Geothermal Energy最新文献

Geothermal energy in the Paris urban area has been exploited since the early 1970s. Deep drilling in the Paris sedimentary basin has targeted hot brine in the Dogger formations from a mid-Jurassic carbonate rocks series. More than a hundred wells have been drilled to depths ranging from 1400 to 2000 m and decades of production and reinjection have resulted in variations in the aquifer pressure and temperature in some areas. The regional numerical model discussed herein is aimed at assessing the potential interactions between doublets and for assessing the impact of the addition of more wells in the future. While the integration of a 3D refined geological model into a large-scale reservoir model needs heavy computational resources, local models simplifying the main productive areas into one or two layers surrounded by impermeable units can be used to approximately assess the reservoir characteristics. The modelling of a semi-regional area of the Dogger reservoir in the Southern part of Paris (Cachan/Orly) has been performed, using a conventional double-layer approach to simulate the natural state and production history of the area using the simulator Waiwera, a fast parallel open-source geothermal simulator from the University of Auckland in New-Zealand. Calibration of a natural state model, which describes the conditions before any geothermal operations, has been performed, including an analysis of the impact of boundary condition values on the ability of the model to match the data available in the public domain. The temperature and pressure distributions, instead of being based on geostatistical mapping methods have been obtained from a calibrated natural state model. The implementation of a regional lateral cross flow observed from past studies proved to be essential for matching the measured temperatures and pressures along with variations in the deep heat flux. A calibrated model has been obtained from matching the available production data with mismatches of no more than 1.5 °C. The modelling results confirm the dominance of the shallower productive zone in the aquifers and give insights into the extent of the cooler areas created by the long-term operations. Thus we have used the Dogger reservoir, with multiple data sets available, as a case study for calibrating a semi regional numerical model of a deep sedimentary aquifer used for geothermal direct-use. Our modelling study accounts for the conceptual understanding of the sedimentary aquifer with its heterogeneities and calibrates the numerical model against the measured historical data. Based on the calibrated reservoir model, the pressure and temperature responses in deep productive areas can be determined enabling operators or decision makers to test future strategies for sustainably operating the geothermal resource.

Geothermally, the lithosphere can be defined as the outermost layer of the Earth in which heat is primarily transferred by conduction. It typically includes the crust and upper mantle. Crustal structural provinces are segments of the crust that have the same range of geochronologic ages and thermogeologic histories. The crustal geothermal regime on the continent is determined by many factors, including heat flow, vertical and lateral variations in thermal conductivity, radiogenic heat production, tectonic history, and surface thermal processes. Studying the thermal structure of the crust by geotectonically characterizing the upper lithospheric layer makes it possible to understand the internal heat flow as an energy source potential, which remains unknown due to limited exploration research. This study presents a crustal heat distribution model using direct temperature data and indirect estimates derived from crustal magnetic field information, the THERMOMAG model. The subsurface layers are identified in order to characterize the entire magnetized crust, thus delimiting the Curie surface (isothermal limit of 580 °C), which is directly linked to the exploration of crustal energy resources. Spectral analysis of the aeromagnetic data was used to estimate the depth of the layer related to the deepest crustal sources and their spatial distribution, thus comparing these discoveries with geothermal fields known from direct modeling. The cross-check in the values for the Curie isotherm inserted by the thermomagnetic model allowed a correction in the values obtained indirectly, called the thermomagnetic correction factor (β) which is directly correlated to the amount of data distributed in the different provinces. The results of this model suggest that the greatest Curie depths in Brazil (> 44 km) are located in the São Francisco and Parnaiba provinces, and for the others, the mean values are 23 km. The regions of geothermal anomalies are found essentially in the northwest region of Paraná province, the northern part of Tocantins West province, the south-central part of Tocantins East province, the north-central part of São Francisco province, and the northeast region of Borborema province. The Brazilian structural provinces have thermal conductivity values ranging from 2.1 to 2.7 W/mK.

