AccScience Publishing / JSE / Online First / DOI: 10.36922/JSE025470118
ARTICLE

Seismic azimuthal amplitude variation with offset response analysis in coalbed methane reservoirs with aligned fractures using Biot theory

ZhaoJi Zhang1 Fei Gong1,2* GuanGui Zou1,2* Qiang Guo3 GuoWei Zhu1,2 Hao Li1
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1 Department of Geophysics, College of Geoscience and Surveying Engineering, China University of Mining and Technology–Beijing, Beijing, China
2 State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources, College of Geoscience and Surveying Engineering, China University of Mining and Technology–Beijing, Beijing, China
3 Department of Geophysics, School of Resources and Geosciences, China University of Mining and Technology, Xuzhou, Jiangsu, China
JSE 2026, 35(2), 025470118 https://doi.org/10.36922/JSE025470118
Submitted: 22 November 2025 | Revised: 3 February 2026 | Accepted: 10 February 2026 | Published: 4 March 2026
© 2026 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

The development of coalbed methane (CBM) relies on high-precision reservoir prediction and lithological inversion. Seismic amplitude variation with offset (AVO) technology is an important tool for fine-scale reservoir characterization. However, the seismic AVO response of CBM reservoirs is complex and is affected by seismic rock physics parameters at different scales. Microscopically, aligned fractures in CBM reservoirs produce complex anisotropy due to formation inclination. At the macroscopic scale, the thickness of CBM reservoirs within seismic frequency bands is comparable to the seismic wavelength and should therefore be treated as a layered medium. In addition, pore fluid significantly affects seismic wave propagation. Consequently, determining the azimuthal AVO response of CBM reservoirs in relation to seismic rock physics parameters at different scales can support high-precision reservoir prediction and lithological inversion. In this study, the primary–primary wave reflection coefficient for a two-phase layered medium was derived using Biot’s theory. Using this model, the response characteristics of the reflection coefficients with respect to seismic azimuth, aligned fracture parameters, reservoir thickness, and seismic main frequency were analyzed. A rotated staggered–grid finite–difference algorithm was employed to simulate wavefield characteristics separately for coal seams and surrounding strata. Seismic attributes were then used to characterize the seismic AVO response. The Z-direction seismic amplitude attributes and reflection coefficients showed similar trends in their responses to seismic rockphysical parameters. This study contributes to establishing a more precise seismic AVO response framework to support CBM reservoir prediction and high-quality lithological inversion.

Keywords
Azimuth
Amplitude variation with offset
Tilted transversely isotropic anisotropy
Fracture
Modeling
Funding
This study was supported by the National Natural Science Fund Projects (42274165,42474146), CNPC Innovation Fund (2024DQ02-0133), and the Fundamental Research Funds for the Central Universities (2024ZKPYDC03).
Conflict of interest
Fei Gong and Qiang Guo are Editorial Board Members of this journal, but were not in any way involved in the editorial and peer-review process conducted for this paper, directly or indirectly. The authors declare they have no competing interests.
References
[1]
  1. Pan J, Ge T, Liu W, et al. Organic matter provenance and accumulation of transitional facies coal and mudstone in Yangquan, China: Insights from petrology and geochemistry. J Nat Gas Sci Eng. 2021;94:104076. doi: 10.1016/j.jngse.2021.104076

 

  1. Zhang D, He H, Ren Y, et al. A mini review on biotransformation of coal to methane by enhancement of chemical pretreatment. Fuel. 2022;308:121961. doi: 10.1016/j.fuel.2021.121961

 

  1. Guo Z, Li X. Azimuthal AVO signatures of fractured poroelastic sandstone layers. Explor Geophys. 2017;48(1):56-66. doi: 10.1071/eg15050

 

  1. Hu H, Xia K, Hilterman F, Zhang Y. Amplitude-Versus-Angle Analysis of Local Angle-Domain Common Image Gathers With Prestack Gaussian-Beam Migration of Seismic Data. IEEE Trans Geosci Remote Sens. 2020;58(8):5969-5975. doi: 10.1109/TGRS.2020.2973654

 

  1. Wandler A, Evans B, Link C. AVO as a fluid indicator: A physical modeling study. Geophysics. 2007;72(1):C9-C17. doi: 10.1190/1.2392817

 

  1. Xu C, Chen C, Deng J, Di B, Wei J. A physical modelling study of the reservoir scale effect on amplitude variation with incidence angle. J Geophys Eng. 2019;16(6):1084-1093. doi: 10.1093/jge/gxz077

 

  1. Xiao K, Zou C, Shang J, Yang Y, Zhang H. Numerical simulation of AVO response characteristics from pore-filling gas hydrate in Qilian mountain permafrost, China. Arab J Geosci. 2019;12(12):379. doi: 10.1007/s12517-019-4548-0

 

