Hundreds of geothermal wells have been drilled in Hungary to exploit Pannonian Basin sandstones for district heating, agriculture, and industrial heating projects. Most of these sites suffer from reinjection issues, limiting efficient use of this vast geothermal resource and imposing significant extra costs for the required frequent workovers and maintenance. To better understand the cause of this issue requires details of reservoir rock porosity, permeability, and mineralogy. However, publicly available data for the properties of reservoir rocks at geothermal project sites in Hungary is typically very limited, because these projects often omit or limit data acquisition. Many hydrocarbon wells in the same rocks are more extensively documented, but their core, log, or production data are typically decades old and unavailable in the public domain. Furthermore, because many Pannonian sandstone formations are poorly consolidated, coring was always limited and the collected core often unsuitable for conventional analysis, only small remnant fragments typically being available from legacy hydrocarbon wells. This study aims to reduce this data gap and to showcase methods to derive reservoir properties without using core for flow experiments. The methods are thin-section analysis, XRD analysis and mercury intrusion porosimetry, and X-CT scanning followed by numerical flow simulation. We validate our results using permeability data from conventional production testing, demonstrating the effectiveness of our method for detailed reservoir characterization and to better constrain the lateral variation in reservoir properties across the Pannonian Basin. By eliminating the need for expensive bespoke coring to obtain reservoir properties, such analysis will contribute to reducing the capital cost of developing geothermal energy projects, thus facilitating decarbonization of global energy supply.
A R T I C L E I N F O Keywords: Cyclic soft stimulation Multi-stage hydraulic stimulation Zonal isolation Realtime seismic monitoring Fluid injection induced seismicity Adaptive traffic light system enhanced geothermal systems (EGS) A B S T R A C T Reykjavik is almost entirely heated by geothermal energy. Yet, recent growth of the city significantly increased the heat demand. Past experiences in Iceland's capital region showed that hydraulic stimulation of existing geothermal wells is suited to improve hydraulic performance and energy supply. However, fluid injection may also trigger felt or even damaging earthquakes, which are of concern in populated areas and pose a significant risk to stimulation operations. Consequently, soft stimulation concepts have been developed to increase geothermal well performance while minimizing environmental effects such as induced seismicity. In a demonstration project of hydraulic soft stimulation in October 2019, more than 20.000 m 3 of water were injected into well RV-43 in Reykjavik in multiple stages and with different injection schemes. The hydraulic performance of the well was improved without inducing felt seismicity. An a priori seismic risk assessment was conducted and for the first time the risk was continuously updated by an adaptive traffic light system supported by a sophisticated realtime microseismic monitoring. Our results confirm that it is possible to improve the performance of geothermal wells in Reykjavik and worldwide with acceptable technical, economic, and environmental risks. Here we provide an overview of the entire stimulation project including site description, stimulation design, zonal isolation, logging, seismic risk assessment and mitigation measures, realtime seismic, hydraulic and chemical monitoring, and stimulation results and challenges.
Coda Wave Interferometry (CWI) is a highly sensitive monitoring technique built on the sensitivity of elastic coda waves to small changes in a diffusive medium. However, a clear connection between the physical processes involved in the evolution of the medium and the time changes observed by CWI has not been clearly described yet. Here, we quantify the impact of elastic deformation on CWI measurements at laboratory scales. We compare experimental results from wave scattering measurements during a uniaxial compression test to those of a numerical approach based on the combination of two codes (SPECFEM2D and Code_Aster), which allows us to model wave propagation in complex diffusive media during its elastic deformation. In both approaches, the reversible time delays measured between waveforms increase with the elastic deformation of the sample. From the numerical modeling, we gain insight to the relative contributions of different physical effects on the CWI measurement: local density changes from volumetric strain, the deformation of scatterers, and acoustoelastic effects. Our results suggest that acoustoelastics effects related to nonlinear elasticity are dominant.
A hydraulic stimulation was carried out on a granodiorite reservoir in an enhanced geothermal system in August 2017 in Pohang, Korea. Water injected into the 4.2 km deep PX-1 well contained c. 330−360 mg/L sulphate, with a negative δ34S. The resulting flowback water became more saline with time, with sulphate and chloride concentrations and dissolved sulphate δ34S all increasing. Compared with conservative advective-dispersive and mixing models, the flowback contained surplus sulphate with an elevated δ34S. The PX-1 reservoir fluid is saturated with respect to anhydrite at downhole temperatures and pressures. Dissolution by injected surface water of secondary anhydrite along fracture surfaces, most likely with elevated δ34S reflecting the reservoir fluid, is likely to have resulted in an excess of 34S-enriched sulphate in the flowback fluid. An alternative hypothesis involving oxidation of pyrite is also plausible but is stoichiometrically inadequate to account for the observed sulphate excess, and unlikely from a sulphur isotopic perspective. This analysis thus contributes to the evidence for water-rock reactions during stimulation of the Pohang granodiorite.
