WaveInsight: A Source-Independent Full Waveform Inversion Application for Seismic Modeling

Asido Saputra Sigalingging; Ignatius Sonny Winardhi; Handoyo

doi:10.25299/jgeet.2025.10.4.24921

Authors

Asido Saputra Sigalingging Geophysical Engineering, Institut Teknologi Sumatera, South Lampung, Lampung, Indonesia
Ignatius Sonny Winardhi Geophysical Engineering, Institut Teknologi Bandung, Bandung, west Java, Indonesia
Handoyo Geophysical Engineering, Institut Teknologi Sumatera, South Lampung, Lampung, Indonesia

DOI:

https://doi.org/10.25299/jgeet.2025.10.4.24921

Keywords:

Full Waveform Inversion, Source-Independent FWI, Seismic Modeling

Abstract

Full Waveform Inversion (FWI) is a key method in seismic exploration due to its ability to generate high-resolution subsurface velocity models. However, its success is highly dependent on the accuracy of the source wavelet, an incorrect wavelet estimation can lead to unstable inversion results. To overcome this limitation, Source-Independent FWI (SI-FWI) has been developed, which eliminates the need for precise source wavelet information. This study introduces WaveInsight, an application that efficiently implements SI-FWI using the Julia programming language, with Python integration via Devito for wave simulation. The application features a Streamlit-based graphical user interface, enabling users to perform a complete FWI workflow, including data preparation, initial model generation, and inversion. Experiments on synthetic Overthrust data compare three objective functions: Student-t, Mean Squared Error (MSE), and SI-FWI. The results show that SI-FWI outperforms conventional approaches under wavelet uncertainty, Student-t is more robust to noise, while MSE performs well with clean data. Thus, WaveInsight demonstrates its dual role as both an educational platform and a promising tool for advancing geophysical research and industrial applications.

Downloads

Download data is not yet available.

References

Akmal, F., Dzulizar, M.C.R., Rafli, M.F., Az-Zahra, F., Haq, M.I.K., Dharmawan, I.A., 2023. Machine learning prediction of tortuosity in digital rock. Journal of Geoscience, Engineering, Environment, and Technology 8, 06–12.

Alkhalifah, T., Choi, Y., 2013. From tomography to full-waveform inversion with a single objective function. Geophysics 79, R55–R61.

Berkhout, A.J., 2012. Combining full wavefield migration and full waveform inversion, a glance into the future of seismic imaging. Geophysics 77.

Brittan, J., Jones, I., 2019. FWI evolution - From a monolith to a toolkit. Leading Edge 38, 179–184.

Choi, Y., Alkhalifah, T., 2011. Source-independent time-domain waveform inversion using convolved wavefields: Application to the encoded multisource waveform inversion. Geophysics 76.

Fichtner, A., Trampert, J., Cupillard, P., Saygin, E., Taymaz, T., Capdeville, Y., Villaseñor, A., 2013. Multiscale full waveform inversion. Geophys J Int 194, 534–556.

Geng, Y., Wu, R.S., Gao, J., 2011. Efficient Gaussian Packets representation and seismic imaging, in: Society of Exploration Geophysicists International Exposition and 81st Annual Meeting 2011, SEG 2011. pp. 3398–3403.

Hoving, R., Slot, G., Jansen, S., 2013. Python: Characteristics identification of a free open source software ecosystem. IEEE International Conference on Digital Ecosystems and Technologies 13–18.

Huang, R., Zhang, Z., Wu, Z., Wei, Z., Mei, J., Wang, P., 2021. Full-waveform inversion for full-wavefield imaging: Decades in the making. Leading Edge 40, 324–334.

Jaelani, L.M., Pangestu, M.A., 2023. Monitoring of Lake Water Quality Through Streamlit Web Application (Case Study: Lake Matano And Lake Towuti, South Sulawesi). Geoid 18, 293.

Jin, P., Feng, Y., Feng, S., Wang, H., Chen, Y., Consolvo, B., Liu, Z., Lin, Y., 2024. An empirical study of large-scale data-driven full waveform inversion. Sci Rep 14.

Khusnani, A., Anggraini, A., Jufriansah, A., Zulfakriza, Z., Pramudya, Y., Margiono, Wae, K.W., 2024. Relocation Study of Flores Sea Hypocenter (Mw = 7.3) Based on Single Station Estimation Using ObsPy. Journal of Geoscience, Engineering, Environment, and Technology 9, 113–120.

Krell, M.M., Straube, S., Seeland, A., Wöhrle, H., Teiwes, J., Metzen, J.H., Kirchner, E.A., Kirchner, F., 2013. PySPACE - A signal processing and classification environment in python. Front Neuroinform 7, 1–11.

