Sürdürülebilir Kalkınma Amaçları
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- MakaleAçık Erişim2026Structural joint modeling of magnetotelluric data and Rayleigh wave dispersion curves using Pareto-based particle swarm optimization: an example to delineate the crustal structure of the southeastern part of the Biga Peninsula in western Anatolia
Büyük, Ersin; Zor, Ekrem; Tapırdamaz, Mustafa Cengiz
It is widely acknowledged that the joint inversion of magnetotelluric and seismological datasets enhances the quality of the crustal structure solution, even when the physical correlation between electrical resistivity and seismic velocity is weak or indirect. The structurally coupled joint inversion approach has received considerable attention over the past two decades for its ability to estimate such parameters by penalizing their cross-gradient vectors at similar spatial positions. Despite this interest, various structural couplings and different physical directions (incremental or decremental) have been partially overlooked. We hereby propose an approach for the joint inversion of magnetotelluric (MT) and Rayleigh wave dispersion (RWD) data to estimate uncorrelated parameters by integrating particle swarm optimization (PSO) and the Pareto optimality approach. We used the optimality framework of these methods to overcome the difficulties associated with traditional joint inversion algorithms and to obtain optimal solutions that account for both similar and contrasting physical sensitivities. The significant correlation between the inverted and synthetic models under both noise-free and noisy datasets, together with the consistent results obtained from comparison with a traditional derivative-based joint inversion algorithm, further strengthened our confidence in applying the proposed modeling approach to the field data from the southeastern Biga Peninsula, western Anatolia. The models inverted from the field data corroborate the efficacy of the presented method. A notable characteristic of the proposed methodology is its capacity to estimate uncorrelated physical parameters, such as electrical resistivity and seismic velocity, without the imposition of penalties. Therefore, the presented method not only offers advantages in joint inversion but also allows modelers to observe and analyze model parameters having different sensitivities that may indicate different physical directions.
- MakaleAçık Erişim2026Post-Seismic Variation in Petrophysical Parameters and Heat Storage at the Tuzla Geothermal Field, Biga Peninsula (NW Anatolia) From Resistivity-Depth Model Using Differential Evolution Algorithm
Büyük, Ersin; Uzel, Bora; Sözbilir, Hasan; Baba, Alper
Electrical resistivity has been shown to offer significant insights into post-seismic changes in geothermal reservoirs; however, its interpretation is complicated by the fact that it is controlled not only by temperature, but also by porosity and clay content. In this study, we used a post-seismic electrical resistivity-depth model from magnetotelluric data to estimate the temperature changes following a seismic swarm in the vicinity of the Tuzla Geothermal Field in the Biga Peninsula of northwestern Anatolia. In the absence of pre-seismic resistivity data for the field, we attribute the characteristic part of the post-seismic model to the seismic swarm. Temperature changes were then evaluated using pre- and post-seismic wellhead temperature observations together with the post-seismic resistivity-depth model. In order to address the relationships between resistivity and petrophysical parameters, the present study combined the established equations for temperature, porosity and clay-related effects. The estimation of petrophysical parameters from combined equations was then conducted using the differential evolution algorithm (DEA), a method that has gained popularity due to its effectiveness in solving non-linear optimization problems. The main contribution of this study lies in the integrated use of a unified petrophysical framework and the DEA to jointly estimate post-seismic changes in temperature, porosity and clay content from the resistivity model. Furthermore, an estimation was made of the reduction in stored heat within the defined reservoir zone. The results indicate that the observed increase in resistivity is primarily associated with a decrease in reservoir temperature, which is consistent with the observed decrease in wellhead temperatures. In addition, changes in clay content and porosity contribute significantly to the resistivity response. The findings demonstrate the efficacy of models of resistivity-depth, obtained following seismic activities, in facilitating the inference of changes in petrophysical parameters and thermal state in geothermal systems.
