Advances in Integrated Prediction Methods for Complex Volcanic Reservoirs and Their Applications

Jiaheng Pan

doi:10.54254/2755-2721/2025.MH27973

Applied and Computational EngineeringOpen access

Advances in Integrated Prediction Methods for Complex Volcanic Reservoirs and Their Applications

Research Article

Open Access

Advances in Integrated Prediction Methods for Complex Volcanic Reservoirs and Their Applications

Jiaheng Pan ^1*

¹ China University of Geosciences

^*Corresponding author: panjheng@qq.com

Published on 22 October 2025

ACE Vol.198

ISSN (Print): 2755-273X

ISSN (Online): 2755-2721

ISBN (Print): 978-1-80590-469-4

ISBN (Online): 978-1-80590-470-0

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Abstract

Volcanic reservoirs represent a significant domain in global hydrocarbon exploration, characterized by substantial resource potential yet considerable exploration challenges. These reservoirs exhibit diverse storage types, complex pore structures, highly variable fracture development, and strong heterogeneity, which render conventional exploration methods inadequate for effective prediction. This paper provides a systematic review of recent advances in the study of volcanic reservoirs, focusing on rock physical characteristic analysis, well-log interpretation, seismic inversion techniques, and integrated prediction using multi-scale data. The applications and limitations of existing technologies are summarized. Research indicates that the identification of sensitive parameters based on rock physical analysis offers a theoretical foundation for reservoir prediction. Techniques such as pre-stack geostatistical inversion have significantly enhanced the accuracy of volcanic reservoir characterization. Moreover, the integration of multi-disciplinary data and facies-controlled modeling has considerably improved the reliability of reservoir predictions. Nevertheless, current research still suffers from insufficient understanding of reservoir formation mechanisms, limited integration of multi-scale data, and a lack of generalizability in predictive models. Future studies should focus on developing intelligent prediction technologies leveraging interdisciplinary approaches and deepening quantitative evaluation and geological modeling of volcanic reservoirs to facilitate efficient exploration and development.

Keywords:

Volcanic Reservoir, Rock physics Characteristics, Seismic Inversion, Integrated Multi-Scale Prediction, Reservoir Prediction

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References

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References

[2]. Khalili, Y., & Ahmadi, M. (2023). Reservoir modeling & simulation: Advancements, challenges, and future perspectives. Journal of Chemical and Petroleum Engineering, 57(2), 343-364.

[9]. Tang, H., & Ji, H. (2006). Incorporation of spatial characteristics into volcanic facies and favorable reservoir prediction. SPE Reservoir Evaluation & Engineering, 9(05), 565-573.

[12]. Zhang, Z. M. (2016). Seismic Interpretation and Reservoir Prediction of Yingcheng Formation in Xingshan Area. Northeast Petroleum University.

[13]. Acocella, V., Ripepe, M., Rivalta, E., Peltier, A., Galetto, F., & Joseph, E. (2024). Towards scientific forecasting of magmatic eruptions. Nature Reviews Earth & Environment, 5(1), 5-22.

Cite this article

Pan,J. (2025). Advances in Integrated Prediction Methods for Complex Volcanic Reservoirs and Their Applications. Applied and Computational Engineering,198,1-9.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of CONF-FMCE 2025 Symposium: AI and Machine Learning Applications in Infrastructure Engineering

ISBN: 978-1-80590-469-4(Print) / 978-1-80590-470-0(Online)

Editor: Anil Fernando, Manoj Khandelwal

Conference website: https://www.conffmce.org/mounthelen.html

Conference date: 24 September 2025

Series: Applied and Computational Engineering

Volume number: Vol.198

ISSN: 2755-2721(Print) / 2755-273X(Online)

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