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Revista Brasileira de Geofísica, 2016
ABSTRACT. A practical approach to estimate rock thermal conductivities is to use models based on the observed mineral content. Here we evaluate the performances of the Krischer and Esdorn (KE), Hashin and Shtrikman (HS), classic Maxwell (CM), Maxwell-Wiener (MW), and geometric mean...Keywords: thermal conductivity, rock models, crystalline rocks, Borborema Province. RESUMO. Uma abordagem prática para estimar a condutividade térmica de uma rocha é usar modelos baseados no conteúdo de minerais constituintes. Nesse estudo, nós avaliamos o desempenho dos modelos de Krischer e Esdorn...Palavras-chave: condutividade térmica, modelos de rocha, rochas cristalinas, Província Borborema...
Thermal Conductivity in Relation to Porosity and Geological Stratigraphy
2010
Thermal conductivity of rocks is one of the most important parameters in thermal studies of geothermal features. The best estimation of heat quantity and heat flow of geothermal systems depends on accurate calculations of thermal conductivity in porous media. Several authors have studied thermal conductivity and have found it to be connected to several parameters including rock porosity, the most influential parameter. The aim of this project is to analyse small scale variations in thermal conductivity in context with porosity and the stratigraphic column. High resolution temperature logs were made for this project in well HS-36 located in Reykjavík, SW-Iceland. A detailed study focusing primarily on the depth between 400 and 600 m was completed. The temperature gradient was studied where the vertical heat flow is constant and does not have a horizontal component. The results obtained show that thermal conductivity decreases with increasing porosity and the relationship between ther...
Mineralogy, porosity and fluid control on thermal conductivity of sedimentary rocks
Geophysical Journal International, 1989
Estimates of thermal conductivity of the main non-clay and clay sedimentary minerals are presented, especially for the case of argillaceous ones. These estimates are averaged estimates based on the interpretation of laboratory conductivity, porosity and mineralogy measurements performed on small volumes (of the order of 100 cm3) of water-saturated, moist and air-saturated samples. The sampling is representative of the main sedimentary rocks (sandstones, carbonates, evaporites and shales), and it is composed of samples considered as structurally isotropic material.First, we experimentally verify the first-order control of mineralogy, porosity and fluid content on bulk conductivity, and we demonstrate that such influences may be predicted accurately using a geometric mean model, as long as isotropic samples are used. Then we interpret the data using an inverse method, in order to estimate the average mineral conductivities of the main non-clay and clay minerals which give the best fit to the individual laboratory measurements through the geometric mean model.The analysis is based on measurements on 82 non-clay samples and 29 clay samples taken on oil-well cores or cuttings, on outcrops and on artificially recompacted samples. Estimates of average mineral conductivities returned by the inversion process, for the main non-clay minerals, are similar to generally admitted values: 7.7 W m-1 K-1 for quartz, 3.3 W m-1 K-1 for calcite, 5.3 W m-1 K-1 for dolomite and 6.3 W m-1 K-1 for anhydrite. Values obtained for the clay minerals are systematically lower than those obtained for non-clay ones, they are of the order of 1.9 W m-1 K-1 for illite and smectite, 2.6 W m-1 K-1 for kaolinite and 3.3 W m-1 K-1 for chlorite.These estimates, combined with porosity and mineralogy data, are used with the geometric mean model in order to verify its first-order validity for predicting thermal conductivity of small volumes of porous isotropic sedimentary rocks. The bulk conductivity is predicted with an accuracy of the order of ±10 per cent for moist or water-saturated samples, and of the order of ±20 per cent for air-saturated samples.