- DüzeltmeYalnız künye2026Corrigendum to “3-D Magnetotelluric Modeling and Radiogenic Heat Reservoir for EGS Development: A Case Study of the Kestanbol Granitoid Intrusion (NW Türkiye)” [Geothermics, 140 (2026) 103728]
Büyük, Ersin; Hacıoğlu, Özlem; Ayzit, Tolga; Baba, Alper
The authors regret that the resistivity color legend range in Figures 5 and 8 and Supplementary Material 2 was incorrectly displayed in the published article. The published figures show the resistivity scale from1 10¹ to 10⁵ Ωm; however, the correct display range should be 10¹ to 10³ Ωm.Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.geothermics.2026.103806.Image, application 1 (figure presented) (figure presented)
- MakaleYalnız künye20263-D magnetotelluric modeling and radiogenic heat reservoir for EGS development: A case study of the Kestanbol Granitoid intrusion (NW Türkiye)
Büyük, Ersin; Hacioglu, Ozlem; Ayzit, Tolga; Baba, Alper
Enhanced Geothermal Systems (EGS) provide firm, low-carbon baseload power and can contribute to reducing fossil-fuel-based energy generation. Granites and granitoids are particularly favourable EGS hosts due to their widespread occurrence, fracture-controlled permeability, and long-term heat supply from radiogenic decay. This study proposes an EGS development plan for the Kestanbol Granitoid Intrusion (KGI) in NW Anatolia, T & uuml;rkiye, based on a three-dimensional magnetotelluric (MT) model integrated with geochemical constraints on radiogenic heat production (RHP). We invert MT data acquired at fifty unevenly spaced sites to image the 3D resistivity structure of the KGI and its surroundings, resolving a highly resistive plutonic body bounded by relatively conductive fault-fracture zones. To quantify the radiogenic heat reservoir, we determine RHP rates from uranium, thorium, and potassium concentrations measured on twenty-seven rock samples from the KGI and adjacent lithologies, and integrate these values with the MT-derived pluton geometry. When combined with the regional stress regime, the integrated results indicate that the KGI hosts elevated RHP relative to surrounding rocks and that its internal structure and fault-controlled permeability architecture are favourable for EGS development. In particular, the north-western margin of the KGI emerges as the most promising target for injection-production well pairs. This workflow demonstrates how integrated MT, geochemical, and structural analyses can provide a quantitative, site-specific basis for EGS prospect ranking and drilling strategy in radiogenic granite/granitoid provinces. Overall, we propose a site-specific and risk-aware EGS development plan for the KGI that couples subsurface structure, radiogenic heat supply, and permeability architecture, providing a transferable framework for assessing radiogenic granite/granitoid provinces.
- MakaleYalnız künye2024Caprock integrity at Çanakkale-Tuzla hydrothermal system inferred from magnetotelluric modeling using particle swarm optimization
Büyük, Ersin; Karaman, Abdullah
The impermeable caprock within a geothermal system serves the purpose of effectively sealing the reservoir, resulting in an elevation of both pressure and temperature. This sealing mechanism plays a crucial role in the long-term preservation of the system while also contributing to its overall sustainability. Caprock failure subsequent to seismic activity near a geothermal site can lead to the permeation of the caprock structure, resulting in diminished sealing capabilities and a decline in the reservoir temperature. In addition, this process alters the geochemical composition of the water by creating a hydrothermal mixture zone that disrupts the resistivity structure of the caprock, which is typically characterized by low resistivity values due to its substantial clay content and mineral alteration. This study focuses on investigating the integrity of the caprock at the Çanakkale-Tuzla geothermal field in Turkey, where water temperature and conductivity were reported to have decreased after a moderate-magnitude earthquake and subsequent aftershocks. For this purpose, we have performed magnetotelluric (MT) measurements, a method known for its sensitivity to geochemical reactions. These measurements are conducted along two parallel profiles that encompassed a total of 32 stations. The particle swarm optimization (PSO) technique is used to overcome the subtle difficulties associated with conventional inversion methods in modeling the MT data of complex formations. This is the first study that overcomes the difficulties emanating from the caprock failure by modeling MT data using PSO. Our modeling approach produces resistivity images that we interpreted as the signature of the failed caprock following the earthquake at the study site. Our results appear to confirm the documented geochemical changes, or hydrothermal mixture zone around the caprock structure.
- MakaleAçık Erişim2024A new method of smoothness-constrained magnetotelluric modelling with the utility of Pareto-optimal multi-objective particle swarm optimization
Büyük, Ersin
Particle swarm optimization, one of the modern global optimization methods, is attracting widespread interest because it overcomes the difficulties of conventional inversion techniques, such as trapping at a local minimum and/or initial model dependence. The main characteristic of particle swarm optimization is the large search space of parameters, which in a sense allows the exploration of the entire objective function space if the input parameters are properly chosen. However, in the case of a high-dimensional model space, the numerical instability of the solution may increase and lead to unrealistic models and misinterpretations due to the sampling problem of particle swarm optimization. Therefore, smoothness-constrained regularization techniques used for the objective function or model reduction techniques are required to stabilize the solution. However, weighting and combining objective function terms is partly a subjective process, as the regularization parameter is generally chosen based on some kind of criteria of how the smoothing constraints affect the data misfits. This means that it cannot be completely predefined but needs to be adjusted during the inversion process, which begins with the response of an initial model. In this paper, a new modelling approach is proposed to obtain a smoothness-constrained model from magnetotelluric data utilizing multi-objective particle swarm optimization based on the Pareto optimality approach without using a regularization parameter and combining several objective function terms. The presented approach was verified on synthetic models and an application with field data set from the Çanakkale–Tuzla geothermal field in Turkey. Findings from these analyses confirm the usefulness of the method as a new approach for all constrained inversions of geophysical data without the need to combine the objective function terms weighted by a regularization parameter.