IRANIAN JOURNAL OF GEOPHYSICS
Year:2026 | Volume:20 | Issue:1|Papers Count:10

Geodetic velocity data are vital for understanding crustal surface strain,however, since GPS measurements are taken at discrete locations, analyzing crustal deformation as a continuous field becomes challenging. This study employs the geostatistical kriging method to interpolate GPS velocity fields into a regular grid, thereby creating a continuous model of velocity and strain rates in the oblique collision zone of the Arabian-Eurasian tectonic plates. The input data comprise geographical coordinates and velocity components from 365 non-uniformly distributed stations of the Iranian Permanent GPS Network. The output includes horizontal velocity components, estimation errors on a 30-minute interval grid, and invariant quantities derived from the strain tensor.     Based on the validation results, the Gaussian semi-variogram model is chosen for generating the Variance-Covariance matrix among reference and interpolation points. The RMSE values of 1. 13 mm/year and 1. 73 mm/year were obtained for the northern and eastern components, respectively, in anisotropic mode. The azimuths for the semi-major axis of the anisotropy ellipse, which indicate the maximum directions of change for the northern and eastern components, were estimated to be 107 degrees and 103 degrees, respectively. The average azimuth for the semi-major axis of the anisotropy ellipse, representing the two northern and eastern components, nearly coincides with the boundary of the oblique collision zone. Semi-variogram graphs indicate that the level of anisotropy in the eastern components is greater than that in the northern components. High anisotropy in the eastern component suggests that the Central Iran, Lut, and South Caspian blocks exhibit resistance to deformation within the oblique collision zone.     By analyzing the components of the interpolated velocity field, it can be inferred that all of Iran is affected by the deformation resulting from the oblique collision zone of the Arabia and Eurasia tectonic plates. Deformation is not smoothly distributed in the study area. The direction of the eastern components (VE) within Iran varies, predominantly pointing westward in most areas, while in the southeast and northwest regions, it points eastward. The values of the northern velocity components (VN) decrease from south to north and from east to west. In other words, the southwestern region of Iran moves faster than the northeastern region. The range of the northern component is greater than that of the eastern component. The changes in the northern velocity component indicate the resistance of the South Caspian Sea block, as well as the Helmand and Turan blocks, to deformation in the collision zone. The changes in the magnitude of the principal strain axes and the maximum compression azimuth indicate that the spatial distribution of the interpolated velocity field in the region is irregular and exhibits a clear partitioning characteristic. The strain rate derived from the interpolated velocity field indicates convergence-type deformation, affirming the presence of compression in the study area. Strain concentration is evident around the majority of the active faults in the region.

This study utilizes three-dimensional Rayleigh wave group velocity tomography to investigate the shallow crustal velocity structure of Qeshm Island, located at the eastern end of the Zagros Mountain Range beneath the Bandar Abbas region. Qeshm Island, with its unique geological features, hosts a prominent salt dome known as Gavrzin, recognized as a hydrocarbon trap critical for underground oil and gas storage. Thus, this research emphasizes the necessity of comprehensive investigations into such geological structures due to their economic and environmental implications. For the three-dimensional Rayleigh wave tomography and velocity structure imaging, the study employs the Neighborhood Algorithm, a direct search technique that has emerged in recent decades for geophysical data inversion. The data used include aftershocks from the December 27, 2005 (6 Azar 1384), Qeshm Island earthquake, recorded by a network of 17 short-period seismic stations. The results reveal a salt dome situated near the Qeshm Fault, migrating westward. The initial depth of this salt dome is approximately 15 km, with its dimensions increasing as the depth decreases. The findings indicate that the Qeshm Fault plays a significant role in the formation and displacement of the Gavarzin salt dome. These results enhance the understanding of subsurface geology in the region and carry implications for the exploration and management of subsurface resources.  

