173 citations · 338 across the 16 of their papers we have counts for
18 papers
SeisCoDE: 3D Seismic Interpretation Foundation Model with Contrastive Self-Distillation Learning
Goodluck Archibong, Ardiansyah Koeshidayatullah, Umair Waheed +3
Seismic interpretation is vital for understanding subsurface structures but remains labor-intensive, subjective, and computationally demanding. While deep learning (DL) offers prom…
Recursions Are All You Need: Towards Efficient Deep Unfolding Networks
Rawwad Alhejaili, Motaz Alfarraj, Hamzah Luqman +1
The use of deep unfolding networks in compressive sensing (CS) has seen wide success as they provide both simplicity and interpretability. However, since most deep unfolding networ…
Meta-Optimization of Deep CNN for Image Denoising Using LSTM
Basit O. Alawode, Motaz Alfarraj
The recent application of deep learning (DL) to various tasks has seen the performance of classical techniques surpassed by their DL-based counterparts. As a result, DL has equally…
Joint Learning for Spatial Context-based Seismic Inversion of Multiple Datasets for Improved Generalizability and Robustness
Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
Seismic inversion plays a very useful role in detailed stratigraphic interpretation of seismic data. Seismic inversion enables estimation of rock properties over the complete seism…
Spatiotemporal Modeling of Seismic Images for Acoustic Impedance Estimation
Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
Seismic inversion refers to the process of estimating reservoir rock properties from seismic reflection data. Conventional and machine learning-based inversion workflows usually wo…
Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset
Yuting Hu, Zhiling Long, Anirudha Sundaresan +4
Tactile sensing or fabric hand plays a critical role in an individual's decision to buy a certain fabric from the range of available fabrics for a desired application. Therefore, t…
Semi-supervised Sequence Modeling for Elastic Impedance Inversion
Motaz Alfarraj, Ghassan AlRegib
Recent applications of machine learning algorithms in the seismic domain have shown great potential in different areas such as seismic inversion and interpretation. However, such a…
Estimation of Acoustic Impedance from Seismic Data using Temporal Convolutional Network
Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
In exploration seismology, seismic inversion refers to the process of inferring physical properties of the subsurface from seismic data. Knowledge of physical properties can prove…
Semi-supervised Learning for Acoustic Impedance Inversion
Motaz Alfarraj, Ghassan AlRegib
Recent applications of deep learning in the seismic domain have shown great potential in different areas such as inversion and interpretation. Deep learning algorithms, in general,…
Structure Label Prediction Using Similarity-Based Retrieval and Weakly-Supervised Label Mapping
Yazeed Alaudah, Motaz Alfarraj, Ghassan AlRegib
Recently, there has been significant interest in various supervised machine learning techniques that can help reduce the time and effort consumed by manual interpretation workflows…
3D Curvature Analysis of Seismic Waveforms and its Interpretational Implications
Haibin Di, Motaz Alfarraj, Ghassan AlRegib
The idea of curvature analysis has been widely used in subsurface structure interpretation from three-dimensional (3D) seismic data (e.g., fault/fracture detection and geomorpholog…
Multiscale Fusion for Seismic Geometric Attribute Enhancement
Motaz Alfarraj, Haibin Di, Ghassan AlRegib
In this abstract, we propose a multiscale fusion technique to enhance seismic geometric attributes, such as dip and curvature, which are very sensitive to noise present in seismic…
Petrophysical Property Estimation from Seismic Data Using Recurrent Neural Networks
Motaz Alfarraj, Ghassan AlRegib
Reservoir characterization involves the estimation petrophysical properties from well-log data and seismic data. Estimating such properties is a challenging task due to the non-lin…
Multiresolution Analysis and Learning for Computational Seismic Interpretation
Motaz Alfarraj, Yazeed Alaudah, Zhiling Long +1
We explore the use of multiresolution analysis techniques as texture attributes for seismic image characterization, especially in representing subsurface structures in large migrat…
A Machine Learning Benchmark for Facies Classification
Yazeed Alaudah, Patrycja Michalowicz, Motaz Alfarraj +1
The recent interest in using deep learning for seismic interpretation tasks, such as facies classification, has been facing a significant obstacle, namely the absence of large publ…
Subsurface structure analysis using computational interpretation and learning: A visual signal processing perspective
G. AlRegib, M. Deriche, Z. Long +5
Understanding Earth's subsurface structures has been and continues to be an essential component of various applications such as environmental monitoring, carbon sequestration, and…
A comparative study of texture attributes for characterizing subsurface structures in seismic volumes
Zhiling Long, Yazeed Alaudah, Muhammad Ali Qureshi +8
In this paper, we explore how to computationally characterize subsurface geological structures presented in seismic volumes using texture attributes. For this purpose, we conduct a…
Content-adaptive non-parametric texture similarity measure
Motaz Alfarraj, Yazeed Alaudah, Ghassan AlRegib
In this paper, we introduce a non-parametric texture similarity measure based on the singular value decomposition of the curvelet coefficients followed by a content-based truncatio…