TY - BOOK

T1 - A petrographic-coded model - Derivation of relationships between thermal and other physical rock properties

AU - Gegenhuber, Nina

N1 - no embargo

PY - 2011

Y1 - 2011

N2 - Thermal conductivity is one of the key properties of geothermal and other geological and geophysical applications. Due to difficult measurements of thermal conductivity in boreholes, in most cases only laboratory data are available. Therefore the knowledge of correlations between thermal conductivity and other petrophysical properties (compressional wave velocity, density, electrical resistivity), which are measurable in a well, could deliver it indirectly. The analysis of experimental data clearly indicates that correlations between thermal conductivity and parameters like compressional wave velocity or density are very complex with partially opposite directions of influences from the controlling parameters. Three main influences could be detected -mineral composition or rock type -pore- or fracture volume fraction (porosity) -pore- or fracture geometry. In order to implement these influences a modular concept of model architecture has been developed. It comprises two main steps and is focussed mainly on the relationship between thermal conductivity and compressional wave velocity: Step 1: Modelling of mineral composition – this controls the petrographic code or rock type Step 2: Modelling or implementation of fractures, pores etc. with two model types (inclusion model, defect model). For implementation of fractures, pores etc., two models have been designed. The first one is an inclusion model and the second one a simpler defect model. Both can demonstrate the two main influencing factors on derived correlations: mineral composition and fractures/pores. These models have furthermore been applied on different rock types (metamorphic/magmatic rocks, sandstone, carbonates). The result is “a petrographic-coded thermal parameter estimation”. The application of correlations to measured logs results in a “thermal conductivity log”. The correlation between thermal conductivity and density seems relatively simple, but has a principal problem: Thermal conductivity is strongly controlled by pore and fracture shape, and by porosity – but, density is controlled only by porosity. Thus, density cannot cover the influence of internal rock geometry. -As a test also electrical resistivity was considered for carbonates. Compared with thermal conductivity the electrical resistivity cannot cover and express a variation of mineral composition. Therefore it works only within one exactly defined rock type (in this case carbonates). Specific models for the calculation of the anisotropy of thermal conductivity and an improved method to determine heat production from integral gamma ray logs have been developed. In the additional section the calculation of thermal heat production from rocks was evaluated and a new equation - implementing also a petrographic- coded concept - could be derived and tested.

AB - Thermal conductivity is one of the key properties of geothermal and other geological and geophysical applications. Due to difficult measurements of thermal conductivity in boreholes, in most cases only laboratory data are available. Therefore the knowledge of correlations between thermal conductivity and other petrophysical properties (compressional wave velocity, density, electrical resistivity), which are measurable in a well, could deliver it indirectly. The analysis of experimental data clearly indicates that correlations between thermal conductivity and parameters like compressional wave velocity or density are very complex with partially opposite directions of influences from the controlling parameters. Three main influences could be detected -mineral composition or rock type -pore- or fracture volume fraction (porosity) -pore- or fracture geometry. In order to implement these influences a modular concept of model architecture has been developed. It comprises two main steps and is focussed mainly on the relationship between thermal conductivity and compressional wave velocity: Step 1: Modelling of mineral composition – this controls the petrographic code or rock type Step 2: Modelling or implementation of fractures, pores etc. with two model types (inclusion model, defect model). For implementation of fractures, pores etc., two models have been designed. The first one is an inclusion model and the second one a simpler defect model. Both can demonstrate the two main influencing factors on derived correlations: mineral composition and fractures/pores. These models have furthermore been applied on different rock types (metamorphic/magmatic rocks, sandstone, carbonates). The result is “a petrographic-coded thermal parameter estimation”. The application of correlations to measured logs results in a “thermal conductivity log”. The correlation between thermal conductivity and density seems relatively simple, but has a principal problem: Thermal conductivity is strongly controlled by pore and fracture shape, and by porosity – but, density is controlled only by porosity. Thus, density cannot cover the influence of internal rock geometry. -As a test also electrical resistivity was considered for carbonates. Compared with thermal conductivity the electrical resistivity cannot cover and express a variation of mineral composition. Therefore it works only within one exactly defined rock type (in this case carbonates). Specific models for the calculation of the anisotropy of thermal conductivity and an improved method to determine heat production from integral gamma ray logs have been developed. In the additional section the calculation of thermal heat production from rocks was evaluated and a new equation - implementing also a petrographic- coded concept - could be derived and tested.

KW - thermal conductivity

KW - petrophysic

KW - compressional wave velocity

KW - heat production

KW - anisotropy

KW - correlation

KW - inclusion model

KW - defect model

KW - logs

KW - Wärmeleitfähigkeit

KW - Petrophysik

KW - Kompressionswellengeschwindigkeit

KW - Wärmeproduktion

KW - Anisotropie

KW - Korrelationen

KW - Inklusion Model

KW - Defekt Model

KW - Logs

M3 - Doctoral Thesis

ER -