In the futures studies literature, weak signals are considered a pioneering and cutting-edge notion in forecasting systems and patterns. This concept has gradually entered other fields. The term weak signal refers to information that has been overlooked, undervalued, or is incomplete, yet mismanagement in addressing it can lead to significant consequences. This study explores how deep sedimentary basins in the Makran subduction zone amplify long-period seismic waves, creating potential risks for structures and infrastructures. The Makran region, spanning southeastern Iran and southwestern Pakistan, is known for its thick accretionary prism filled with soft sediments, which can significantly amplify seismic waves with long wavelengths (1-10s). This poses serious concerns for tall buildings, commercial ports, and industrial facilities. The geometry and structure of sedimentary basins are key factors influencing the amplification of earthquake ground motions. However, elements such as corrections for geometric spreading and magnitude, intrinsic attenuation, the mechanism and location of earthquakes, location errors, and discrepancies between models and actual ground conditions introduce errors and uncertainties in calculating this amplification. To better understand this effect, we performed 3D seismic wave simulations using the SPECFEM3D software, applying a recently developed shear wave velocity model for the region. We simulated 45 synthetic earthquakes with random locations and focal mechanisms to analyze spectral amplification on synthetic seismograms. In addition, we analyzed real seismic data from both local and teleseismic earthquakes recorded by local networks in the region. The findings revealed that coastal Makran of accretionary prism experiences significant wave amplification, with amplitudes increasing by 2. 5 to 4 times for periods between 1 to 4 seconds. Interestingly, in eastern part of coastal Makran, data from real earthquakes showed slightly higher amplification compared to the simulations, likely due to differences between the velocity model and real earth, especially near the surface. This indicates that studying the site effect using the H/V method, especially for long wavelengths, is not always sufficient. Conventional methods may not accurately capture amplitude amplification of long-wavelength earthquake waves in the region. This can be considered as a weak signal in futures studies, and understanding it is crucial to preventing unexpected outcomes during crises. Earthquakes locating errors and considered approximations in correcting for geometric spreading and magnitude may also contribute to this discrepancy. Teleseismic earthquakes provided further evidence of strong amplification in the region, with some stations showing amplification up to five times compared to reference stations outside the basin. These findings underscore the critical need to account for the deep sedimentary basin effect in seismic hazard assessments for Makran, especially considering its growing urban and industrial development. The analysis reveals that long-period waves, which tend to resonate with tall buildings, pose the greatest risk. Ignoring these effects in seismic design could lead to underestimating ground motion intensity and increasing the risk of structural damage during major earthquakes. Ultimately, this study emphasizes the importance of improved seismic velocity models, expanded seismic monitoring networks, and more advanced 3D modeling to better predict seismic hazards and protect critical infrastructures in this economically important region.

Induced seismic events triggered by human activities such as subsurface fluid extraction and injection can jeopardize the integrity of critical infrastructure. The multistage framework proposed here obviates the need for exhaustive geological models and dense seismic arrays, yet accurately and reliably estimates the regional epicenter location. To derive region-based labels for the supervised classifiers, K-means clustering was first applied to the latitude–longitude coordinates of all recorded events,the resulting cluster assignments were adopted as class labels, providing an objective, data-driven regional segmentation for subsequent training.    