This paper investigates the feasibility of coaxial deep borehole heat exchanger (CDBHE) applications to the University of California San Diego (UCSD) campus. By collecting different geophysical source data for various formations and well logs around the UCSD campus, a multilayered thermophysical model for the ground on the site is established. Water circulation within a closed coaxial loop system considers the geothermal energy extraction under uncertainty consideration of the unknown deeper layers heat flow gradient as coupled with the variation of pipe insulation properties, flow rates, outer pipe diameter, grout, and depths between 1 and 4 km. A finite-element framework models the Navier–Stokes fluid flow and heat transfer in the CDBHE system, validated with a field test on CDBHE from the literature. Results show that a 4-km CDBHE could produce a thermal power of 600 kW under the optimum geological conditions at the UCSD site: the water flow rate of 2.78 L/s and a ground thermal gradient of 60 ℃/km. Thermal power shares from different layers indicate that deeper formation layers contribute more to the thermal power than the shallower layers because increasing the CDBHE length from 1 to 4 km can lead to a maximum of 900% increase in thermal power and a 50% expansion in thermal plume for a CDBHE with an insulated inner pipe between the upper and lower bound heat flow bounds. An inner pipe with an insulated depth of 2 km produces only 1–6% less power than a fully insulated inner pipe for the 4-km CDBHE, and thus, a partially insulated vacuum-insulated tube (VIT)-plastic inner pipe is suggested as the best practice. Furthermore, the CDBHE thermal power increases by 5% when the grout thermal conductivity increases from 1 to 3.65 W/(K∙m), close to the formation thermal conductivity, and then maintains almost the same, and the 4-km CDBHE with flow rates of 2.78–6.94 L/s at the UCSD site can directly supply a low-temperature heating radiator system for room heating. This study suggests practical ranges for geothermal energy extraction for southern California. A CDBHE with a well-insulated inner pipe of 0.05 W/(m∙K), the thermal power of lower and upper-bound heat flow cases can vary by 60% from the mean. Finally, water as the working fluid is more efficient than CO₂, doubling CDBHE's thermal power. The effects of the investigated factors provide guidelines for future geothermal resource exploitation in southern California.

Low injectivity is often experienced in geothermal doublets installed in sandstone reservoirs. This even led to a shutdown of the Mezőberény (Hungary) geothermal site. An on-site campaign was carried out in January 2021 to prepare a stimulation aiming to enhance the transmissivity of the sedimentary reservoir and the near-wellbore zone of this site. Previous studies have concluded that insufficient injectivity may be linked to a high skin effect in the near well-bore zone and pore clogging in combination with the low net sandstone content of the fluvio-deltaic reservoir. A chemical soft stimulation based on the injection of hydrochloric acid (HCl) was successfully used to unclog and recover the well injectivity. Despite such empirical evidence, the geochemical mechanisms leading to both, detrimental formation of clogging and the HCl-driven transmissivity restoration, have not yet been elucidated. This work presents the results of a novel analysis aiming at (a) predicting the dominant type of clogging forming in the near-well bore zone; (b) quantifying the drop in hydraulic conductivity as clogging occurs; and (c) supporting the optimization of the HCl dosage during the chemical soft stimulation. The study is supported by new experimental datasets never presented before from the Mezőberény site and a geochemical model set-up simulating the main mechanisms involved in the clogging and unclogging processes. It is concluded that the biofilm formation was the dominant, while the precipitation of calcite and amorphous ferrihydrite—later reduced to magnetite by microbes—was the secondary clogging mechanism: In the long-term (yearly scale) simulating the hydraulic conductivity showed a decline with forming scales; therefore, biofilm was presumably responsible for the experienced rapid (1 month) clogging. When modelling the chemical stimulation, the estimated amount of precipitated minerals was dissolved already with 2.5 mol of HCl per liter of water (~ 10 m/m%). Therefore, the 20 m/m% of HCl chosen during the field campaign might had a beneficial effect dissolving the potentially higher amount of scaling and/or the carbonate minerals of the matrix near the wellbore. Overall, it is concluded that the chemical and the microbial analyses together with the geochemical model were critical to tailor the remediation attempts and to propose further development or reconstruction of the surface system before going into operation to prevent recurrent impairments. Our findings highlight the importance of interactions of various clogging mechanisms with each other as well as with the reservoir processes and provide approaches to tackle the issue of injectivity drop by characterizing and quantifying their effects.

This study reports on newly acquired density data of synthetically prepared pure and mixed NaCl and CaCl₂ aqueous solutions that span a wide range of geothermally encountered concentrations and mixing ratios. The analytical data are provided for the temperature range of 293–353 K at ambient pressure. For the reproduction of that data, PHREESCALE was used. The predictive potential of this numerical tool regarding the density of geothermal fluids of known composition was the major target herein. As a result, the measured data are in good agreement with previous analytical studies found in the literature. Possible sources of errors are discussed in this paper. Density data of the mixed solutions at temperatures other than ambient are unique and close existing data gaps. The numerical model reproduces the newly measured and already existing density data within an error band of approximately 1%. For further use in geothermal applications, this can be considered an excellent agreement. Moreover, the model yields a direct calculation of density without the need to establish complex empirical equations of state and mixing rules. Finally, sensitivity calculations performed with a thermal–hydraulic (TH) numerical reservoir model demonstrate the required accuracy of fluid density for reliably predicting the long-term performance of deep geothermal energy systems. In terms of the productivity index and the timing of thermal breakthrough it shows that the present analytical and numerical uncertainty in density is small enough to reliably state both reservoir parameters.