This public report entitled Risk Governance Strategy corresponds to the Deliverable 3.3 of the European DESTRESS project. This comprehensive report is done on the framework of the WP3 dealing with “Risk management workflows for deep geothermal energy”. The main objective of this sub-task was to analyze the public uptake of geothermal energy and geothermal projects in various socio-economic conditions in Europe. Several countries and organizations were involved in this study: the University of Strasbourg (UoS) and the company Electricity of Strasbourg (EGS) in France, the Netherlands Organisation for applied scientific research (TNO) in the Netherlands, the University of Glasgow (UoG) in the United Kingdom, the Swiss Federal Institute of Technology in Zurich (ETH) in Switzerland. This report is structured in six chapters. The first chapter provides a brief overview of the state of the art regarding EGS technologies and the risks involved, followed by a summary of the orientations of social science research on deep geothermal energy. The second chapter presents the different case studies on which the work carried out under WP 3.3 of the DESTRESS program has focused, with references to national contexts. Chapters 3 to 5 present the work and results of the research carried out under the DESTRESS program according to three main subjects, media studies, research on public perception of deep geothermal energy, and work on public engagement. The last chapter discusses different issues - the fate of rooted and unrooted projects, the dynamics of social movements, the role played by the state and local authorities - and ends with a series of recommendations.
This chapter presents the latest trends of deep geothermal energy (DGE) in Switzerland. The country played a pioneering role in the development of low-enthalpy DGE. But setbacks in early flagship projects have slowed these efforts. Since then, the development of DGE in Switzerland has been characterised by a plurality of technologies, actors and institutional frameworks. We examine how federalism and direct-democracy has shaped this plural landscape and how it influences current DGE development. The chapter first introduces the institutional and political setting of DGE, as well as the main actors involved. Then, focusing on specific cases, the chapter presents different forms of public engagement that are shaped by the variety of actors involved, as well as the regulatory frameworks and cultural backgrounds. The results underline the importance of taking into account the social context of DGE projects. Furthermore, the results highlight that such a context is dynamic and responsive to the communication and public engagement strategies set up by DGE project operators. In conclusion, using Switzerland as an example, we show that operators must develop functional-dynamic siting, communication and public engagement procedures.
By looking at deep geothermal energy in Switzerland, this article illustrates how innovation pathways in federal countries take entangled forms between top-down and bottom-up. The Swiss federal government presents deep geothermal energy as an important technology to decarbonize electricity production. Setbacks in early projects have slowed these efforts. Despite strong policy incentives from the federal government, no electricity is being produced from geothermal projects in Switzerland in 2019. Based on four case studies, we analyze how some cantons and cities have taken different pathways: Rather than implementing federal objectives, they favor heat production instead of electricity generation. The relative success of these initiatives led federal authorities to modify their approach to promoting geothermal energy. This study shows that federal mechanisms and instruments alone are not enough to make energy infrastructures acceptable locally. To learn from bottom-up experiences and adapt federal policies to local reality, better coordination between the federal and subnational levels is needed.
Flowback water from the 4215 m deep (True Vertical Depth) PX-1 borehole, following the August 2017 hydraulic stimulation of a granodiorite geothermal reservoir in Pohang, South Korea, was monitored for a suite of physicochemical, chemical and isotopic parameters. The results provide unique insights into mixing processes, fluid evolution and rapid water-rock interaction in a deep geothermal system. Injected water for stimulation was relatively fresh, oxidising surface water, with temperature 29.5 °C and pH c. 6.5. The flowback water showed an increasing content of most solutes, with the evolution conforming to an exponential ‘flushing’ model for conservative solutes such as chloride. Flowback water became progressively Na–Cl dominated, with a circumneutral pH (7.1) and negative oxidation-reduction potential (c. −180 mV). Some solutes (including, Na, K and Si) increased more rapidly than a flushing model would suggest, implying that these had been acquired by the flowback water due to mineral hydrolysis. Stable isotopes of O and H indicate that initially meteoric waters have undergone geothermal oxygen isotope exchange with minerals. Evolution of redox species in recovered water suggests progressively oxidising zonation around the injection borehole in an otherwise reducing reservoir. Rapidly increasing silica concentrations in flowback water suggests extensive quartz dissolution and indicated a reservoir temperature of up to 169 °C. This lends plausible, if equivocal support to the hypothesis that quartz dissolution by injection water may have contributed to triggering movement on the pre-stressed fault associated with the November 2017 Mw 5.5 Pohang earthquake.
