Threats posed by the climate crisis have created an urgent need for sustainable green energy. Geothermal resources have the potential to provide up to 150 GWe of sustainable energy by 2050. However, the key challenge in successfully locating and drilling geothermal wells is to understand how the heterogeneous structure of the subsurface controls the existence of exploitable fluid reservoirs. In this Review, we discuss how key geological factors contribute to the profitable utilization of intermediate-temperature to high-temperature geothermal resources for power generation. The main driver of geothermal activity is elevated crustal heat flow, which is focused in regions of active magmatism and/or crustal thinning. Permeable structures such as faults exercise a primary control on local fluid flow patterns, with most upflow zones residing in complex fault interaction zones. Major risks in geothermal resource assessment and operation include locating sufficient permeability for fluid extraction, in addition to declining reservoir pressure and the potential of induced seismicity. Advanced computational methods permit effective integration of multiple datasets and, thus, can reduce potential risks. Future innovations involve engineered geothermal systems as well as supercritical and offshore geothermal resources, which could greatly expand the global application of geothermal energy but require detailed knowledge of the respective geological conditions. Successful discovery and operation of geothermal resources requires a thorough understanding of the heterogeneous geological subsurface. This Review discusses the key geological factors that contribute to the effective exploration of intermediate-temperature to high-temperature geothermal resources used for power generation and direct use applications.

Geological controls on geothermal resources for power generation

Petrophysical heterogeneity of the early Cretaceous Alamein dolomite reservoir from North Razzak oil field, Egypt integrating well logs, core measurements, and machine learning approach

. Petrophysical and mechanical rock properties are key parameters for the
characterization of the deep subsurface in different disciplines such as
geothermal heat extraction, petroleum reservoir engineering or mining. They
are commonly used for the interpretation of geophysical data and the
parameterization of numerical models and thus are the basis for economic
reservoir assessment. However, detailed information regarding petrophysical
and mechanical rock properties for each relevant target horizon is often
scarce, inconsistent or distributed over multiple publications. Therefore,
subsurface models are often populated with generalized or assumed values
resulting in high uncertainties. Furthermore, diagenetic, metamorphic and
hydrothermal processes significantly affect the physiochemical and
mechanical properties often leading to high geological variability. A
sound understanding of the controlling factors is needed to identify
statistical and causal relationships between the properties as a basis for a
profound reservoir assessment and modeling. Within the scope of the GEMex project (EU H2020, grant agreement no. 727550), which aims
to develop new transferable exploration and exploitation approaches for
enhanced and super-hot unconventional geothermal systems, a new workflow was
applied to overcome the gap of knowledge of the reservoir properties. Two
caldera complexes located in the northeastern Trans-Mexican Volcanic Belt –
the Acoculco and Los Humeros caldera – were selected as demonstration sites. The workflow starts with outcrop analog and reservoir core sample studies
in order to define and characterize the properties of all key units from the
basement to the cap rock as well as their mineralogy and geochemistry. This
allows the identification of geological heterogeneities on different scales
(outcrop analysis, representative rock samples, thin sections and chemical
analysis) enabling a profound reservoir property prediction. More than 300 rock samples were taken from representative outcrops inside the Los Humeros and Acoculco calderas and the surrounding areas and from
exhumed “fossil systems” in Las Minas and Zacatlan. Additionally, 66
core samples from 16 wells of the Los Humeros geothermal field and 8 core
samples from well EAC1 of the Acoculco geothermal field were collected.
Samples were analyzed for particle and bulk density, porosity, permeability,
thermal conductivity, thermal diffusivity, and heat capacity, as well as
ultrasonic wave velocities, magnetic susceptibility and electric
resistivity. Afterwards, destructive rock mechanical tests (point load
tests, uniaxial and triaxial tests) were conducted to determine tensile
strength, uniaxial compressive strength, Young's modulus, Poisson's ratio, the
bulk modulus, the shear modulus, fracture toughness, cohesion and the friction
angle. In addition, X-ray diffraction (XRD) and X-ray fluorescence (XRF) analyses were performed on 137 samples to
provide information about the mineral assemblage, bulk geochemistry and the
intensity of hydrothermal alteration. An extensive rock property database was created (Weydt et al., 2020;
 https://doi.org/10.25534/tudatalib-201.10 ), comprising 34 parameters
determined on more than 2160 plugs. More than 31 000 data entries were
compiled covering volcanic, sedimentary, metamorphic and igneous rocks from
different ages (Jurassic to Holocene), thus facilitating a wide field of
applications regarding resource assessment, modeling and statistical
analyses.

