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Fourth EAGE Borehole Geology Workshop
- Conference date: September 27-29, 2021
- Location: Online
- Published: 27 September 2021
21 - 22 of 22 results
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Advanced Mud Logging application to Shallow Geothermal
By K. BondabouSummaryWith recent trends in global energy mix and sustainable development geothermal energy is gradually growing in its application. Both shallow and deep geothermal energy systems are contributing to this, learning from the technological advances from fossil fuel industry. This work presents a case study from Parisian basin, where shallow slim-holes were drilled at different inclination to tap the geothermal energy for local urban consumption. Drill-cuttings were studied and analysed to understand the lateral variations in the clay-type and its impact on the drilling practices. No measurement while drilling (MWD) data was acquired. Only the drill-cuttings were analysed. DRIFTS provided mineralogy and clay profile that allowed to spot smectite intervals. Digital imaging helped to correlate the formation-tops across the study-wells. Cuttings collected helped understand any possible losses and drilling events. Drilling and completion of shallow wells planned for urban geothermal energy consumption could run into problems and shoot up the cost if mineralogy variations and its impact are not analysed on a wider scale. This study from a Paris suburb shows the scale and magnitude of lateral variability in geology and the need to perform cutting-based study for such geothermal wells.
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Advanced spectrum analysis of image logs for petrophysical characterisation of laminated turbiditic reservoirs an innovative workflow
Authors M.T. Galli, R. Berto and M. PirroneSummaryA novel approach has been developed to provide the high resolution petrophysical characterisation of thin layered, rich-in-silt reservoirs, where conventional formation evaluation cannot honour gas production rates. The approach is based on the integration of micro-resistivity image logs, Nuclear Magnetic Resonance (NMR) and dielectric dispersion measurements, into a fit-for-purpose workflow to provide quantitative evaluation of high-resolution porosity and water saturation profiles. The analysed reservoirs, Pleistocene sequences of thin-to-very-thin fine sands, characterised by grain size variations and silty thin beds, showed high water saturation profiles even in producing intervals. Besides, operational criticalities often prevented the acquisition of a complete suite of logs in every well. The need for a strong objectivity in the interpretation and the bias of time constraints lead to the use of automatic image processing techniques for the analysis of image logs and of supervised learning techniques for the propagation of the results. A new integrated method based on the definition of the petrophysical model in key wells and its propagation to target wells by means of machine learning techniques provided suitable solutions. The petrophysical model, evaluated from dielectric dispersion logs, was reproduced through the integration of spectrum analysis of high-resolution resistivity images and core calibrated NMR logs.
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