Uncertainty analysis of gravity disturbance for geothermal exploration in the Geneva Basin (Switzerland)

Perozzi, Lorenzo; Guglielmetti, Luca; Moscariello, Andrea

doi:10.31223/x52p5t

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…Various ML algorithms, including k-means clustering, artificial neural networks (ANNs), and backpropagation neural networks (BPNNs), have been successfully employed in geothermal reservoir engineering. For instance, k-means clustering facilitates the identification of distinct reservoir zones with unique characteristics [35], while ANNs and BPNNs excel at learning complex relationships between input variables and production outcomes. These algorithms have been Instrumental in enhancing geothermal well drilling strategies [36] and predicting reservoir production with improved accuracy [37].…”

Section: Application Of New Technologymentioning

confidence: 99%

Unlocking Geothermal Energy: A Thorough Literature Review of Lithuanian Geothermal Complexes and Their Production Potential

Memon,

Makauskas,

Kaminskaite-Baranauskiene

et al. 2024

Energies

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Lithuania is located on the East of Baltic sedimentary basin and has a geothermal anomaly situated in the southwestern region of the country. There are two primary geothermal complexes within the anomaly, composed of Cambrian and Devonian aquifers. The Cambrian formation is composed of sandstones that have a reservoir temperature reaching up to 96 °C (depth > 2000 m). The Devonian aquifer is composed of unconsolidated sands of Parnu–Kemeri and has a reservoir temperature of up to 46 °C (depth > 1000 m). Historically, both formations have been investigated for geothermal energy production. In this article, we present a detailed literature review of the geothermal work carried out on both formations, including past, present, and some possible future studies. The study presented in this paper highlights the key findings of previous research work, summarizes the research gaps, and then elaborates on the possible applications of emerging technologies to bridge the research gaps and improve our understanding of geothermal complexes in Lithuania. Although it is not the main aim of this article, this article also touches upon the important need to develop 2D/3D numerical models, to quantify uncertainties, in the evaluation of the geothermal potential in Lithuania for commercial development. This study also highlights possibilities of extending geothermal development to depleted hydrocarbon reservoirs through repurposing the high-water-production wells. Moreover, from the literature review, it can be concluded that the Lithuanian geothermal aquifers are hyper-saline in nature and temperature changes lead to the deposition of salts both upstream and downstream of the reservoir. Therefore, there is a need for developing multiphysics thermo-mechanical–chemical (THMC) models for evaluation of reservoir behavior. The literature also describes the potential use and development of the THMC model as a part of future work that must be carried out.

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Section: Application Of New Technologymentioning

confidence: 99%

Unlocking Geothermal Energy: A Thorough Literature Review of Lithuanian Geothermal Complexes and Their Production Potential

Memon,

Makauskas,

Kaminskaite-Baranauskiene

et al. 2024

Energies

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“…Recent advancements in machine learning (ML) techniques and their application to geology and geoscience have greatly benefited geothermal energy during exploration. The applications of ML techniques to characterizing geothermal exploration processes have led to more efficient and cost-effective research [19,20].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Techniques in Predicting Bottom Hole Temperature and Remote Sensing for Assessment of Geothermal Potential in the Kingdom of Saudi Arabia

Alqahtani,

Ehsan,

Abdulfarraj

et al. 2023

Sustainability

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The global demand for energy is increasing rapidly due to population growth, urbanization, and industrialization, as well as to meet the desire for a higher standard of living. However, environmental concerns, such as air pollution from fossil fuels, are becoming limiting factors for energy sources. Therefore, the appropriate and sustainable solution is to transition towards renewable energy sources to meet global energy demands by using environmentally friendly sources, such as geothermal. The Harrat Rahat volcanic field, located in the western region of the Kingdom of Saudi Arabia (KSA), gets more attention due to its geothermal potential as a viable site for geothermal energy exploration due to its high enthalpy. The prime objective of this study is to present up-to-date and comprehensive information on the utilization of borehole temperature and remote sensing data to identify the most prospective zones with significant geothermal activity favorable for exploration and drilling. A brief description of the selected wells and the methodology used to determine the petrophysical parameters relevant to the geothermal potential assessment are presented. Special emphasis is given to gamma-ray ray and temperature logs for calculating heat production and the geothermal gradient. The effectiveness of various machine learning techniques are assessed throughout this study for predicting the temperature-at-depth to evaluate the suitability of employing machine learning models for temperature prediction, and it is found that XG Boost provided excellent results. It can be observed that some linear anomalies can be traced in the NW, trending on the west side of the Harrat volcanic field based on magnetic data interpretation. The land surface temperature in 2021 exhibited higher temperatures compared to 2000, suggesting potential volcanic activity in the subsurface. It is concluded that the integration of remote sensing data with subsurface data provides the most reliable results.

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Uncertainty analysis of gravity disturbance for geothermal exploration in the Geneva Basin (Switzerland)

Cited by 2 publications

References 33 publications

Unlocking Geothermal Energy: A Thorough Literature Review of Lithuanian Geothermal Complexes and Their Production Potential

Unlocking Geothermal Energy: A Thorough Literature Review of Lithuanian Geothermal Complexes and Their Production Potential

Machine Learning Techniques in Predicting Bottom Hole Temperature and Remote Sensing for Assessment of Geothermal Potential in the Kingdom of Saudi Arabia

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