In the initial processing stage, three-component seismic recordings were pre-processed by applying the short-term average to long-term average ratio (STA/LTA) to identify and correct abrupt baseline offsets. The cleaned records were then paired to form cross-correlation matrices at four lags (0. 5, 0. 1, 0. 05 and 0. 01 s) capturing relative information across multiple temporal scales. Recursive feature elimination with cross-validation (RFECV) extracted the most informative subset of correlation coefficients, substantially reducing dimensionality while preserving discriminative power. These feature vectors drove a probabilistic-averaging (soft-voting) ensemble that couples a support-vector machine (SVM) with an extreme-gradient-boosting (XGBoost) classifier, combining the margin-maximizing strength of SVM with the nonlinear learning capacity of boosted decision trees.    Model development was conducted twice (first on the raw, imbalanced data and then on data balanced with the Synthetic Minority Over-sampling Technique (SMOTE)) to quantify the influence of class imbalance. Without SMOTE, decreasing the correlation-window step from 0. 5 s to 0. 1 s improved classification accuracy for epicentral region assignment from 0. 73 to 0. 90 while markedly shrinking the standard deviation of epicentral errors, indicating greater solution stability. Moving to still finer steps (0. 05 s and 0. 01 s) made the model increasingly sensitive to high-frequency noise, saturating accuracy gains and slightly inflating variance,the 0. 1 s lag therefore emerged as an optimal trade-off between resolution and robustness.    With SMOTE, overall stability improved further and error dispersion contracted, yet a modest drop in accuracy appeared at steps coarser than 0. 01 s, attributable to the limited representativeness of some synthetic samples. The best performance arose from pairing SMOTE with the 0. 01 s step, achieving a classification accuracy of 0. 93 in epicentral region assignment, an absolute gain of 5. 7%  over the non-SMOTE result.    These findings demonstrate that the proposed workflow can deliver accurate, repeatable epicentral estimates in data-limited environments, supporting real-time decision-making without the need for comprehensive subsurface models. Furthermore, where computational resources are constrained, the 0. 1 s configuration without SMOTE remains a well-balanced option that combines high classification accuracy with modest processing cost.  

As the extraction of information about petrophysics and fluid content from near-field versus far-field variations has gained more importance in recent years, understanding the effect of shale anisotropy in near-field versus far-field is essential. The layered structure of clay minerals causes elastic anisotropy. Shales (even conventional shale samples) are often elastically anisotropic due to the alignment of anisotropic clay minerals with the bedding plane. This research aims to address this issue by presenting a method based on rock physics modeling and the use of Thomsen parameters for AVO analysis in VTI environments. In this study, the impact of shale anisotropy on amplitude versus offset (AVO) analysis at the gas sand/shale interface in the Kerman Formation has been examined. This issue is important because accurate AVO analysis can be effective in identifying hydrocarbon areas, but in many previous studies, isotropy in environments has been assumed, which may lead to errors. In this study, the amplitude versus offset analysis in a vertically transverse isotropic (VTI) medium has been examined. For this purpose, Thomsen's anisotropy parameters were calculated. Since the anisotropy of shale affects the results of amplitude versus offset analysis at the gas sand/shale contact in the Kerman Formation, we have evaluated the impact of shale on amplitude versus offset analysis in the Kerman Formation. The results showed that in an anisotropic environment, Class 1 AVO is identifiable, indicating the presence of hydrocarbons, whereas in an isotropic environment, no distinct trend is observed in the AVO class. Additionally, it was observed in synthetic models that the effect of anisotropy is more pronounced at larger angles. The innovation of this study lies in presenting a combined analytical approach based on rock physics modeling and Thomsen parameters for AVO analysis in an anisotropic environment, which goes beyond classical isotropy assumptions and can aid in improving the location of new drilling areas.

