Renate Pechnig

Mobile NMR for porosity analysis of drill core sections

We apply a novel mobile nuclear magnetic resonance (NMR) scanning system, the NMR-MOUSE? (NMR-MOUSE (Nuclear Magnetic Resonance Mobile Universal Surface Explorer) is a registered trademark of RWTH Aachen University), for measuring porosity of geological drill core sections. The NMR-MOUSE? is used for transverse relaxation measurements on water-saturated core sections using a CPMG sequence with a short echo time. A regularized Laplace-transform analysis by the UPEN program yields the distribution of transverse relaxation times. The signal amplitudes and the distribution integrals correlate directly with the porosity of the cores, in spite of the influence of diffusion in the strong field gradient of the NMR-MOUSE?, which is discussed. The method is particularly attractive because it neither requires a volume calibration nor the samples to be machined to fit the coil, and because the device is mobile and particularly attractive for field use such as on logging platforms and research vessels.

Rock classification based on resistivity patterns in electrical borehole wall images

Electrical borehole wall images represent grey-level-coded micro-resistivity measurements at the borehole wall. Different scientific methods have been implemented to transform image data into quantitative log curves. We introduce a pattern recognition technique applying texture analysis, which uses second-order statistics based on studying the occurrence of pixel pairs. We calculate so-called Haralick texture features such as contrast, energy, entropy and homogeneity. The supervised classification method is used for assigning characteristic texture features to different rock classes and assessing the discriminative power of these image features. We use classifiers obtained from training intervals to characterize the entire image data set recovered in ODP hole 1203A. This yields a synthetic lithology profile based on computed texture data. We show that Haralick features accurately classify 89.9% of the training intervals. We obtained misclassification for vesicular basaltic rocks. Hence, further image analysis tools are used to improve the classification reliability. We decompose the 2D image signal by the application of wavelet transformation in order to enhance image objects horizontally, diagonally and vertically. The resulting filtered images are used for further texture analysis. This combined classification based on Haralick features and wavelet transformation improved our classification up to a level of 98%. The application of wavelet transformation increases the consistency between standard logging profiles and texture-derived lithology. Texture analysis of borehole wall images offers the potential to facilitate objective analysis of multiple boreholes with the same lithology.

The Den Haag Geothermal District Heating Project - 3-D Models for Temperature Prediction.

In the frame of the „ Den Haag Zuidwest“ geothermal district heating system a deep geothermal installation is projected. The target horizon of the planned doublet is the „ Delft sandstone“, an upper Jurassic sandstone layer, which has been extensively explored for oil- and gas reservoirs in the last century.