Samples of flowback water from a 4.3 km deep geothermal borehole in granite (Pohang, South Korea) were collected following a period of hydraulic stimulation by injection of surface water. Electrical conductivity, temperature and water chemistry of the flowback water were measured. To a first approximation, the data conform closely to a simple 'mixing tank' model, with an exponential trend between two end members: an initial injected surface water to a more brackish 'resident groundwater' composition. Significant deviation from the 'mixing tank' trend would be an indication of significant recent water-rock interaction or other anomalous factors. Such a deviation can tentatively be seen in Na + /Cl-data, especially between 88 and 200 m 3 flowback (2.8 to 8.8 hr).
The geothermal doublet at Mezőberény in SE Hungary has suffered from poor productivity and injectivity since it began operation in 2012. The injection and production wells of the doublet are near vertical and have ~400 m production interval, consisting of few thin sandstone bodies in a shale matrix. Previous studies have considered chemical factors, such as scaling and clay mobilisation, as possible causes of injectivity and productivity limitations. So far, however, the possible impact of poor hydraulic connectivity on these limitations has not been considered. Therefore, a geological model describing the geometry of the sandstone bodies in the aquifer and its net sandstone content have been derived in this study. The model is based on a geological dataset from the Békés Basin including core samples, 2D seismic lines and Gamma Ray logs of nearby petroleum wells. Dozens of aquifer realisations of this model were generated, which capture the sedimentary architecture of the aquifer utilising an object-based modelling approach. For each realisation, the volume of sandstone bodies that both wells intersect was calculated. We found that only a small percentage of the total sandstone volume in the realisations was intersected by both wells. This indicates that the net aquifer volume is most likely much smaller than the net-sandstone content of 11% that was derived from the well logs. Therefore, these results suggest that it is likely that hydraulic connectivity is poor between the injection and production well in the doublet, limiting injection and production rates. In addition, our results highlight the importance of sedimentary facies analysis as a tool for successful exploitation of geothermal resources
The Klaipeda Geothermal Demonstration Plant (KGDP), Lithuania, exploits a hypersaline sodium-chloride (salinity c. 90 g/L) groundwater from a 1100 m deep Devonian sandstone/siltstone reservoir. The hydrogen and oxygen stable isotope composition is relatively undepleted ( δ18O=c. -4.5‰), while the δ³⁴ S is relatively “heavy” at +18.9‰. Hydrochemical and isotopic data support the existing hypothesis that the groundwater is dominated by a hypersaline brine derived from evapoconcentrated seawater, modified by water-rock interaction and admixed with smaller quantities of more recent glacial meltwater and/or interglacial recharge. The injectivity of the two injection boreholes has declined dramatically during the operational lifetime of the KGDP. Initially, precipitation of crystalline gypsum led to a program of rehabilitation and the introduction of sodium polyphosphonate dosing of the abstracted brine, which has prevented visible gypsum precipitation but has failed to halt the injectivity decline. While physical or bacteriological causes of clogging are plausible, evidence suggests that chemical causes cannot be excluded. Gypsum and barite precipitation could still occur in the formation, as could clogging with iron/manganese oxyhydroxides. One can also speculate that inhibitor dosing could cause clogging of pore throats with needles of calcium polyphosphonate precipitate.
Abstract Coda wave interferometry (CWI) is a high-resolution technique that aims at tracking small changes in a diffusive medium from the time correlation of seismic waveforms. CWI has been widely used in recent years to monitor the fine-scale evolution of fault zones and more recently of deep reservoirs. However, to provide a quantitative interpretation of the reservoir, direct modeling of physical effects like the influence of temperature on seismic wave scattering is required to investigate temperature effects from measurements of velocity changes. Here, we propose to quantify the impact of thermo-elastic deformation on CWI measurements by comparing experimental results obtained from a previous study on Westerly Granite to a numerical approach based on two combined codes (SPECFEM2D and Code_Aster) for modeling wave propagation in complex media during thermo-elastic deformation. We obtain two major results. First, we show that multiple reflections on the boundaries of our simplified numerical sample reproduce well the wave scattering properties of the experimental granitic sample characterized by a complex mineral assembly and a large set of microcracks. We based our comparison on the wave diffusion model that describes both the experimental and numerical samples (similarity in energy density function and mean free path). We also show that both samples share a similar thermo-elastic behavior, but only after the second heating and cooling cycle. Second, the stretching technique used for CWI measurements on both samples reveals reversible time shifts correlated with the thermo-elastic deformation of the sample. However, the influence of thermo-elastic deformation is different between our numerical proxy and the experimental sample. We discuss the role of irreversible deformation (e.g., microcracking) for the observed discrepancy by introducing temperature dependence of elastic moduli in the model. These results suggest that there are open perspectives to monitor thermal strain in geothermal reservoirs using CWI.
