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Accurately estimating the dolomite content in carbonate rocks is crucial for optimizing oil and gas exploration and production strategies. Hyperspectral techniques for estimating dolomite content have advantages in terms of efficiency, cost-effectiveness, and non-destructiveness compared with traditional laboratory methods. Despite the abundance of hyperspectral data, feature selection and extraction remain challenging. In this study, hyperspectral data collected from surface outcrop in the field using the analytical spectral device (ASD) were applied to construct model for estimating dolomite content. Firstly, the data were preprocessed via outlier analysis and continuum transformation. Next, a hybrid approach integrating spectral knowledge with machine learning was proposed and applied to facilitate efficient and precise feature selection of the hyperspectral data; in this approach, preliminary screening based on spectral knowledge is followed by further hyperspectral data feature selection using a random forest algorithm. The selected features were then combined using a support vector regression algorithm to obtain the estimation model. Finally, the accuracy of the model was evaluated using the hyperspectral data from field outcrop samples. To further verify the effectiveness of this method, various combinations of eight input variables and four machine learning algorithms were compared. Among all combinations, our model achieved the highest accuracy with a test R² value of 0.91 and a root-mean-square error of only 0.122. The proposed method is practical and efficient and provides precise quantitative data for field geologists to identify the mineral distribution in outcrops. Thus, our method provides robust support for understanding reservoir characteristics and has significant practical value in geological surveys and mineral exploration. [ABSTRACT FROM AUTHOR]

Across Germany, coal-fired power plants will be shut down not later than 2038. In the Rhine-Ruhr area of western Germany, their waste heat is the main supply for one of Europe's largest district heating networks. Because of the projected shutdown of coal-fired power plants, sustainable alternatives must be implemented. This paper evaluates the hydrothermal potential of Devonian carbonates. A depofacies and mineralogy model is proposed and discussed. Tentative conclusions are drawn based on petrophysical laboratory tests. Extrapolating the thermal and hydraulic rock properties into geothermal reservoir depths offers constraints for associated reservoir simulations. This task applies existing and derived extrapolation equations taking local pressure and temperature gradients into consideration. The change from a non-linear to a linear development at the critical crack-closure pressure provides evidence regarding the petrophysical in-situ reservoir conditions. Results show a positive effect of increased dolomite volumes on reservoir properties. The spatial distribution of fracture networks significantly affects the geothermal reservoir potential, whereas the impact of regionally distributed depofacies variations is moderate. The critical crack-closure pressure equals 40 MPa for limestones and 60 MPa for dolomitic limestones, as well as dolostones, representing depths of approx. 3.6 and 5.4 km, respectively. At depths of 6 km, non-linear and linear extrapolation principles must be applied accordingly. At that depth, the thermal conductivity decreases by 14 to 20% compared to the outcrop values, depending on the sample category. The equivalent decrease in porosity amounts to one to two orders of magnitude. The permeability decrease equals three to four orders of magnitude. The petrophysical values of outcrop samples discussed here plot, within the error range, in the same domain as those of the Malm carbonates in the Munich area. Results are considered encouraging for those concerned with the sustainable transition of the district heating network in the Rhine-Ruhr area. Side-strands of regionally important fault systems, often characterised by hydrothermal dolomitisation, combine tectonic and petrophysical aspects that are advantageous and highly relevant for hydrothermal operations. • Devonian Massenkalk carbonates exhibit promising geothermal reservoir properties. • Fracture peculiarities are crucial for the hydraulic reservoir potential. • Dolomitisation further enhances the reservoir potential of Massenkalk carbonates. • Pressure effect on hydraulic properties is crucial for extrapolation models. [ABSTRACT FROM AUTHOR]