AccScience Publishing / JSE / Online First / DOI: 10.36922/JSE025310048
ARTICLE

A fluid factor inversion method using the frequency-domain two-step sub-band regularization

Peng Zhang1 Ying Xiao1 Peng Xiao2,3* Pang Chen1 Wangyang Xu3
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1 Geophysical R&D Institute, Geophysical-COSL Oilfield Services Ltd., Tianjin, China
2 Sichuan Energy Investment Group Co., Ltd., Chengdu, Sichuan, China
3 Reservoir Geophysics Laboratory, School of Geoscience and Technology, Southwest Petroleum University, Chengdu, Sichuan, China
Submitted: 28 July 2025 | Revised: 23 September 2025 | Accepted: 11 October 2025 | Published: 30 October 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

In oil and gas seismic exploration, fluid factors are key parameters for identifying reservoir fluid properties and evaluating reservoir potential. Although regularization methods are commonly used to enhance inversion stability, traditional time–domain lateral constraint methods struggle to effectively address the issue of abrupt lateral stratigraphic variations. This paper aims to improve the prediction accuracy and stability of fluid factors in such scenarios. Based on the characteristic that frequency-domain seismic data exhibit stronger correlation during stratigraphic abrupt changes, this paper proposes a frequency-domain two-step sub-band regularization inversion method. First, a difference operator is introduced into the frequency domain to construct the objective function, and the Alternating Direction Method of Multipliers algorithm is adopted as the solution. Furthermore, a two-step sub-band regularization strategy is proposed: First, integrating low-frequency and high-frequency residual terms into the same objective function; then performing inversion in two stages. These stages first use low-frequency data inversion to obtain the general profile of the subsurface structure as an initial model, followed by using high-frequency data inversion based on this to obtain detailed information. Theoretical model tests have verified the superiority of this method under complex geological conditions. Field application in practical work areas shows that the frequency-domain two-step method significantly outperforms the traditional time–domain lateral constraint L1 regularization method in terms of vertical resolution and lateral continuity. This method provides a more accurate and stable solution for fluid identification under complex geological conditions.

Keywords
Frequency-domain regularization
Fluid factor
Lateral constraint
Alternating Direction Method of Multipliers
Pre-stack inversion
Funding
This work was supported in part by the Technology Cooperation Project of the CNPC-SWPU Innovation Alliance (2020C×020000) and in part by the Natural Science Foundation of Sichuan Province (24NSFSC0808).
Conflict of interest
The authors declare they have no competing interests.
References
  1. Smith GC, Gidlow PM. Weighted stacking for rock property estimation and detection of gas. Geophys Prospect. 1987;35(9):993-1014. doi: 10.1111/j.1365-2478.1987.tb00856.x

 

  1. Goodway B, Chen T, Downton J. Improved AVO fluid detection and lithology discrimination using lame petrophysical parameters; “λρ, μρ, λμ fluid stack”, From P and S inversions. SEG Ann Meet. 1997;22:183-186. doi: 10.1190/1.1885795

 

  1. Connolly P. Elastic impedance. Lead Edge. 1999; 18(4):438-438. doi: 10.1190/1.1438307

 

  1. Smith GC. The Fluid Factor Angle and the Crossplot Angle. SEG Annual Meeting. United States: Society of Exploration Geophysicists; 2003. doi: 10.1190/1.1817679

 

  1. Peng ZM, Li YL, Wu SH, He ZH, Zhou YJ. Discriminating gas and water using multi-angle extended elastic impedance inversion in carbonate reservoirs. Chin J Geophys. 2008;51(3):881-885. doi: 10.1002/cjg2.1253

 

  1. Zheng JJ, Yin XY, Zhang GZ. Fluid factor analysis and the construction of the new fluid factor. Prog Geophys. 2011;26(2):579-587. doi: 10.3969/j.issn.1004-2903.2011.02.024

 

  1. Zong Z, Yin X, Wu G. Direct inversion for a fluid factor and its application in heterogeneous reservoirs. Geophys Prospect. 2013;61(5):998-1005. doi: 10.1111/1365-2478.12038

 

  1. Yin X, Zong Z, Wu G. Research on seismic fluid identification driven by rock physics. Sci China Earth Sci. 2015;58(2):159-171. doi: 10.1007/s11430-014-4992-3

 