Earthquake exposure describes the assets that are exposed to seismic activity and are susceptible to be damaged. In seismic risk applications, it mostly refers to the residential and commercial building portfolios, although in general may also include transport infrastructure and lifelines. Providing an efficient description of a complex urban environment in terms of the structural characteristics of buildings related to their seismic vulnerability is challenging, considering the variety of building practices, materials and configurations. A common approach entails the use of pre-defined building typologies, but this may introduce a bias in the resulting models. Faceted taxonomies have been recently introduced to provide a standardised description of buildings using a rich set of basic attributes, but cannot be used directly for risk-related applications. We argue that a bottom-up approach to exposure modelling might prove instrumental in increasing the quality and reliability of risk assessment, and propose hereby a novel score-based methodology to define and assign building classes to unclassified buildings in a sound and transparent way. The approach can be adopted for standard building classifications as well as for original typologies that may be more efficient in capturing the specific features of the building stock. The proposed methodology efficiently decouples the collection of buildings observations, typical of surveying activities, from the assignment of risk-aimed building classes, and provides a useful tool to practitioners and engineers involved in large-scale earthquake risk assessment. The proposed methodology has been exemplified with a building portfolio collected in France near the geothermal plant of Soultz-sous-Forêts, and is used to rapidly characterise the seismic exposure of a built environment for induced seismicity applications.
Earthquakes, despite being a mostly natural phenomenon, may also be induced by a wide range of anthropogenic activities such as mining, fluid injection and extraction, hydraulic fracturing and geothermal reservoir processes. In recent years, the occurrence of induced and triggered seismicity and its potential impact on the built environment have heightened both public concern and regulatory scrutiny, motivating the need for an integrated risk management framework. Non-standard monitoring approaches provide valuable tools for mitigating the risk associated with earthquakes. These solutions include the use of advanced sensors and the implementation of performance-based rapid response systems for infrastructure, as well as monitoring the structural response of buildings and infrastructure in real time. Such technical solutions can be further used for validating damage forecasts determined by probabilistic approaches. The goal of this study is to establish a performance-driven monitoring system for induced seismicity. For this purpose, it is necessary to integrate analytical fragility curves in real time. These fragility curves can be derived by simplified vulnerability models that require input obtained from advanced exposure-monitoring techniques. Considering the case of induced seismicity, this also requires the expected damage to refer to non-structural components. Hence, the derived fragility curves are based on the non-structural damage criteria of typical residences. Therefore a new approach is presented for defining analytical fragility curves of traditional or historic masonry structures, which can be found in large numbers near the geothermal platforms considered in this work.
The Mw 5.5 earthquake which struck South Korea on November 2017 was one of the largest and most damaging event in this country since the last century. Its proximity to an Enhanced Geothermal Systems site, where high pressure hydraulic injection had been performed during the previous two years, raises the possibility that this earthquake was anthropogenic. If so, it would be the largest and most damaging earthquake ever to have been associated with deep geothermal activity, making it a potential 'game changer' for the geothermal industry worldwide. Here we combine seismological and geodetic analyses to characterize the main shock and its aftershocks, constrain the geometry of this seismic sequence and shed light on its casual factors.
