysical logs, and build a factor model which link in situ chemical element to minerals were studied. The results show that Potassium and Thorium logs are the most discriminating logs in metamorphic rocks. Pearson correlation shows that Potassium and Thorium are the largest contributors to the gamma ray responses. Factor analysis results show a 2 factor model-where factor 1 (amphibole mineral) and factor 2 (K-feldspar mineral) described 76.261% of the variation in log responses. These statistical methods can be a very helpful tool in helping the task of geoscientists in the context of research drillings.
Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine, 2017
The availability of a deep well that penetrates deep into the Ultra High Pressure (UHP) metamorphic rocks is unusual and consequently offers a unique chance to study the metamorphic rocks. One such borehole is located in the southern part of Donghai County in the Sulu UHP metamorphic belt of Eastern China, from the Chinese Continental Scientific Drilling Main hole. This study reports the results obtained from the analysis of oxide log data. A geochemical logging tool provides in situ, gamma ray spectroscopy measurements of major and trace elements in the borehole. Dry weight percent oxide concentration logs obtained for this study were SiO2, K2O, TiO2, H2O, CO2, Na2O, Fe2O3, FeO, CaO, MnO, MgO, P2O5 and Al2O3. Cross plot and Principal Component Analysis methods were applied for lithology characterization and mineralogy description respectively. Cross plot analysis allows lithological variations to be characterized. Principal Component Analysis shows that the oxide logs can be summar...
Shakhla Abdullayeva, Baku State University, Azerbaijan, Vasif Baba-zadeh, Baku State University, Azerbaijan, Sergo Kekeliya, Tbilisi State University, Al. Janelidze Institute of Geology, Georgia, Nazim Imamverdiyev,Baku State University, Azerbaijan, Mamoy Mansurov, Baku State University, Azerbaijan, Tarana Takhmazova, Baku State University, Azerbaijan, Maren Kekeliya, Tbilisi State University, Al. Janelidze Institute of Geology, Georgia, Alexander Romanko, Geological Institute, Academy of Sciences, Moscow, Russian Federation Abstract. Under the multi-factor models of the deposits we mean a set of informative features of near-ore space, necessary and sufficient to quantitative assessment of the prospective area with the rank of their differentiation. It should be emphasized that without knowledge of features that characterize the supra-ore, ore and under-ore areas of any genetic type of deposits, any stage prospecting of geological exploration process will fail. Obligatory condition of isolating factors (attributes) is the ability of recognizing them with modern geological, geochemical and geophysical methods. It is known that the regional metallogenic studies use ore-formation analysis which assesses the ore potential of the region (qualitative estimate) with the assistance of an abstracted image of a group of deposits (ore formation) that are similar in material composition and geological settings and that respond to certain 2496 Engineering Computations stages of the development of mobile belts. Therefore, the possibilities of ore formation analysis are limited. Large-scale studies require knowledge of specific reference objects. The latter have unique features of near-ore space, depending on the individual development of concrete blocks of the earth's crust, hosting oremagmatic systems. As grounds, on the basis of which were developed multi-factor models, were
Log interpretation parameters determined from chemistry, mineralogy and nuclear forward modeling
The determination of suitable parameters to properly interpret log data in terms of porosity, clay content and water saturation is often arduous. For example, classical estimates of clay volume frequently use the range of observed gamma ray values over a depth interval as a clay calibration. An improved procedure presented here integrates core mineralogy and chemistry as well as nuclear forward modeling. Accurate mineralogy (± 2 wt %) from the Dual-Range Fourier Transform Infrared (FT-IR) spectroscopy procedure is used. The chemical element analysis includes not only the major compositional elements but also all trace and minor elements that can significantly influence log responses. The chemical and mineralogical data are then used with nuclear forward modeling to provide the log response of logging sondes such as gamma ray, matrix density, hydrogen index, photoelectric absorption cross section, and thermal and epithermal neutron responses. It is then usually straightforward to see simple relationships between available logging variables and desired parameters.
