Journal of Engineering Geology

Probabilistic seismic hazard analysis and preparation of acceleration zoning maps: a case study of Shahid Rajaei Port

Maedeh Roshan Liarajdameh

Iran, due to its location between two active tectonic plates, has always been exposed to numerous earthquakes. The occurrence of more than 100 severe earthquakes in the past century indicates the country’s high level of vulnerability to this natural hazard. The aim of this research is to analyze the seismicity and assess the earthquake hazard in Shahid Rajaei Port, as the largest commercial port in Iran (located at the intersection of the North-South transit corridor), which will be a fundamental step in enhancing the resilience and sustainability of the vital infrastructures in this region. In this study, all seismic events occurring within a 200-kilometer radius of the site were used, along with the Knopoff and Ez-Frisk software. The statistical analysis of historical and instrumental earthquakes indicates a high level of seismicity in the region, characterized by moderate-magnitude earthquakes with short return periods, such that earthquakes with magnitudes between four and five on the Richter scale constitute a larger share. The probabilistic hazard assessment estimated the maximum horizontal and vertical accelerations as 0.385 and 0.290 (g), respectively. Additionally, the site response spectrum was prepared based on the accelerographs of the Tabas earthquake and the isoacceleration maps of the study area, generated at intervals of 1.0 degrees in both latitude and longitude directions. The results showed that the study area has a seismic hazard of 0.85 (g), which is higher than the standard values specified in Iran’s Code 2800, placing it within the very high relative hazard zone. Therefore, implementing risk-based approaches in infrastructure development helps optimize port design and reduce earthquake-related damages.

The Necessity of Pumping Tests and Exploratory Well Drilling in Groundwater Baseline Studies: Challenges and Gaps in Iran

Kamal Ganjalipour

Exploratory studies and pumping tests are considered fundamental tools for understanding the hydrogeological behavior of aquifers. They play a critical role in water resources modeling, planning, and governing water resources. This article aims to analyze the role of these studies within the water governance framework in Iran by examining the institutional, technical, and legal challenges in comparison with developed countries. The findings indicate that weak legal requirements, the absence of an integrated data acquisition system, limited equipment, and a shortage of exploratory wells have led to reduced accuracy in baseline studies, weakened numerical models, and unstable decision-making. Additionally, the paper reviews the historical development of exploratory drilling and pumping tests, along with their tools and objectives, emphasizing the role of exploratory wells in developing conceptual models and monitoring aquifer dynamics under declining water table conditions. In conclusion, the article highlights the need to revise policymaking, strengthen institutional structures, and mandate the implementation of precise tests to achieve evidence-based water governance.

3D modeling to determine the geomechanical parameters of the Asmari reservoir and the principal stresses in one of the fields in southwestern Iran

Mehdi Talkhablou

Complex carbonate reservoirs, such as the Asmari Formation, present challenges to the accurate determination of geomechanical parameters and effective stresses due to high lithological and structural heterogeneity. The objective of this study is to develop a comprehensive three-dimensional model of geomechanical parameters and effective stresses in the Kupal oil field. Well log, core, and seismic data were used, and three-dimensional modeling was performed using the Sequential Gaussian Simulation (SGS) method based on variogram analysis. The prevailing stress regime was validated using FMI logs and wellbore breakout analysis. Additionally, a one-at-a-time sensitivity analysis was conducted on key parameters, including static Young’s modulus, Poisson’s ratio, cohesion, internal friction angle, and pore pressure. Results indicate that the maximum vertical effective stress (σ_v) is 87 MPa and the maximum horizontal effective stress (σH_max) is 127 MPa. Analysis of wellbore imaging data confirms a normal faulting stress regime (σ_v>σH_max>σh_min) in the field. Stress concentration around minor faults was also identified. The model was validated against one-dimensional models achieving 88% agreement. The findings of this study can be applied to well design, gas injection, and reservoir stability assessment in the Kupal field.