The monitoring of induced seismicity is a common operation in many industrial activities, such as conventional and non-conventional hydrocarbon production or mining and geothermal energy exploitation, to cite a few. During such operations, we generally collect very large and strongly noise-contaminated data sets that require robust and automated analysis procedures. Induced seismicity data sets are often characterized by sequences of multiple events with short interevent times or overlapping events; in these cases, pick-based location methods may struggle to correctly assign picks to phases and events, and errors can lead to missed detections and/or reduced location resolution and incorrect magnitudes, which can have significant consequences if real-time seismicity information are used for risk assessment frameworks. To overcome these issues, different waveform-based methods for the detection and location of microseismicity have been proposed. The main advantages of waveform-based methods is that they appear to perform better and can simultaneously detect and locate seismic events providing high-quality locations in a single step, while the main disadvantage is that they are computationally expensive. Although these methods have been applied to different induced seismicity data sets, an extensive comparison with sophisticated pick-based detection methods is still missing. In this work, we introduce our improved waveform-based detector and we compare its performance with two pick-based detectors implemented within the SeiscomP3 software suite. We test the performance of these three approaches with both synthetic and real data sets related to the induced seismicity sequence at the deep geothermal project in the vicinity of the city of St. Gallen, Switzerland. © The Author(s) 2018. Published by Oxford University Press on behalf of The Royal Astronomical Society.
The DBSCAN (Ester et al. 1996) is a popular data-clustering algorithm. The algorithm processes in arbitrary order every point Pk in the dataset, skipping every point already assigned to a cluster by the previous iterations. If at least N points are within distance R from Pk (including it), then Pk is called a Core Point and the points within distance R from a Core Point are said to be directly density-reachable. If Pk is not a Core Point it is simply skipped, otherwise a new cluster is defined with Pk as first element. The cluster is then connected to all the density-reachable points from Pk, which are the points connected to Pk through a path in which each point is directly density-reachable from the previous one. Those must be either Core Points or, if less than N points are found within distance R, Border Points. The latter can happen only at the last point in a density-reachable path. Once DBSCAN finishes processing the dataset each point either belongs to a specific cluster (i.e. Core or Border point) or it is an outlier. The first cluster property we can derive from the above is that if a point is density-reachable from any one in the cluster then it must be part of the cluster too. However density-reachability is not a symmetric property, as Border points are density-reachable by core points but not vice versa. Thus Ester et al. (1996) defines the density-connected symmetric relation: point p is density-connected to a point q if there is a point o such that both, p and q are density-reachable from o. This gives us the second cluster property: all points within the cluster are reciprocally density-conneted.
Fluid flow in the Earth's crust is controlled by pore-connectivity over scales from mm to km. Micro-scale pore-connectivity structures can appear as fractures on the meso-scale, and at macro-scales they can appear as displacement faults. Whatever their appearance, however, pore-connectivity structures are characterized by a single spatial correlation process attested by well-log spatial fluctuation systematics over the cm to km scale range. The crustal spatial correlation process is seen as 1/k power-law scaling of well-log Fourier power-spectra, S(k) ~ 1/k, over five decades of spatial frequency k from 1/km to 1/cm. Because pore-connectivity structures are due to random processes, they are inhomogeneously distributed in space. Power-law scaling spatial correlation means that one cannot meaningfully average pore-connectivity and associated permeability structures within or across geological layers. The effect of spatial correlation from 1/k scaling is apparent in different data related to fluid flow: well-logs, well-productivity, and well-core. Relevant accessible datasets have been analysed from different geothermal fields in the world, e.g. Indonesia, New Zealand, Mexico, Germany and Lithuania. Measurements of well-core samples show that porosity spatially correlates with the logarithm of permeability. Where porosity is greater, permeability is very much greater due to strongly increased pore-connectivity leading to increased fluid flow. The combined effect of increased porosity and very much increased permeability results in lognormally distributed well productivities, as observed in crustal fluid flow systems across the world. Lognormality is particularly important in convective geothermal fields, where only very few wells give the necessary high flow output while the better part yielding low to moderate outputs are commercially useless. These natural fluid flow pathways can be altered by effects of field operations. Physical, chemical and biological processes can trigger blocking of natural flow structures and lead to exponentially declining injection curves. Small-scale changes in grain-scale pore-connectivity can lead to a huge negative influence on large-scale sustainability of geothermal systems. That is, strong negative effects caused by field operations flow can be based on the grain-scale connectivity nature of fluid flow in geological media. Such changes can be induced by chemical processes in the reservoir and the plant (precipitation, corrosion). Also, biological reactions can either directly affect the physical flow structure (biofilm) or interact with chemical reactions (triggered precipitation or corrosion). Therefore, it is important to consider the interaction of different processes that occur in geothermal reservoirs. These processes have been observed and analysed at field data from a geothermal plant in Lithuania. In particular, the observed injectivity decline for a low enthalpy heating plant provides an example of pore-connectivity reduction mechanisms during standard geothermal operations. Both understanding of location and structure of natural fluid pathways and how they can be altered during field operations are of greatest interest for sustainable reservoir management.
