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Open research questions in Seismic Imaging and Inversion Techniques

90 gap statements mined from Seismic Imaging and Inversion Techniques papers in our 4.5M-paper local library, which holds 1,094 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.

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What the literature leaves open

  • Future research should focus on incorporating multi-attribute classification, refining rock physics constraints, and extending the probabilistic workflow to other Nile Delta concessions. Similarly, deterministic seismic inversion is inherently limited by the vertical resolution of the input seismic data; the inversion results cannot exceed this resolution.

    Probabilistic 3D lithology classification from elastic property volumes an advanced inversion workflow at Desouq Gas Field, West Nile Delta, Egypt · 2026 · DOI

  • Further studies can be conducted to apply the approach to other oilfields. Additional research can be done to improve the accuracy of predictions of remaining oil and gas.

    Analysis of Rock Physics Variation Patterns and Time-Lapse Seismic Response Characteristics · 2026 · DOI

  • The application of machine learning in wave propagation modeling is a relatively new area of research. There is a need to explore the potential of machine learning in seismology.

    Machine learning in wave propagation modeling: From standard numerical methods to physics-informed neural networks in seismology · 2026 · DOI

  • The limited resources on edge devices pose significant challenges to achieving high software efficiency and low latency. Traditional FWI methods rely on physics-driven approaches that demand substantial computational resources.

    DiGiT: A Diffusion-based Modular Geophysical Toolkit for On-device Multi-modal Data Generation · 2026 · DOI

  • Future work will focus on introducing more robust multi-scale dip or structural tensor estimates and conducting key parameter perturbation experiments to enhance cross-regional generalizability and reproducibility, while incorporating parallel implementations to improve large-scale data processing efficiency.

    Structure-Guided Directional-Decomposition Lp–L2 Regularization for Prestack Multi-Parameter Seismic Inversion · 2026 · DOI

  • The need for a sparse seismic acquisition design without losing data fidelity.

    Compressive sensing based seismic data acquisition a case study in northeast China · 2026 · DOI

  • Targeting reservoirs below seismic resolution is a primary challenge in reservoir characterization. The difficulty of identifying thin-sand bodies in the Guantao Formation.

    Thin-bed reservoir characterisation using high-resolution ocean-bottom-node seismic data, seismic waveform indication inversion, and a Gaussian mixture model: A case study from the Guantao Formation, Bohai Bay Basin, China · 2026 · DOI

  • The approach aims to address this gap by using a multi-attribute machine learning workflow.

    Facies classification and channel detection for reservoir characterization using self-organizing maps in geologically complex groningen gas field, The Netherlands · 2026 · DOI

  • The method is tested on synthetic data and a limited number of real field data samples. The generalization to real field data is confirmed, but further testing is required.

    DANTE: Physics-Informed Neural Operator for DAS-to-Velocity Waveform Reconstruction Without Co-located Seismometers · 2026

  • While the proposed NWT algorithm demonstrates strong performance across the tested logging datasets, several physical limitations remain to be addressed in subsequent research.

    Neighborhood Width Transform: A Structural Stability Framework for Peak Selection in Noisy 1D Coherence Curves · 2026 · DOI

  • The assumption of a horizontally layered medium in down-down deconvolution methods is a limitation. The need for a generalization of the theory to arbitrarily inhomogeneous media is a research gap.

    Representations for multidimensional down-down deconvolution of ocean-bottom seismic data: Theory and practical implications · 2026 · DOI

  • Complete tilted transversely isotropic reprocessing is often constrained by anisotropic parameter estimation, access to original seismic data, and computational cost. The method is evaluated using a synthetic model and two field datasets, but more datasets may be needed to further validate the method.

    Enhancement of isotropic pre-stack depth migration guided by a tilted transversely isotropic model using a gated residual network · 2026 · DOI

  • Future research may focus on evaluating the method using more datasets. Future research may focus on improving the accuracy of the method under more complex conditions. Future research may focus on applying the method to other seismic imaging applications.

    Enhancement of isotropic pre-stack depth migration guided by a tilted transversely isotropic model using a gated residual network · 2026 · DOI

  • The gap is the lack of a method to provide a qualitative estimation of the current model's suitability for FWI.