Deep learning has gained attention as a potentially powerful technique for modeling natural-state geothermal systems; however, its physical validity and prediction inaccuracy at extrapolation ranges are limiting. This study proposes the use of transfer learning in physics-informed neural networks to leverage prior expert knowledge at the target site and satisfy conservation laws for predicting natural-state quantities such as temperature, pressure, and permeability. A neural network pre-trained with multiple numerical datasets of natural-state geothermal systems was generated using numerical reservoir simulations based on uncertainties of the permeabilities, sizes, and locations of geological units. Observed well logs were then used for tuning by transfer learning of the network. Two synthetic datasets were examined using the proposed framework. Our results demonstrate that the use of transfer learning significantly improves the prediction accuracy in extrapolation regions with no observed wells.

Methods and instrumentation for measuring grout quality in heat pump boreholes, including the measurement of groundwater flow through boreholes outside partly grouted borehole exchanger pipes, have been developed in the Czech Republic. A Semtex charge has also been developed to repair rock massifs, which reliably disconnects borehole exchanger pipes without severely harming the surrounding rock environment or buildings. The resulting hole can then be used for regrouting, thus preventing undesirable vertical water flow through the borehole.

The global priority for sustainable societies drives the transition to green energy, with geothermal power as a promising alternative. Latin-American countries benefit from the active volcanism along the Pacific Rim, which fuels their significant geothermal potential. Geothermal electricity production in the region is steadily growing and currently represents approximately (11%) of global output (16 GW). This paper provides details on the installed capacity of electrical generation in the most geothermally significant Latin-American countries, as well as the estimated potential production from existing prospects in the region. We also discuss the multiple challenges that limit the widespread development and exploitation of this valuable resource in Latin-America. As México stands as the top electricity producer in the region and ranks sixth worldwide, we offer an overview of its geothermal potential, the use of electromagnetic imaging technologies to enhance Mexican geothermal resource exploration, and the challenges and limitations associated with traditional exploration techniques. Additionally, we present recent case studies on the combined use of these technologies in México, highlighting best practices and lessons learned. The paper identifies open questions and outlines future research directions, particularly in México, to unlock the geothermal potential of the entire region.

This study investigates the feasibility to repurpose wells from gas production for geothermal closed-loop application in the North German Basin (NGB). The objective for this research topic is to extend the value-added chain of idle wells by re-completion as coaxial deep borehole heat exchangers as an efficient way to produce green energy without drilling new wells by saving the carbon emission and costs of building a new geothermal well. With numerical models of two typical geological settings of the NGB and two different completion schemes, it is possible to simulate the thermal performance over a lifetime of 30 years. The calculated heat extraction rates range from 200 to 400 kW, with maximum values of up to 600 kW. Sensitivity analyses demonstrate that re-completion depth and injection temperature are the most sensitive parameters of thermal output determination. The heat demand around the boreholes is mapped, and heat generation costs are calculated with heating network simulations. The initial production costs for heat are comparable to other renewable energy resources like biomass and competitive against gas prices in 2022. This study highlights available geothermal resources’ environmental and economic potential in already installed wells. The application has almost no geological and no drilling risks and may be installed at any idle well location.

Thermal properties of grouting materials for borehole heat exchangers (BHE) are currently analysed with varying measurement methods and analysis procedures, resulting in difficulties when comparing values of different studies. This study therefore provides the first comprehensive investigation of different analysis procedures by systematically comparing the influence of the measurement method and the sample preparation on the determination of the thermal conductivity and the volumetric heat capacity. Seven dissimilar grouting materials with varying water–solid ratios (W/S) and compositions are analysed. The thermal conductivities of the materials range between 0.9 and 1.8 W m⁻¹ K⁻¹ (transient plane source method, TPS). The volumetric heat capacities range between 3.01 and 3.63 MJ m⁻³ K⁻¹ (differential scanning calorimetry, DSC). From the findings of this study, a standardised analysis of grouting materials is provided which suggests mixing of the grouting material at a high mixing speed and sample curing under water for 28 days at room temperature. The benefits of calculating the volumetric heat capacities of grouting materials from the specific heat capacities of dry samples measured with the DSC, the water content and the bulk density are demonstrated. Furthermore, an estimation procedure of volumetric heat capacity from the W/S and suspension density with an uncertainty of smaller ± 5% is provided. Finally, this study contributes to consistency and comparability between existing and future studies on the thermal properties of grouting materials.