Sadegh Karimpouli
YOU?
Author Swipe
View article: MaxMagMod: A Web-Based Application for Next Largest Magnitude Forecasting in Enhanced Geothermal Systems
MaxMagMod: A Web-Based Application for Next Largest Magnitude Forecasting in Enhanced Geothermal Systems Open
Enhanced geothermal systems offer a promising solution for sustainable energy by injecting water into hot underground reservoirs to generate electricity or heat. However, the process often induces significant seismic activity, posing chall…
View article: Forecasting induced seismicity in enhanced geothermal systems using machine learning: challenges and opportunities
Forecasting induced seismicity in enhanced geothermal systems using machine learning: challenges and opportunities Open
SUMMARY Induced seismicity poses a significant challenge to the safe and sustainable development of Enhanced Geothermal Systems (EGS). This study explores the application of machine learning (ML) for forecasting cumulative seismic moment (…
View article: Empowering Machine Learning Forecasting of Labquake Using Event‐Based Features and Clustering Characteristics
Empowering Machine Learning Forecasting of Labquake Using Event‐Based Features and Clustering Characteristics Open
Following recent advances of machine learning (ML), we present a novel approach to extract spatiotemporal seismo‐mechanical features from Acoustic Emission (AE) catalogs to empower ML‐based forecasting. The AE data were recorded during lab…
View article: Event-based features: An improved feature extraction approach to enrich machine learning based labquake forecasting
Event-based features: An improved feature extraction approach to enrich machine learning based labquake forecasting Open
Earthquake forecasting is a highly complex and challenging task in seismology ultimately aiming to save human lives and infrastructures. In recent years, Machine Learning (ML) methods have demonstrated progressive achievements in earthquak…
View article: Unsupervised clustering of catalogue-driven features for characterizing temporal evolution of labquake stress
Unsupervised clustering of catalogue-driven features for characterizing temporal evolution of labquake stress Open
SUMMARY Earthquake forecasting poses significant challenges, especially due to the elusive nature of stress states in fault systems. To tackle this problem, we use features derived from seismic catalogues obtained from acoustic emission (A…
View article: Analysis of Interlayer Bonding and Pore Structure of 3d-Printed Lightweight Cementitious Mortarsanalysis of Interlayer Bonding and Pore Structure of a 3d-Printed Cementitious Mortar with Recycled Lightweight Aggregates
Analysis of Interlayer Bonding and Pore Structure of 3d-Printed Lightweight Cementitious Mortarsanalysis of Interlayer Bonding and Pore Structure of a 3d-Printed Cementitious Mortar with Recycled Lightweight Aggregates Open
View article: Explainable machine learning for labquake prediction using catalog-driven features
Explainable machine learning for labquake prediction using catalog-driven features Open
View article: Applicability of 2D algorithms for 3D characterization in digital rocks physics: an example of a machine learning-based super resolution image generation
Applicability of 2D algorithms for 3D characterization in digital rocks physics: an example of a machine learning-based super resolution image generation Open
Digital rock physics is based on imaging, segmentation and numerical computations of rock samples. Due to challenges regarding the handling of a large 3-dimensional (3D) sample, 2D algorithms have always been attractive. However, in 2D alg…
View article: Feasibility Study of Three-Dimensional Crack Growth Modeling in Porous Media with Circular Pores Using Two-Dimensional Sections
Feasibility Study of Three-Dimensional Crack Growth Modeling in Porous Media with Circular Pores Using Two-Dimensional Sections Open
با توجه به پیچیدگیهای مطالعات آزمایشگاهی رشد ترک در مقیاس حفره، روشهای عددی متعددی در تحلیل مسایل محیطهای متخلخل استفاده شده است. این روشها، در مورد نمونههای سه بعدی حجیم با هزینههای محاسباتی زیادی همراه است. بنابراین، ارائه روشهایی…
View article: Application of Remote Sensing and Field Geophysics for Exploration of Cu Deposits in Bab-Zangoeie, Chahar-Gonbad Region of Kerman, Iran
Application of Remote Sensing and Field Geophysics for Exploration of Cu Deposits in Bab-Zangoeie, Chahar-Gonbad Region of Kerman, Iran Open
Application of Remote Sensing and Field Geophysics for Exploration of Cu Deposits in Bab-Zangoeie, Chahar-Gonbad Region of Kerman, Iran
View article: Ultrasonic prediction of crack density using machine learning: A numerical investigation
Ultrasonic prediction of crack density using machine learning: A numerical investigation Open
Cracks are accounted as the most destructive discontinuity in the rock, soil, and concrete. Enhancing our knowledge from their properties such as crack distribution, density, and/or aspect ratio is crucial in geo-systems. The most well-kno…
View article: Single-Station Coda Wave Interferometry: A Feasibility Study Using Machine Learning
Single-Station Coda Wave Interferometry: A Feasibility Study Using Machine Learning Open
Coda wave interferometry usually is applied with pairs of stations analyzing the signal transmitted from one station to another. A feasibility study was performed to evaluate if one single station could be used. In this case, the reflected…
View article: Physics informed machine learning: Seismic wave equation
Physics informed machine learning: Seismic wave equation Open
View article: Comments to "Characterization of fractures in potential reservoir rocks for geothermal applications in the Rhine-Ruhr metropolitan area (Germany)" by Balcewicz et al.
Comments to "Characterization of fractures in potential reservoir rocks for geothermal applications in the Rhine-Ruhr metropolitan area (Germany)" by Balcewicz et al. Open
The paper is about evaluation of potential geothermal reservoirs using field and lab data.The topic is high demanding and interesting for a broad range of communities.Data were surveyed and measured accurately, which worth to be published.…
View article: A review of experimental and numerical modeling of digital coalbed methane: Imaging, segmentation, fracture modeling and permeability prediction
A review of experimental and numerical modeling of digital coalbed methane: Imaging, segmentation, fracture modeling and permeability prediction Open
View article: Stochastic modeling of coal fracture network by direct use of micro-computed tomography images
Stochastic modeling of coal fracture network by direct use of micro-computed tomography images Open
View article: Using a Feature Subset Selection method and Support Vector Machine to address curse of dimensionality and redundancy in Hyperion hyperspectral data classification
Using a Feature Subset Selection method and Support Vector Machine to address curse of dimensionality and redundancy in Hyperion hyperspectral data classification Open
View article: High performance of the support vector machine in classifying hyperspectral data using a limited dataset
High performance of the support vector machine in classifying hyperspectral data using a limited dataset Open
To prospect mineral deposits at regional scale, recognition and classification of hydrothermal alteration zones using remote sensing data is a popular strategy. Due to the large number of spectral bands, classification of the hyperspectral…
View article: Automated diffraction delineation using an apex-shifted Radon transform
Automated diffraction delineation using an apex-shifted Radon transform Open
Diffraction arrivals are important data that have increasingly been used to delineate the sources of diffractors and to explore subsurface discontinuities. In prestack data, diffractions are both zero- and non-zero offset hyperbolas while …