There are currently around 30 operational geothermal "doublets" in the Netherlands, consisting of an injector and a producer. These projects primarily provide heat for greenhouse horticulture, with some also supplying heat to homes and buildings. The Dutch geothermal sector is experiencing significant growth, approximately 23 installations collectively produced 7.49 PJ of geothermal energy in 2024, and three new installations became operational.
The factors that enable Geothermal projects in the Netherlands are: - Heat supply: Subsurface resources delivering the geothermal power - Heat demand: availability of customers - Publicly available data: the Dutch Technical advisor to the regulator, TNO, maintains active websites with all relevant data on all mining activities including oil and gas and geothermal - New data availability: The State Energy Company EBN is drilling several Geothermal exploration wells and has acquired and interpreted hundreds of 2D seismic lines, as part of the SCAN programme, which will be publicly available. - Tools: TNO has made standard tools available, like doublet calc for calculation of geothermal power - Process: The license award process is clear and standardized - Financial incentives: Geothermal projects can apply for an SDE++ subsidy through the above standardized process as part of the license applications

The presentation the success factors will be discussed in more details - with examples of work that PanTerra performed - in addition PanTerra is also involved in the work on the SCAN exploration wells, which is the topic of another presentation in this conference.

The publicly funded SCAN program (Seismic Campaign Geothermal Heat Netherlands) entails seismic surveys as well as the completion of eight data acquisition wells. This research aims to provide a regional dataset for the mapping of the geothermal potential in the Dutch subsurface. The Lower Permian (‘Rotliegend’) Slochteren Formation is the most important source for deep geothermal heat in the Netherlands, and the most extensively cored reservoir within the program. In the Dutch onshore, the 50-250 m thick Slochteren Formation comprises dry aeolian, rarely fluvial sediments with high matrix brine permeability. Detailed core evaluation of the new SCAN wells including CoreDNA screening, SCAL, sedimentological core logging and petrographic study enabled the distinction of reservoir rock type zones, which are linked to sedimentary facies. Aeolian dune deposits have the highest flow potential over aeolian sandflat and fluvial channel facies because of the very low clay content and a moderate impact of mechanical compaction. Diagenetic cements and faults including deformation bands can locally overprint reservoir quality but have limited control on the spatial properties of the reservoir overall. The reservoir zonation imparted by sedimentary facies is further recognised after core-to-log integration (core analysis and log-derived NMR T2) and flow profiles derived from injection tests. As a result, the geothermal potential of the Slochteren Formation can be underpinned by realistic transmissivity values, providing a de-risked dataset for future geothermal installations.

As the demand for renewable energy rises, Germany faces a critical need to develop and utilize geothermal energy. An important initiative addressing this is the WärmeGut project, supported by the Federal Ministry for Economic Affairs and Energy (Bundesministerium für Wirtschaft und Energie). The project prioritizes evaluating the potential of shallow to medium-depth geothermal resources in the Tertiary sandstones of the North German Basin (NGB).

The Tertiary succession of the NGB is characterized by alternating sandstone and shale intervals. This study aims to predict the presence and thickness of sandstone bodies within this succession by analyzing downhole gamma ray (GR) logs. We hypothesize that sandstone intervals, having higher sedimentation rates than shale, correspond to higher frequency components in GR signal records. To test this, we analyzed GR logs from three biostratigraphically controlled sites spanning the marginal to basinal regions of the NGB. Wavelet analysis was employed to investigate the frequency-depth dependence of the GR signals, revealing consistent patterns associated with sandy intervals. These findings form the basis of a predictive model for sandstone occurrence and thickness in areas lacking detailed lithological or cutting data. The model offers a valuable tool for stratigraphic interpretation, correlation and resource assessment in data-limited parts of the basin.

Pore pressure is a key quantity for safe and economically viable geothermal development. Good knowledge about the pore pressure prior to drilling can help reduce drilling related problems. Pore pressure indicators (PPIs)­­—such as drilling mud weights, kicks, and wireline formation tests—from nearby, previously drilled wells are a valuable data source for improving this knowledge. An issue with PPIs is their varying degree of uncertainty, with the most ubiquitously available PPIs from offset wells having weaker ties to the actual pore pressure than the sparse high-quality measurements. To analyze this diverse set of data, we propose a Bayesian framework for pore pressure prediction from offset wells.

Our method is based on continuous underground domains (e.g., stratigraphic layers) in which pore pressure is governed either by constant vertical effective stress, constant overpressure with reference to a hydraulic potential, or hydrostasy. All PPI data within such a domain measure the same pore pressure state. Furthermore, all data are assumed to be drawn from measurement distributions parameterized by this state. We propose—reflecting qualities of the respective measurement processes—three simple measurement distributions for maximum mud weight, kick, and wireline formation test data. Our Bayesian analysis then derives posterior distributions of pore pressure within the target well depth interval covered by a domain from all offset well PPIs within the same domain. In the planning stage of a well, these posterior distributions indicate with which probability pore pressure may fall into certain ranges with depth. Mud weight can then be planned accordingly.