Ning Wang

PhD Students

PhD Student

Current

Location:

B#1/L#3 – 3305-WS03

Social Profile:

Contact Information:

ning.wang.2@kaust.edu.sa

Biography

I am a PhD candidate in Geophysics at King Abdullah University of Science and Technology (KAUST), specializing in seismic processing, imaging, inversion, and machine learning (ML) techniques. My background includes an M.S. in 3-D anisotropic electromagnetic modeling, an Aramco internship, an invited EAGE workshop talk, and academic exchange at National University of Singapore and Nanyang Technological University.

Research Interests

seismic imaging, data processing, interferometry, machine learning, multiple elimination, full-waveform inversion, multi-dimensional deconvolution, seismic-while-drilling method

Selected Publications

Ning Wang, Matteo Ravasi, Marine Deheuvels, and Tariq Alkhalifah, “Application of Multi-Dimensional De-convolution to Enhance Seismic-While-Drilling Data Imaging”, DOI: 10.22541/essoar.174559302.21363958/v1.

Ning Wang, Matteo Ravasi, and Tariq Alkhalifah, “Efficient Upside-Down Rayleigh-Marchenko Imaging through Self-Supervised Focusing Function Estimation”, arXiv:2507.21561.

Ning Wang, and Tariq Alkhalifah, “A Deep-Learning-Driven Optimization-Based Inverse Solver for Accelerating the Marchenko Method”, arXiv:2509.16774.

Ning Wang, Matteo Ravasi, and Tariq Alkhalifah, 2025, “Accelerating Marchenko Imaging by Self-Supervised Prediction of Focusing Functions”, JGR: Machine Learning and Computation, vol. 2, no. 3, e2025JH000673.

Ning Wang, and Matteo Ravasi, 2025, “Imaging the Volve ocean-bottom field data with the upside-down Rayleigh-Marchenko method”, Geophysical Journal International , vol. 241, no. 2, 1432-1447.

Ning Wang, and Matteo Ravasi, 2024, “Upside-down Rayleigh-Marchenko: a practical redatuming scheme for seabed seismic acquisitions”, Geophysics, vol. 89, no. 6, 1-67.

Ning Wang, Changchun Yin, Lingqi Gao, Changkai Qiu, and Xiuyan Ren, 2023, “3-D anisotropic modeling of geomagnetic depth sounding based on unstructured edge-based finite-element method”, Geophysical Journal International , vol. 235, no. 1, 178-199.

Ning Wang, Changchun Yin, Lingqi Gao, Yang Su, Yunhe Liu, and Bin Xiong, 2020, “Airborne EM denoising based on curvelet transform”, Chinese Journal of Geophysics, vol. 63, no. 12, 4592-4603.

    Education

    • PhD in Earth Science and Engineering — KAUST, Saudi Arabia (2022–present)

    • MSc in Applied Geophysics — Jilin University, China (2019–2022)

    • BSc in Applied Geophysics — Jilin University, China (2015–2019)

    Professional Profile

    Ning’s work focuses on developing innovative seismic imaging and inversion methods using both physics-based and data-driven approaches. She specializes in Marchenko redatuming, Upside-Down Rayleigh–Marchenko imaging, multi-dimensional deconvolution (MDD), seismic-while-drilling data imaging and processing. Her recent work incorporates machine learning, including U-Net architectures, implicit neural representations, and plug-and-play regularization.

    Awards

    Outstanding Graduate  June 2022

    KAUST Affiliations

    Earth Science and Engineering

    Seismic Wave Analysis Group (SWAG)

    DeepWave Consortium

    Research Interests Keywords

    Seismic Imaging Seismic Processing Machine Learning FWI