Earthquakes, despite being a mostly natural phenomenon, may also be induced by a wide range of anthropogenic activities such as mining, fluid injection and extraction, and hydraulic fracturing. In recent years, the occurrence of induced seismicity and its potential impact on the built environment have heightened both public concern and regulatory scrutiny, motivating the need for a framework for the management of induced seismicity. Earthquake early warning systems, coupled with non-standard monitoring approaches, provide valuable tools for mitigating the risk associated with earthquakes. These solutions might include the use of advanced sensors and the implementation of performance-based on-site early warning and rapid response systems for infrastructure, as well as monitoring the structural response of buildings and infrastructure in real time. Such technical solutions can be further used for validating damage forecasts determined by probabilistic approaches. The goal of this study is to establish a monitoring and early warning system for induced seismicity. For this purpose, it is necessary to integrate analytical fragility curves in real time. These fragility curves can be derived by simplified vulnerability models that require input obtained from advanced exposure-monitoring techniques. Considering the case of induced seismicity, this also requires the expected damage to refer to non-structural components. Hence, the derived fragility curves are based on the non-structural damage criteria of typical residences. We therefore present a new approach for defining analytical fragility curves of traditional or historic masonry structures, which occur in large numbers near the geothermal platforms considered in this work.
The ultimate objective of any effective program for the management of induced seismicity in geothermal platforms must be to limit the consequent seismic risk. Towards this goal, the seismic hazard, the exposure and the vulnerability of the considered structures should be carefully considered. Hazard is defined by a measure of the expected ground shaking and the associated probability of exceedance. Exposure refers to a listing, or a geo-statistical model, of the assets susceptible to be damaged and their structural features. Vulnerability is finally encoding the relationships between ground shaking and resulting damage for the different exposed elements. In applications related to induced seismicity particular care has to be devoted to the modeling of exposure and vulnerability when expected consequences mostly consist of non-structural damage to buildings and annoyance to the affected population. Furthermore, the assessment of risk should be carried out in a rapid, non-invasive manner, in order not to raise alarm in the affected communities, often situated in areas with little or no historical seismicity. We propose an advanced framework for risk assessment, monitoring and early warning, which is custom tailored to the specific risk-reduction requirements of geothermal plants. This solution entails the use of a new generation of smart sensor devices which implement a performance-based on-site early warning and rapid response system for specific infrastructure, and can be used also for real-time monitoring of the structural response of buildings and infrastructure. In particular, after reviewing the protocols already present in literature, a novel approach is proposed for analytically modeling fragility curves for the most relevant building types. This approach has been developed for the seismic demands generally imposed upon linear and slightly nonlinear systems of single and multiple degrees of freedom which is the case for induced seismicity demands. Within this framework based on the forecasted performance level (i.e. the expected damage to the specific structure), or according to pre-defined thresholds on the incoming ground motion, a feedback may be promptly sent to plant managers and local stakeholders.
Geochemistry is the study of the chemical composition of the materials found in the subsurface of the earth, and of the reactions that they undergo. In the context of geothermal engineering, we typically consider the geochemical and mineralogical composition of the reservoir rocks or sediments (primary geochemistry). We also consider the precipitates, scales and secondary minerals that may form in reservoir, wells or at the surface in heat exchangers and plant as a result of the operation of the geothermal scheme (secondary geochemistry). Hydrochemistry is the study of the chemical composition of natural waters. Many deep geothermal fluids have rather unusual hydrochemical characteristics: they can be highly saline, very reducing or have high contents of dissolved gases (and the composition of these dissolved gases can be very important in many contexts). Also of interest is the composition of waters, acids and other fluids which are injected into the geothermal reservoir for purposes of hydraulic or chemical stimulation. To successfully run a geothermal plant, the geothermal engineers need to understand the chemical interactions between fluids, rock minerals and gases during the stimulation and operation of a geothermal system. Therefore, the abrupt temperature changes that the fluids and rocks may undergo have to be taken into account. In particular, hydrochemists will consider how the compositions of the fluids, minerals and gases change throughout the lifetime of a geothermal site, in order to understand the chemical processes taking place in the reservoir. This will allow hydrochemists to evaluate whether these changes are likely to lead to the formation of secondary minerals, permeability decreases, scaling or clogging of the reservoir or of wells, or whether they may lead to permeability enhancement. This information must successfully be communicated to the geothermal engineers as clear recommendations for the stimulation or operation of the geothermal system. Full text available at http://www.destress-h2020.eu/en/Best-Practices/Geochemistry-and-Hydrochemistry/