To investigate the seismotectonics of NW Iran and East Turkey using the multi-event hypocentroid decomposition method,  12 seismic clusters comprising 2, 149 relocated earthquakes were analyzed. Among these,  688 earthquakes were assigned focal depths with uncertainties of 2–3 km, and 234 focal mechanisms were calculated for these events. In this study,  all available datasets were utilized to examine correlations between known active faults and their associated seismicity and mechanisms, identify potential new faults, estimate the mechanisms of active faults in the region and finally revise the kinematic deformation model of the region. The results confirm that the primary tectonic boundaries defined in NW Iran and East Turkey, along with their associated mechanisms, remain largely valid, with most seismicity concentrated along block boundaries. However,  intra-block seismicity is observed within parts of the NW Iran and Van blocks. The seismicity pattern indicates that the majority of the seismic activity is concentrated along the right-lateral strike-slip North Tabriz Fault and its continuation toward the Gailatu-SiahCheshmeh-Khoy and Chalderan fault systems. Instrumental records reveal that seismic activity has persistently affected most segments of these faults over time. Our findings highlight a prominent and concentrated seismicity trend with normal mechanisms extending from the Zagros Mountains toward Salmas. Additionally,  another seismicity trend with right-lateral strike-slip mechanisms is observed, initiating at the terminus of the Zagros Main Recent Fault System and extending toward southeast Anatolia. Furthermore,  two newly identified trends perpendicular to the North Tabriz Fault, with a northeast orientation, emerge in the data. These may indicate the presence of fault segments characterized by left-lateral strike-slip mechanisms, which partially accommodate the displacement along the North Tabriz Fault. The distribution of aftershock cloud and variety of their focal mechanisms indicate that the fault geometry and mechanism in Khoy are more complex than the existing simplified fault maps suggest. Notably,  the right-lateral strike-slip mechanisms along the Talesh–South Caspian boundary as proposed in earlier tectonic models were not observed. Similarly, the relocated seismicity does not show any seismic activity along the south Baskale fault or the Maragheh fault. Based on earthquake focal depths and focal mechanisms, we hypothesize that faults parallel to the western Caspian fault are responsible for deep strike-slip earthquakes with a transtensional component in the Kura Basin. The intermediate-depth events may suggest underplating of northwestern region of SCB beneath Kura basin. The focal and centeriod depths indicate that the depth of the earthquakes along the primary boundaries of tectonic blocks ranges from 10 to 12 kilometers. However, within the blocks, specifically in the Ahar-Varzeqan cluster, as well as in the Zagros region, including the Oshnaviyeh and Bashkal clusters the depth of earthquakes is larger. This may be due to the young and immature nature of the faults responsible for these earthquakes. Additionally, the depth of earthquakes in the Talesh region and the South Caspian Basin may exceed 40 kilometers, indicating seismic activity occurring within the cold igneous crust of the South Caspian Basin lying beneath a thick sedimentary cover.

Electrical resistivity tomography (ERT) is a widely used for investigating subsurface properties, particularly in near-surface studies. It has found broad application in various fields, such as groundwater exploration, archaeology, environmental monitoring, and hydrogeophysical research, including the evaluation of aquifer parameters. In ERT, electrodes are strategically placed according to the survey goals and site characteristics to gather data. These measurements, which represent the distribution of potential or apparent resistivity, are then analyzed using inverse modeling techniques to obtain the actual resistivity distribution. This process involves solving a nonlinear inverse problem, which aims to minimize discrepancies between field data and theoretical predictions by optimizing an objective function.     The method is based on forward modeling, which simulates the physical behavior of the system, often by solving Poisson’s equation through a finite difference approach. Accurate forward modeling is crucial for effective inversion. In this study, resistivity responses are derived by simulating the flow of current through the Earth's surface, with Poisson's equation serving as the guide. A finite-difference algorithm is employed to discretize the models, incorporating mixed boundary conditions to enhance precision and reliability. One key advantage of the finite-difference method over other approaches is its established ability to quickly approximate solutions for complex and arbitrary structural models, often providing faster results than the finite-element method. The partial differential equations that describe the resistivity problem are derived using the principles of charge conservation and the continuity equation. To solve the inverse problem, the equations are linearized through iterative processes.     A central focus of this study is the application of inverse modeling to electrical resistivity data. The forward and inverse problem formulations, along with their respective solutions, have been implemented in MATLAB, with performance improvements achieved through C programming for computational efficiency. Field data are subject to noise, which may arise from factors such as imperfect measuring instruments, suboptimal field conditions, operator errors, and geological influences. These noise components can significantly affect the inversion process, given the inherent challenges of the inverse problem.     This study investigates the impact of data weighting matrices on the accuracy of geoelectrical data inversion, with focus on electrical resistivity data. The Occam inversion method was utilized as the primary framework for applying various weighting matrices and constraints during the inversion process. Our analysis shows that due to the presence of random noise, variations in the signal-to-noise ratio, the spacing between current and potential electrodes, the different arrays used along a profile, and geological complexities at the data acquisition site, employing data weighting matrices is essential for accurate inversion. Results from synthetic and field models demonstrate that applying a weighting matrix significantly improves the representation of conductive layers and reduces inversion errors. In field studies, validation using agricultural water wells confirmed that inversion results with a weighting matrix closely match geological realities. Additionally, the evaluation of inversion sections using resolution density, upper bounds of the resistivity variation, and sensitivity pattern indicates that the application of weighting matrices produces more reliable results.