/pdf/petrophysical-and-mechanical-rock-property-database-of-the-42f3m5j6ci.pdf

Petrophysical and mechanical rock property database of the Los Humeros and Acoculco geothermal fields (Mexico)

Descriptive statistical analysis of experimental data for wettability alteration with surfactants in carbonate reservoirs

For the successful realization and productivity prediction of new hydrothermal projects in the South German Molasse Basin, the hydraulic matrix properties of the Upper Jurassic Malm reservoir have to be determined as accurately as possible. To obtain specific information on the distribution of the petrophysical parameters (e.g., rock density, porosity, and permeability) 363 samples of rare drilling cores from the reservoir northeast of Munich (wells Moosburg SC4 and Dingolfing FB) were investigated using different experimental methods. Additionally, porosity was calculated by a downhole resistivity log of a nearby borehole close to Munich for comparison and the attempt of transferability of the data set to other locations within the Central Molasse Basin. Core data were divided into groups of different stratigraphic and petrographic units to cover the heterogeneity of the carbonate aquifer and provide data ranges to improve reservoir and prediction models. Data for effective porosity show a high variance from 0.3 to 19.2% throughout this heterogeneous aquifer. Permeability measured on core samples is scattered over several orders of magnitude (10−4–102 mD). Permeability models based on the porosity–permeability relationship were used to estimate permeability for the whole aquifer section and identify possible flow zones. A newly developed empirical model based on distinct lithofacies types allows a permeability estimation with a deviation < 10 mD. However, fractured, karstified, and vuggy zones occurring in this typically karstified, fractured, and porous reservoir cannot yet be taken into account by the model and result in an underestimation of permeability on reservoir scale. Overall, the dominant permeability trends can be mapped well using this model. For the regional transfer and the correlation of the results, a core-related porosity/permeability log for the reservoir was compiled for a well close to Munich showing similarities to the core investigations. The validation of the regional transferability of the parameter set to other locations in the Molasse Basin was carried out by correlation with the interpreted log data of a well near Munich.

/pdf/porosity-permeability-relationship-derived-from-upper-n2zorh8ch8.pdf

Porosity–permeability relationship derived from Upper Jurassic carbonate rock cores to assess the regional hydraulic matrix properties of the Malm reservoir in the South German Molasse Basin

Geothermal energy applications are seen as one key element for a successful heat transition in Bavaria. But there are still some barriers for a further development. To minimize these barriers the joint research project Geothermal Alliance Bavaria (GAB) is established. One important issue to foster the implementations of geothermal projects is the assessment of geothermal load prediction in the South German Molasse Basin (SGMB). This includes, aside from a reservoir temperature prognosis, an accurate description of the hydraulic properties of the Upper Jurassic Malm reservoir. Hydraulic test analyses are conducted in the framework of the GAB to obtain specific information about the hydraulic productivity of the reservoir. Results from these analyses show a decrease of rock permeability in southern direction within the reservoir. Because the spatial distribution of hydraulic test data is limited, the porosity of the reservoir is assessed by borehole core tests and logs interpretation. A trend of matrix porosity decrease with depth is recognised and correlates with the hydraulic test results. Based on these findings and combined with further information the Upper Jurassic reservoir could be classified in separated zones of similar production rates, which can now be used for a thermal output prognosis for the Bavarian part of the SGMB. To spatially expand these prognoses more data must be investigated in the next research phase of the GAB.

Characterisation of the Upper Jurassic geothermal reservoir in the South German Molasse Basin as basis for a potential assessment to foster the geothermal installation development – Results from the joint research project Geothermal Alliance Bavaria

Abstract. The localization and characterization of hydraulically active zones in a
geothermal well is a major task in understanding the hydro geothermal
reservoir. This is often done based on interpretations of spinner flow meter
measurements that are performed at the end of the well test while injecting
cold water. Once a production well is equipped with an electric submersible
pump, data collection inside the reservoir and monitoring of the flow zones
is usually barely possible. In a 3.7 km (MD) deep geothermal production well
in Munich, Germany, it was successfully demonstrated in 2019 that a
permanently installed optical fiber cable could close this measurement gap.
We used this fiber-optic monitoring system to collect distributed
temperature data once the well was set into production. We inversely modeled
the inflow from the formation into the borehole from the production
temperature data with an energy and mass balance model. The derived flow
profile correlates with previous flow meter analysis and indicates that a
karstified region at the very top of the reservoir is the driving factor for
hydraulics and obtained production temperature. Qualitatively, the two
profiles acquired by distributed temperature sensing (DTS) and flow meter
are matchable, yet the production inflow profile by DTS logging is more
differentiated compared to spinner flow meter logs interpretation during
injection.


Inverse flow zone characterization using distributed temperature sensing in a deep geothermal production well located in the Southern German Molasse Basin

D. Pfrang

Papers

Porosity–permeability relationship derived from Upper Jurassic carbonate rock cores to assess the regional hydraulic matrix properties of the Malm reservoir in the South German Molasse Basin

Characterisation of the Upper Jurassic geothermal reservoir in the South German Molasse Basin as basis for a potential assessment to foster the geothermal installation development – Results from the joint research project Geothermal Alliance Bavaria

Inverse flow zone characterization using distributed temperature sensing in a deep geothermal production well located in the Southern German Molasse Basin