Microseismic monitoring is common operation in different georesources related industrial activities, such as oil&gas and mining operations or geothermal energy exploitation. In microseismic monitoring operations we generally deal with large dataset requiring robust automated analysis procedures. Such seismic datasets are often characterized by multiple events with short inter-event times or overlapping events; in this case, correct phase identification and event association are challenging, and errors can lead to missed detections and/or reduced location resolution. In the last years, to improve the performance of the current data analysis procedure various waveform-based methods for the detection and location of microseismicity have been proposed. These methods exploit the coherence of the waveforms recorded at different stations and do not require any automated picking procedure. Although this family of methods have been applied to different induced seismicity datasets, an extensive comparison with sophisticated pick-based detection and location methods is still lacking. We aim here to perform a systematic comparison in term of performance among waveform-based methods and the pick-based detection and location methods (SCAUTOLOC and SCANLOC) implemented within the SeisComP3 software package. SCANLOC is a new detection and location method specifically designed for seismic monitoring at local scale. Although recent application led to interesting results an extensive test with induced seismicity datasets have been not yet performed. This method is based on a cluster search algorithm to associate detections to one or many potential earthquake sources. On the other hand, SCAUTOLOC is more a “conventional” method and is the basic tool for seismic event detection and location in SeisComp3. This approach was specifically designed for regional and teleseismic applications, thus its performance with microseismic data might be limited. We analyze the performance of the three methodologies for a synthetic dataset with realistic noise conditions as well as for the first hour of continuous waveform data, including the Ml 3.5 St. Gallen earthquake, recorded by a microseismic network deployed in the area. We finally compare the results obtained all these three methods with a catalogue obtained by using a waveform template matching method.
Waveform based location method (Grigoli et al 2016 SciRep) applied to volcanic data.
Microseismic monitoring is common operation in different georesources related industrial activities, such as oil&gas and mining operations or geothermal energy exploitation. In microseismic monitoring operations we generally deal with large dataset requiring robust automated analysis procedures. Such seismic datasets are often characterized by multiple events with short inter-event times or overlapping events; in this case, correct phase identification and event association are challenging, and errors can lead to missed detections and/or reduced location resolution. In the last years, to improve the performance of the current data analysis procedure various waveform-based methods for the detection and location of microseismicity have been proposed. These methods exploit the coherence of the waveforms recorded at different stations and do not require any automated picking procedure. Although this family of methods have been applied to different induced seismicity datasets, an extensive comparison with sophisticated pick-based detection and location methods is still lacking. We aim here to perform a systematic comparison in term of performance among waveform-based methods and the pick-based detection and location methods (SCAUTOLOC and SCANLOC) implemented within the SeisComP3 software package. SCANLOC is a new detection and location method specifically designed for seismic monitoring at local scale. Although recent application led to interesting results an extensive test with induced seismicity datasets have been not yet performed. This method is based on a cluster search algorithm to associate detections to one or many potential earthquake sources. On the other hand, SCAUTOLOC is more a “conventional” method and is the basic tool for seismic event detection and location in SeisComp3. This approach was specifically designed for regional and teleseismic applications, thus its performance with microseismic data might be limited. We analyze the performance of the three methodologies for a synthetic dataset with realistic noise conditions as well as for the first hour of continuous waveform data, including the Ml 3.5 St. Gallen earthquake, recorded by a microseismic network deployed in the area. We finally compare the results obtained all these three methods with a manual revised catalogue.
An extended description of the implementation of the deep geothermal wells GRT-1 and GRT-2 respectively drilled in 2012 and 2014 in the framework of the ECOGI project is given. These wells located in Rittershoffen (France) offer a unique opportunity to gather high quality datasets on a deep geothermal system in the Upper Rhine Graben at the transition between the Buntsandstein sandstone and the Palaeozoic granite basement. We present the extensive logging and well testing program that was applied and focus on hydraulic and thermal characterization of the targeted deep reservoir. Well architectures of GRT-1 and GRT-2 are described. Temperature logs in both wells are discussed in details. In particular, temperature in the production well GRT-2 is shown to reach 177°C at 3196m MD at thermal equilibrium. Production tests of both wells, reservoir development strategy applied in well GRT-1 and circulation test realised between wells are analysed. Productivity and injectivity indexes of GRT-1 and GRT-2 are estimated: Post-stimulation injectivity of GRT-1 and productivity of GRT-2 are respectively estimated to 2.5l/s/bar and 3.5l/s/bar. Hydraulic properties of the reservoir are inferred from production tests. Implications for the characterization of the large scale natural hydro-thermal system are discussed.