Electromagnetic (EM) noise induced by high-voltage power grids remains a significant impediment to seismic data acquisition, particularly in large-scale hydrocarbon exploration projects. While conventional frequency-based filtering methods are commonly used to suppress EM noise, they often fall short in handling the transient and spatially variable nature of such interference. Moreover, these techniques risk attenuating critical portions of the seismic signal when the frequency spectra of signal and noise overlap. This study was focused on evaluating the performance of a novel approach to removing EM noise (herein referred to as “pure EM noise removal”), where the complex synthetic Marmousi II model was used as the testbed. In the evaluated denoising method, the EM noise was supposed to be recorded concurrently with seismic data via dedicated EM receivers, allowing direct application of amplitude and phase corrections prior to subtraction from the raw seismic traces. The Marmousi II model, with its high-resolution representation of geologically realistic subsurface structures, provides a rigorous and controlled environment to examine the behavior of EM noise suppression under varied conditions. By simulating diverse acquisition scenarios within the Marmousi II framework, effects of critical parameters were systematically explored, including the phase correction window size (in number of samples), amplitude correction factor, signal-to-noise ratio (SNR), and the spatial positioning of the EM receivers relative to the source of the EM noise (i. e. , power lines). Optimal performance was achieved with a 500-sample phase correction window, a negative amplitude correction factor, an SNR of 3, and positioning the EM receiver at an identified optimal location (EM5), resulting in denoising errors as low as 0. 009%. The spatial positioning of EM receivers emerged as a key factor in the effectiveness of the denoising. Incorrect placement led to reduced quality of recorded noise and, hence, increased denoising errors or waveform distortion after processing. The controlled layout of the Marmousi II model enabled fine-grained assessment of receiver geometry, ensuring that optimal locations could be reliably identified and replicated across different acquisition trials. Furthermore, the analysis highlighted the importance of synchronized acquisition of the EM noise together with the primary seismic acquisition, as the inherently dynamic and non-stationary behavior of the EM noise makes the real-time concurrent recording essential. Using the Marmousi II model made it possible to systematically follow a one-factor-at-a-time approach, offering insights that are often obscured by environmental noise, equipment variability, and logistical limitations in field data acquisition. Time-domain and frequency-domain evaluations confirmed that the pure EM noise removal method effectively preserved the integrity of the seismic signal, even in cases of spectral overlap with the EM noise. The results suggest that the proposed method not only offers enhanced denoising capabilities but also reduces the risk of signal loss compared to traditional filtering techniques. The findings underscore the potentials of the proposed method as a robust alternative to frequency-based filters, particularly in environments with strong power grid interference. Its adoption could significantly improve seismic data quality and interpretation reliability in both synthetic and real-world scenarios.