A study on the mechanism of freezing-thawing and salt crystallization processes in the deterioration of building stones

Amin Jamshidi

Stones are widely used for building facades, flooring, paving, stairs, kerbs and load-bearing components. Weathering processes can have adverse effects on stones in terms of their aesthetic and technical properties. Changes in these properties will lead to the stone deterioration, resulting in financial damage to the building from both architectural and structural perspectives. Understanding the mechanisms by which weathering processes cause stone deterioration can be as a useful and efficient tool for assessing the long-term durability behavior of stone during its service life in a building. This study systematically investigated the mechanisms of the freezing-thawing and salt crystallization processes in the building stones deterioration. To this end, published papers on the deterioration of building stones, including igneous, sedimentary, and metamorphic, due to freezing-thawing and salt crystallization processes were collected. Discussions performed on the mechanisms of freezing-thawing and salt crystallization reported in these papers from various perspectives were compared. The findings indicate that in each of these processes, more than one mechanism involved in the deterioration of building stone. In addition, results showed that depending on factors related to the surrounding environment of the stone and on the other hand, the inherent properties of the stone, various mechanisms will have different adverse effects in the deterioration of building stone.

Magnetic Data Inversion Optimization Using the Mountain Gazelle Optimization Algorithm: A Case Study of 2D Dipping Dykes

reza Toushmalani

Inversion of magnetic data to characterisegeological structures, such as dikes, is a fundamental challenge in engineering geophysics due to its highly non-linear and ill-posed nature, necessitating robust optimization methods. This study introduces and evaluates for the first time, the Mountain Gazelle Optimizer (MGO) for the first time, examining its efficiency and potential as an effective solution to this problem. The MGOalgorithm is designed to find the global optimum by intelligently balancing exploration and exploitation within the parameter space. The performance of the MGO was assessed by comparing it with two distinct approaches: a powerful machine learning algorithm called Random Forest (RF), and a classic processing-estimation method based on Reduction to the Pole (RTP). Evaluations were conducted on synthetic data (with noise levels ranging from 0% to 20%) as well as on real field data from the Gansu iron deposit in China. The results clearly demonstrated the superiority of MGO in all scenarios. Not only did the algorithm exhibit greater stability against noise than RF, it also, achieved a Root Mean Square Error (RMSE) of 0.48 in the real data case study,, which was significantly lower than the error achieved by the classic method (0.88). Furthermore, the parameters estimated by MGO showed better alignment with the geological information from existing drilling data in the area. This study suggests that MGO's superiority obtained from its direct and global inversion approach. Ultimately, MGO is presented as an accurate and reliable tool for exploration and engineering applications.

Prediction of the Strength Characteristics of Limestones in the Sanandaj – Sirjan Zone Using Statistical Methods and Neural Network

Gholam Reza Lashkaripour

The Sanandaj–Sirjan Structural-Sedimentary Zone is one of the most important geological regions in Iran. The limestone formations in this area play a key role in civil engineering and mining projects. Knowing the precise mechanical properties of these rocks, especially the uniaxial compressive strength (UCS dry) and dry point load index (Is₅₀-dry), is essential for safely and economically designing structures. Because direct testing methods are costly and time-consuming, this study uses indirect modeling techniques, such as regression and neural networks, to predict these properties. First, a comprehensive database was compiled by collecting the physical, mechanical, dynamic, and chemical data of limestone samples from the region. Then, univariate, bivariate, and multivariate regression analyses were conducted to extract statistical relationships among the variables. Finally, multilayer perceptron neural network models with various architectures based on the Levenberg–Marquardt learning algorithm were developed. The comparison results of the model performance indicated that neural networks, due to their ability to identify complex and nonlinear relationships between parameters, provide more accurate predictions of the limestone mechanical properties compared to statistical models. A comparison of the correlation coefficients of multivariate regression equations and neural network models showed that, overall, using neural network models improves the accuracy of UCS Dry predictions by 14.89% and the Is ₅₀-Dry predictions by 4.70%. The results show that predicting UCS Dry in the presence of Is ₅₀-Dry among the input parameters has a significant impact on improving the accuracy of the models. For example, the model with the inputs Is ₅₀-Dry, SH, γ Dry and n showed very good performance. For predicting Is ₅₀-Dry, the models that included the parameters SDI1 and BI Dry as inputs also performed very well. The application of these models can contribute to cost reduction, increased speed of rock engineering studies, and improved safety in civil projects.