  1. Gavin LJ, Lumley D. The effects of azimuthal anisotropy on 3D and 4D seismic amplitude variation with offset responses. Geophysics. 2019;84(6):C251-C267. doi: 10.1190/geo2018-0450.1

 

  1. Liu H, Ding P, Li X. Physical modeling of seismic responses in thin interbedded reservoirs with horizontal fracture. Chin J Geophys. 2021;64(8):2927-2940. doi: 10.6038/cjg2021O0167

 

  1. Xi Y, Yin X. Seismic Response Models and the AVO Simulation of Coal-Bearing Reservoirs. Minerals. 2022;12(7):836. doi: 10.3390/min12070836

 

  1. Kumar D, Zhao Z, Foster DJ, Dralus D, Sen MK. Frequency-dependent AVO analysis using the scattering response of a layered reservoir. Geophysics. 2020;85(2):N1-N16. doi: 10.1190/geo2019-0167.1

 

  1. Ahmed N, Weibull WW, Quintal B, Grana D, Bhakta T. Frequency-dependent AVO inversion applied to physically based models for seismic attenuation. Geophys J Int. 2022;233(1):234-252. doi: 10.1093/gji/ggac461

 

  1. Ouyang F, Liu XZ, Wang B, et al. The applicability and underlying factors of frequency-dependent amplitudeversus-offset (AVO) inversion. Pet Sci. 2023;20(4):2075-2091. doi: 10.1016/j.petsci.2023.02.011

 

  1. Tian Y, Stovas A, Gao J, Meng C, Yang C. Frequency-Dependent AVO Inversion and Application on Tight Sandstone Gas Reservoir Prediction Using Deep Neural Network. IEEE Trans Geosci Remote Sens. 2023;61:1-13. doi: 10.1109/tgrs.2023.3328183

 

  1. Chen SQ, Li XY, Wang SX. The analysis of frequency-dependent characteristics for fluid detection: a physical model experiment. Appl Geophys. 2012;9(2):195-206. doi: 10.1007/s11770-012-0330-8

 

  1. Si W, Di B, Wei J. Seismic response variation of tight gas sand for uniform and patchy saturation patterns. J Appl Geophys. 2015;116:167-172. doi: 10.1016/j.jappgeo.2015.03.010

 

  1. Wang X, Pan D. Application of AVO attribute inversion technology to gas hydrate identification in the Shenhu Area, South China Sea. Mar Pet Geol. 2017;80:23-31. doi: 10.1016/j.marpetgeo.2016.11.015

 

  1. Yadav A, Mondal S, Yadav J, Chakraborty S. Direct hydrocarbon indicator analysis to predict reservoir in Deepwater Krishna-Godavari basin: a case study. Explor Geophys. 2023;54(6):625-635. doi: 10.1080/08123985.2023.2236119

 

  1. Yang X, Cao S, Guo Q, Kang Y, Yu P, Hu W. Frequency-Dependent Amplitude Versus Offset Variations in Porous Rocks with Aligned Fractures. Pure Appl Geophys. 2016;174(3):1043-1059. doi: 10.1007/s00024-016-1423-8

 

  1. Castoro A, White RE, Thomas RD. Thin-bed AVO: Compensating for the effects of NMO on reflectivity sequences. Geophysics. 2001;66(6):1714-1720. doi: 10.1190/1.1487113

 

  1. Jin Z, Chapman M, Papageorgiou G, Wu X. Impact of frequency-dependent anisotropy on azimuthal P-wave reflections. J Geophys Eng. 2018;15(6):2530-2544. doi: 10.1088/1742-2140/aad882

 

  1. Saeed W, Zhang H, Guo Q, et al. An integrated petrophysical-based wedge modeling and thin bed AVO analysis for improved reservoir characterization of Zhujiang Formation, Huizhou sub-basin, China: A case study. Open Geosci. 2020;12(1):256-274. doi: 10.1515/geo-2020-0011

 

  1. Shi J, Wang S, Zhang H, et al. A novel method for formation evaluation of undersaturated coalbed methane reservoirs using dewatering data. Fuel. 2018;229:44-52. doi: 10.1016/j.fuel.2018.04.144

 

  1. Wang P, Yao Z, Peng S, Hu S. A novel approximate formula on AVAZ of reflection and transmission qP in TTI media. J Pet Sci Eng. 2020;192:107280. doi: 10.1016/j.petrol.2020.107280

 

  1. Xue J, Gu H, Cai C. Model-based amplitude versus offset and azimuth inversion for estimating fracture parameters and fluid content. Geophysics. 2017;82(2):M1-M17. doi: 10.1190/geo2016-0196.1

 

  1. Shi B, Wang P. Research on Stability Control of Shields at Working Face with Large Dip Angle. Energies. 2023;16(15):5813. doi: 10.3390/en16155813

 

  1. Tu H, Tu S, Yuan Y, Wang F, Bai Q. Present situation of fully mechanized mining technology for steeply inclined coal seams in China. Arab J Geosci. 2014;8(7):4485-4494. doi: 10.1007/s12517-014-1546-0