    Full-Waveform Inversion Cycle-Skipping Mitigation with Dynamic Time Warping, Part 1: A Method for a Proximity Analysis Between the Current and the Observed Data · 2026 · DOI

  • This paper is Part 1 of a study that explores the potential of using the Dynamic Time Warping (DTW) methodology to address cycle-skipping with a focus on underinvestigated approaches.

    Full-Waveform Inversion Cycle-Skipping Mitigation with Dynamic Time Warping, Part 1: A Method for a Proximity Analysis Between the Current and the Observed Data · 2026 · DOI

  • It is recommended to integrate real-time LMO QC during acquisition, employ GPS-based dynamic positioning system, seasonal planning of acquisition campaigns, automate geometry verification using AI-Assisted LMO Tools.

    Evaluating Linear Moveout Effectiveness in Detecting 3-D Seismic Survey Geometry Errors in Chad Basin, Nigeria · 2026 · DOI

  • The scope of the experiments was limited due to low permeability of some cores. Some cores were prone to structural collapse or damage during saturation or pressurization processes.

    Analysis of Rock Physics Variation Patterns and Time-Lapse Seismic Response Characteristics · 2026 · DOI

  • The LSRTM method is time-consuming and memory-intensive. The method suffers from oversampling/aliasing when modeling deeper subsurface zones.

    On the Steadfastness of the Least-Square Reverse-Time Migration Wavefield Extrapolation via 1st-Order Riemannian Axis Finite-Difference Solver · 2026 · DOI

  • Conventional FWI based on the L2 metric requires strict point-by-point matching between signals.

    Multi-parameter full waveform inversion based on optimal transport distance in VTI media · 2026 · DOI

  • Restoring the missing portions of the band-limited seismic wavelet. Attenuating residual noise without degrading the broad-band geological signal.

    WigglePy: a QGIS‑integrated workflow for converting raster legacy seismic profiles into SEG‑Y format · 2026 · DOI

  • The limited resources on edge devices. The high computation costs due to the high resolution of the input. The large number of timesteps in the diffusion model.

    DiGiT: A Diffusion-based Modular Geophysical Toolkit for On-device Multi-modal Data Generation · 2026 · DOI

  • The requirement for mass conservation in the classical quadratic Wasserstein metric. The limitation of the least-square norm L2 in measuring the data misfit.

    Full-Waveform Inversion with Unbalanced Optimal Transport Metric for Seismic Imaging · 2026 · DOI

  • To extend the CS method to 3D acquisition. To apply the CS method to other types of seismic data. To further improve the reconstruction algorithm and reduce costs.

    Compressive sensing based seismic data acquisition a case study in northeast China · 2026 · DOI

  • Further testing of the method on a larger number of real field data samples. Investigation of the method's performance in different seismic environments and applications.

    DANTE: Physics-Informed Neural Operator for DAS-to-Velocity Waveform Reconstruction Without Co-located Seismometers · 2026

  • Further studies on the seismic hazards of the Isparta Basin. Investigations into the effects of sedimentary sequences on ground-motion characteristics during earthquakes. Application of the 2-D Fourier-based spectral filtering and local optimisation-based inversions to other sedimentary basins.

    Estimation of Basement Relief in the Isparta Basin by Applying Spectral Filtering and Local Optimisation-Based Inversion Techniques to Gravity Data · 2026 · DOI

Most-cited papers in Seismic Imaging and Inversion Techniques

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Open questions raised by papers listed on this page include: (1) Future research should focus on incorporating multi-attribute classification, refining rock physics constraints, and extending the probabilistic workflow to other Nile Delta concessions (“Probabilistic 3D lithology classification from elastic property volumes an…”, 2026); (2) There is a need to explore the potential of machine learning in seismology (“Machine learning in wave propagation modeling: From standard numerical methods…”, 2026); (3) While the proposed NWT algorithm demonstrates strong performance across the tested logging datasets, several physical limitations remain to be addressed in subsequent research (“Neighborhood Width Transform: A Structural Stability Framework for Peak…”, 2026); (4) Future research may focus on evaluating the method using more datasets (“Enhancement of isotropic pre-stack depth migration guided by a tilted…”, 2026). 90 gap statements have been mined from Seismic Imaging and Inversion Techniques papers in our 4.5M-paper local library, which holds 1,094 papers on the topic; the gaps come from whichever of those papers state one. They are mostly the research gaps the authors state and the papers' abstracts, plus future-work, limitations and challenges passages. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one, so you can read the original claim in context.

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