Mineralogy from Geochemical Well Logging
Clays and Clay Minerals, 1986
Multivariate statistical analyses of geochemical, mineralogical, and cation-exchange capacity (CEC) data from a Venezuelan oil well were used to construct a model which relates elemental concentrations to mineral abundances. An r-mode factor analysis showed that most of the variance could be accounted for by four independent factors and that these factors were related to individual mineral components: kaolinite, illite, K-feldspar, and heavy minerals. Concentrations of AI, Fe, and K in core samptes were used to estimate the abundances of kaolinite, illite, K-feldspar, and, by subtraction from unity, quartz. Concentrations of these elements were also measured remotely in the well by geochemical logging tools and were used to estimate these mineral abundances on a continuous basis as a function of depth. The CEC was estimated from a linear combination of the derived kaolinite and illite abundances. The formation's thermal neutron capture cross section estimated from the log-derived mineralogy and a porosity log agreed well with the measured data. Concentrations of V, among other trace elements, were modeled as linear combinations of the clay mineral abundances. The measured core V agreed with the derived values in shales and water-bearing sands, but exceeded the day-derived values in samples containing heavy oil. The excess V was used to estimate the V content and API Gravity of the oil. The logderived clay mineralogy was used to help distinguish nonmarine from transitional depositional environments. Kaolinite was the dominant clay in nonmarine deposits, whereas transitional sediments contained more illite.
Understanding Geology and Structure: An Essential Part of Mineral Resource Estimation
ASEG Extended Abstracts, 2018
The assumption of continuity of mineralisation between sampling points, as stated in the JORC Code, requires a "confident interpretation of the geological framework". The elements of relevance to a geological framework vary greatly depending on the commodity and style of mineralisation. In general terms, at least two elements must be considered to underpin a geological framework: space and time. The geometry and location of a mineralised body are controlled by physical and/or chemical elements, which can be unravelled by detailed geological mapping, adequate geochemical (including a quality analysis-quality control program) and structural interpretations, and by 3D geological modelling. These elements may involve, among other, aspects of stratigraphy, chemical or physical properties of the rocks (e.g. texture, grain size) and structural features such as faults, fractures and folds. Mineralisation events that lead to economic deposits are often relatively short-lived periods of focused fluid transfer and elementexchange, which result in mobilisation and deposition of metals in well-defined areas. Understanding the temporal framework and interaction of structural elements and mineralising events (determining genetic relationships, e.g. pre-, syn-and post-mineralisation) results in the development of more accurate geological models and can lead to predictive capabilities and new discoveries. We present case studies in regional metamorphic, igneous, sedimentary and surficial geological environments, demonstrating how understanding the mineralisation system not only results in increased confidence in the resource, but also facilitates reduction of exploration risks.
Crystals, 2020
Numerical comparison of mineralogical and geochemical data, which is required in a variety of geological applications, is a challenging task, especially when analyzing extensive sample collections. Herein, we apply factor analysis (FA) to a collection of 198 diffraction patterns of bulk rock samples from the Kontozero carbonatite complex. The mineralogical information hidden in the X-ray powder diffraction (XRPD) data is thereby squeezed down to a set of two dozen variables represented by factor scores (FS). The values of these FSs show a functional relationship with the contents of the minerals composing the rocks. Therefore, factor scores can be considered as a beneficial tool for rapid qualitative and semiquantitative analysis of the mineral composition of rocks. Supplementing principal component analysis (PCA) with FSs as independent variables characterizing the mineral content of rocks allows for the numerical comparison of mineralogical and geochemical data. By PCA, we reveal the main trends in the mineralogical and geochemical evolution of the investigated rocks of the Kontozero complex. Furthermore, the results are obtained in the very first stages of the research. This fact elucidates the potential use of the proposed technique in geological studies and mining.