  1. Li C, Zhang JM, Zhu ZY. Direct inversion method for fluid factor in deep reservoirs. Petrol Geophys Prospect. 2017;56(6):827-834. doi: 10.3969/j.issn.1000-1441.2017.06.008

 

  1. Jiang Z, Xiong Y. Seismic inversion for fluid bulk modulus based on elastic impedance. J Appl Geophys. 2019;169:74-84. doi: 10.1016/j.jappgeo.2019.06.013

 

  1. Liu C, Ghosh DP, Salim AMA, Chow WS. A new fluid factor and its application using a deep learning approach. Geophys Prospect. 2019;67(1):140-149. doi: 10.1111/1365-2478.12712

 

  1. Li K, Yin XY, Zong ZY. Facies-constrained prestack seismic probabilistic inversion driven by rock physics. Sci China Earth Sci. 2020;50(6):832-854. doi: 10.1007/s11430-019-9578-1

 

  1. Farfour M, Castagna JP. A new expression for fluid factor using AVO intercept and gradient. Soc Explor Geophys. 2021;9(1):267-271. doi: 10.1190/segam2021-3575102.1

 

  1. Wu HB, Wu RX, Zhang PS, Huang Y, Dong S. Combined fluid factor and brittleness index inversion for coal-measure gas reservoies. Geophys Prospect. 2022;70(4):751-764. doi: 10.1111/1365-2478.13172

 

  1. Zhou L, Liao JP, Liu XY, Wang P, Guo YN, Li JY. A high resolution inversion method for fluid factor with dynamic dry-rock VP/VS ratio squared. Petrol Sci. 2023;20(5):2822-2834. doi: 10.1016/j.petsci.2023.09.015

 

  1. Ruyi Z, Huan W, Yongqiang M, Jianhua T, Chao H, Maoqiang Z. Fluid factor inversion based on Q elastic impedance. Geophys Prospect Petrol. 2024;63(4):826-832. doi: 10.12431/issn.1000-1441.2024.63.04.011

 

  1. Pan F, Li SJ, Qin DW, et al. Direct inversion method for fluid factor and anisotropic parameters in VTI media. Oil Geophys Prospect. 2024;59(4):875-886. doi: 10.13810/j.cnki.issn.1000-7210.2024.04.025

 

  1. Tikhonov AN. On the stability of inverse problems. Dokl Akad Nauk Sssr. 1943;39(5):195-198.

 

  1. Tikhonov AN. Solution of incorrectly formulated problems and the regularization method. Sov Math Dok. 1963;4:1035-1038.

 

  1. Rudin LI, Osher S, Fatemi E. Nonlinear total variation based noise removal algorithm. Phys D Non Phenom. 1992;60(4):259-268. doi: 10.1016/0167-2789(92)90242-F

 

  1. Zou H, Hastie T. Regularization and variable selection via the elastic net. J Roy Statis Soc. 2005;67(2):301-301. doi: 10.1111/j.1467-9868.2005.00503.x

 

  1. Gholami A. Nonlinear multichannel impedance inversion by total-variation regularization. Geophysics. 2015;80(5):217-224. doi: 10.1190/geo2015-0004.1

 

  1. Ruixue S, Liguo H, Eryan S, et al. Dual-parameter shaping regularized full waveform inversion in frequency domain. Glob Geol. 2015;18(4):258-262. doi: 10.3969/j.issn.1673-9736.2015.04.09

 

  1. Mousavi SM, Langston CA, Horton SP. Automatic microseismic denoising and onset detection using the synchrosqueezed continuous wavelet transform. Geophysics. 2016;81(4):341-355. doi: 10.1190/geo2015-0598.1

 

  1. Pan S, Chen Y, Yin C, Gou Q, Zhang D. Prestack inversion method with ATpV regularization based on reweighted L1. J S Petrol Univ Sci Technol. 2024;46(3):13-26. doi: 10.11885/j.issn.1674-5086.2022.08.20.02

 

  1. Wang D, Zhang YM, Niu C, et al. The optimization of sensitive fluid factor removing the effect of porosity and its application to hydrocarbon detection. Geophys Geochem Explor. 2021;45(6):1402-1408. doi: 10.11720/wtyht.2021.1364
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Journal of Seismic Exploration, Print ISSN: 0963-0651, Published by AccScience Publishing