Krischer, L., Megies, T., Barsch, R., Beyreuther, M., Lecocq, T., Caudron, C., Wassermann, J., 2015. ObsPy: A bridge for seismology into the scientific Python ecosystem. Comput Sci Discov 8, 0–17.

Luporini, F., Louboutin, M., Lange, M., Kukreja, N., Witte, P., Hückelheim, J., Yount, C., Kelly, P.H.J., Herrmann, F.J., Gorman, G.J., 2020. Architecture and performance of devito, a system for automated stencil computation. ACM Transactions on Mathematical Software 46.

Muhammad Razzaaq Al Ghiffari, Djoko Nugroho, Rachmat Ramadhan, Mochamad Rifat Noor, Noviarso Wicaksono, Agustan, 2024. The Utilization of LiCSBAS for Deformation Monitoring in Geresa Segment of Matano Fault, Central Sulawesi, Indonesia. Journal of Geoscience, Engineering, Environment, and Technology 9, 28–37.

Pladys, A., Brossier, R., Li, Y., Métivier, L., 2021. On cycle-skipping and misfit function modification for full-wave inversion: Comparison of five recent approaches. GEOPHYSICS 86, R563–R587.

Qi, Q., Huang, W., Zhang, D., Han, L., 2023. Robust Elastic Full-Waveform Inversion Based on Normalized Cross-Correlation Source Wavelet Inversion. Applied Sciences (Switzerland) 13.

Ruthotto, L., Treister, E., Haber, E., 2017. jInv--a Flexible Julia Package for PDE Parameter Estimation. SIAM Journal on Scientific Computing 39, S702–S722.

Shen, X., Ahmed, I., Brenders, A., Dellinger, J., Etgen, J., Michell, S., 2018. Full-waveform inversion: The next leap forward in subsalt imaging. Leading Edge 37, 67b1-67b6.

Sigalingging, A.S., Winardhie, I.S., Dinanto, E., 2021. Ekstrapolasi Frekuensi Rendah pada Full Waveform Inversion (FWI) dengan menggunakan Deep Learning. Part 1 : Validasi data Sintetik. Jurnal Geofisika 19, 74.

Sun, J., Innanen, K., Zhang, T., Trad, D., 2023. Implicit Seismic Full Waveform Inversion With Deep Neural Representation. J Geophys Res Solid Earth 128.

Tarantola, A., 1984. Linearized inversion of multioffset seismic reflection data, Geophysical Prospecting.

Tromp, J., 2020. Seismic wavefield imaging of Earth’s interior across scales. Nat Rev Earth Environ 1, 40–53.

Virieux, J., Operto, S., 2009. An overview of full-waveform inversion in exploration geophysics. Geophysics 74.

Winardhi, S., Sigalingging, A.S., Dinanto, E., 2025. Enhancing FWI convergence through self-supervised low-frequency extrapolation of legacy marine data: A case study from the Asri Basin, Indonesia. First Break 43, 73–79.

Winardhi, S., Sigalingging, A.S., Dinanto, E., 2024a. Application of Source Independent Full Waveform Inversion to Land Seismic Data: A Case Study of Donggi Field, Indonesia, in: IOP Conference Series: Earth and Environmental Science. Institute of Physics.

Winardhi, S., Sigalingging, A.S., Triyoso, W., Sukmono, S., Dinanto, E., Hendriyana, A., Wardaya, P.D., Septama, E., Raguwanti, R., 2024b. Deep learning-based Low Frequency Extrapolation: Its implication in 2D Full Waveform Imaging for marine seismic data in the Sadewa Field, Indonesia. First Break 42, 65–72.

Witte, P.A., Louboutin, M., Kukreja, N., Luporini, F., Lange, M., Gorman, G.J., Herrmann, F.J., 2019. A large-scale framework for symbolic implementations of seismic inversion algorithms in Julia. Geophysics 84, F57–F71.

Yang, Y., Engquist, B., 2018. Analysis of optimal transport and related misfit functions in full-waveform inversion. Geophysics 83, A7–A12.

Yao, G., Wu, D., Wang, S.X., 2020. A review on reflection-waveform inversion. Pet Sci.

Yatini, Y., Kustanto Putra, A., Paripurno, E.T., 2023. Application of HVSR Method on Microtremor Data for Analysis of Earthquake Potential in Candipuro District, Lumajang, Indonesia. Journal of Geoscience, Engineering, Environment, and Technology 8, 288–294.

Zhang, Q., Zhou, H., Li, Q., Chen, H., Wang, J., 2016. Robust source-independent elastic full-waveform inversion in the time domain. Geophysics 81, R29–R44.