Earthquakes may be induced by a wide range of anthropogenic activities such as mining, fluid injection and extraction, and hydraulic fracturing. In recent years, the increased occurrence of induced seismicity and the impact of some of these earthquakes on the built environment have heightened both public concern and regulatory scrutiny, motivating the need for a framework for the management of induced seismicity. Earthquake early warning systems coupled with non-standard monitoring approaches can prove as valuable tools for mitigating the risk associated with earthquakes. These solutions might include advanced sensors with a number of functions, such as implementing a performance-based on-site early warning and rapid response system for infrastructure but also monitoring the structural response of buildings and infrastructure in real time. Such technical solutions can be used also for validating damage forecasts (performance) determined by probabilistic approaches based on suitable fragility curves. Based on the performance level an alert is designated according to pre-defined thresholds for acceptable levels of motion. The ultimate objective of any effective program for the management of induced seismicity must be to limit the consequent seismic risk. Towards this goal, the seismic hazard, the exposure and the vulnerability should be defined. Hazard is defined by a measure of the ground shaking, and in order to quantify the likelihood of the risk, the associated frequency or probability of exceedance. Regarding exposure coupling remote sensing with in-situ imaging can be optimized over broad areas for the characterization of the built environment. Finally, related to vulnerability, for the specific case of induced seismicity different types of consequences might be considered such as non-structural damage to buildings and annoyance of the affected population. It is therefore important to incorporate in an already developed on-site early warning and rapid damage forecasting system (Parolai et. al. 2015) properly derived fragility curves. After reviewing the existing protocols for evaluating the fragility, new proposals are made for analytical fragility curves for typical building types that have been developed for the seismic demands generally imposed upon linear and slightly nonlinear systems of single and multiple degrees of freedom which is the case for induced seismicity demands.
Geothermal reservoir stimulation is a standard technique for enhancing naturally low permeable reservoirs or to overcome formation damage. Hydraulic, chemical or thermal stimulation are applied as standard procedures. Those are supposed to solve individual problems, which might lead to only short-term reservoir enhancement. Constraints in geothermal systems are often more complex and change with time. Therefore, we developed a Feedback Adjustment Procedure for sustainable soft stimulation concepts. The procedure starts with a multidisciplinary database and pre-evaluates potential scenarios. The most important step in the procedure is a re-evaluation loop after each treatment that ensures regularly updated knowledge on site-specific processes. The loop ensures an adapted stimulation concept ending in sustainable reservoir enhancement. At our geothermal test site in Klaipeda (Lithuania) four wells target a highly permeable Lower Devonian sandstone reservoir at about 1 km depth with 39°C warm, highly saline fluid. The geothermal system delivers 41 MW th. Since start of injection in 2001, rates constantly decrease in both injection wells. Several treatments have been used to enhance the injectivity. However, those applications have not yet resolved injectivity decrease. Thus, we applied a new approach incorporating all relevant processes and adjusting the scenarios based on multidisciplinary observations. M ost potential scenarios at the Klaipeda site are ranked based on a Feedback Adjustment Procedure. M ost probably reasons for injectivity problems at the site are clogging of filter screen and/or pores by precipitation of minerals, by corrosion-particles, by biofilm, by injection of finest particles or pollution by drilling mud. In a next step, borehole logs, camera inspection and production and injection tests will be used to further rank scenarios. Specific stimulation treatments will be selected after re-evaluation for each scenario. Precipitations and biofilm will be removed and lifted by chemical-mechanical cleaning. Finest particles and corrosion material will be removed by long-term production tests. A mud cake will be hydraulically stimulated with frac-packs. Any new observation requires a re-evaluation and ordering of scenarios based on updated database. Therefore, the Feedback Adjustment Procedure will guarantee a sustainable overcome of formation damage.
Due to the deep socioeconomic implications, induced seismicity is a timely and increasingly relevant topic of interest for the general public. Cases of induced seismicity have a global distribution and involve a large number of industrial operations, with many documented cases from as far back to the beginning of the 20th century. However, the sparse and fragmented documentation available makes difficult to have a clear picture on our understanding of the physical phenomenon and consequently in our ability to mitigate the risk associated with induced seismicity. This review presents a unified and concise summary of the still open questions related to monitoring, discrimination and management of induced seismicity in the European context and, when possible, provides potential answers. We further discuss selected critical European cases of induced seismicity, which led to the suspension or reduction of the related industrial activities.