The reservoir can cause the leakage of regional faults and the occurrence of induced earthquakes. This study was conducted in the Rudbar Dam of the west of Iran, part of the Zagros seismic zone. where the occurrence of earthquakes with different magnitudes is a characteristic of this seismic state. By considering cyclic loading and orientation, the location and depth of faults can be modeled relative to the reservoir. Reservoir-induced earthquakes occur as a result of a shear failure along a fault plane. In this study, it is assumed that the events follow the Gutenberg-Richter distribution law. With this assumption, the distribution of stress due to the weight of Lake Rudbar on the nearest faults of the Rudbar Dam in Lorestan was modeled. Different stress variables due to the dam reservoir at different sections and the values ​​of stress changes at different distances and depths were calculated. The reservoir site is bounded by two active faults upstream of F1 and downstream of F10. Earthquakes after the impoundment of the Rudbar Dam, show a 70% increase. The dam impoundment was carried out an early 2017, and until the largest earthquake recorded, exceeding 5 on a local scale in December 2019, two periods of loading or lowering of the reservoir water level have occurred in the dam. This event has caused an increase in earthquakes at the dam construction site. After the second period of loading, which was greater than the first period, several earthquakes of ML= 3. 5 have occurred. The diffusion of pore water pressure with a coefficient called c is one of the reasons for the activation of the faults in the region. The Rudbar Dam local network in Lorestan recorded 1080 events in the last year of data collection in this study (2024). 117 events were closer than 50 km. At the beginning of the network installation (2015), out of 737 recorded events, 72 events were closer than 50 km. As can be seen, the total number of events shows an increase. Most of these events occurred between Hendijan and Saravand-Beznovid, which indicates that the faults and the western area of ​​the MHC station have been active in the past year and very high microseismic activity is observed in that area. In the southwestern part of the dam, the recorded events are related to the Lehbari fault. However, many events with a magnitude of less than 0. 5 on the local wave scale were recorded by the Gotvand-Olia stations, which can be observed as a seismic accumulation near this fault. Also, a seismic activity between the Mapharon and Lehbari faults is visible in this study. Therefore, there is a delay in the occurrence of earthquakes between the impoundment of the dam and the increase in pore pressure. This phenomenon has caused earthquakes to occur at greater depths and distances from the dam. The involvement of a greater length and surface area of the fractures has resulted in a smaller stress difference based on the Columbus rupture criterion.

The analysis of fault slip rates plays a crucial role in assessing seismic hazards and understanding the kinematic behavior of active faults. This is particularly critical in regions like Iran, where instrumental earthquake catalogs often lack sufficient temporal coverage (less than 100 years) to reliably estimate seismicity parameters like seismic recurrence intervals, especially for large-magnitude events (Mw > 7). Both long-term (geologic) and short-term (geodetic) approaches rely on measurements of near-surface displacements, and given the relative temporal stability of lithospheric deformation rates over timescales shorter than one million years, their results could be almost equal. However, significant discrepancies persist between published the long-and short-terms slip rates for major faults in Iran. The discrepancies could be related to inherent limitation of the two approaches, quality of their measurements, and also temporal variation of slip-rate. This study focuses on active faults in northeastern Iran, a seismically active deformation zone hosting several destructive earthquakes, to methodologically evaluate these inconsistencies. We compiled all available long-term and short-term slip rate estimates for the region, rigorously assessing their quality based on their used methodology and observational constraints. The lack of precise dating and use of different dating methods can each introduce some degree of uncertainty into long-term slip rate calculations. The length of GPS profile normal to a given active fault, quality of the observed GPS vectors, and presence of faults off the main active fault are influential factors controlling errors in short-term slip rate determinations. After excluding low-quality measurements, we performed comparative analysis of the most reliable estimates from both approaches. Our results demonstrate a linear correlation between geodetic and geologic slip rates, though with a systematic offset in which short-term rates exceed the long-term estimates by an average of ~1. 3 mm/yr. The systematically larger estimate of short-term slip rates arises from inherent limitations in geodetic methods that persist despite advances in remote sensing observation technologies. Geological methods measure slip accumulation along an active fault, whereas geodetic techniques typically resolve cumulative deformation rates across a given fault systems or block boundary. Geodetic measurements require GPS stations to be positioned at least twice the seismogenic layer thickness away from the fault to properly capture strain accumulation, leading to the inclusion of nearby faults off the main active fault and thus higher estimates of slip rates. The linear relationship between long-term and short-term slip rates, and the stochastic nature of temporal changes in slip rate, reject the existence of temporal changes in slip rate, at least for the faults of northeastern Iran. For large faults, a portion of the difference between long-term and short-term rates is related to the fact that the reported rates pertain to different parts of the fault system. The established linear relationship provides a valuable framework for identifying outlier slip rates.