 

  1. Elkibbi M, Yang M, Rial JA. Crack-induced anisotropy models in The Geysers geothermal field. Geophys J Int. 2005;162(3):1036-1048. doi: 10.1111/j.1365-246x.2005.02697.x

 

  1. Kolesnikov Y, Fedin KV, Ngomayezwe L. Compression waves reflection from the low-velocity azimuthally anisotropic medium: a physical model study. Geophys J Int. 2020;221(2):1320-1326.

doi: 10.1093/gji/ggaa031

 

  1. Zhang J, Fan X, Huang Z, Liu Z, Fan Z, Liu L. In situ stress determination in isotropic and anisotropic rocks and its application to a naturally fractured reservoir. Geomech Geophys Geo-Energy Geo-Resour. 2023;9(1):80. doi: 10.1007/s40948-023-00584-6

 

  1. Huang Y, Wei M, Malekian R, Zhen X. CBM Reservoir Rock Physics Model and Its Response Characteristic Study. IEEE Access. 2017;5:5837-5843. doi: 10.1109/access.2017.2687882

 

  1. Wu H, Guo J, Ji G, Huang Y, Ding H, Lin P. Estimating the anisotropy of the vertical transverse isotropy coal seam by rock physics model–based inversion. Geophys Prospect. 2024;72(5):2064-2075. doi: 10.1111/1365-2478.13470

 

  1. Gong F, Zou G, Zhang Z, Peng S, Wang G, Chen H. An anisotropic rock physics modeling for the coalbed methane reservoirs and its applications in anisotropy parameter prediction. J Appl Geophys. 2024;225:105381. doi: 10.1016/j.jappgeo.2024.105381

 

  1. Mavko G, Mukerji T, Dvorkin J. The Rock Physics Handbook. 2nd ed. Cambridge University Press; 2010. doi: 10.1017/cbo9780511626753

 

  1. Zhao M, Jin Y, Liu X, Zheng J, Liu S. Characterizing the Complexity Assembly of Pore Structure in a Coal Matrix: Principle, Methodology, and Modeling Application. J Geophys Res Solid Earth. 2020;125(12):e2020JB020110. doi: 10.1029/2020jb020110

 

  1. Gong F, Huang A, Kang W, et al. The influence of lamination and fracture on the velocity anisotropy of tectonic coals. Geophysics. 2024;89(6):MR355-MR365. doi: 10.1190/geo2024-0033.1

 

  1. Alkhimenkov Y, Quintal B. A simple and accurate model for attenuation and dispersion caused by squirt flow in isotropic porous rocks. Geophysics. 2023;89(1):MR1-MR10. doi: 10.1190/geo2023-0049.1

 

  1. Mavko G, Nolen-Hoeksema RC. Estimating seismic velocities at ultrasonic frequencies in partially saturated rocks. Geophysics. 1994;59(2):252-258. doi: 10.1190/1.1443587

 

  1. Biot MA. Theory of Propagation of Elastic Waves in a Fluid-Saturated Porous Solid. I. Low-Frequency Range. J Acoust Soc Am. 1956;28(2):168-178. doi: 10.1121/1.1908239

 

  1. Carcione JM, Kosloff D, Behle A. Long-wave anisotropy in stratified media; a numerical test. Geophysics. 1991;56(2):245-254. doi: 10.1190/1.1443037

 

  1. Chen T, Liu Y. Multi-component AVO response of thin beds based on reflectance spectrum theory. Appl Geophys. 2006;3(1):27-36. doi: 10.1007/s11770-006-0004-5

 

  1. Kennett BLN, Kerry NJ. Seismic waves in a stratified half space. Geophys J Int. 1979;57(3):557-583. doi: 10.1111/j.1365-246x.1979.tb06779.x

 

  1. Sidler R, Holliger K. Seismic reflectivity of the sediment-covered seafloor: effects of velocity gradients and fine-scale layering. Geophys J Int. 2010;181(1):521-531. doi: 10.1111/j.1365-246x.2010.04519.x

 

  1. Wang Y, Yang C, Lu J. Dilemma faced by elastic wave inversion in thinly layered media. Chin J Geophys. 2018;61(3):1118-1135. doi: 10.6038/cjg2018L0404

 

  1. Liu Y, Schmitt DR. Amplitude and AVO responses of a single thin bed. Geophysics. 2003;68(4):1161-1168. doi: 10.1190/1.1598108

 

  1. Meissner R, Meixner E. Deformation of seismic wavelets by thin layers and layered boundaries. Geophys Prospect. 1969;17(1):1-27. doi: 10.1111/j.1365-2478.1969.tb02069.x

 

  1. Pan W, Innanen KA. AVO/AVF analysis of thin beds in elastic media. In: SEG Technical Program Expanded Abstracts 2013. Society of Exploration Geophysicists; 2013. doi: 10.1190/segam2013-0587.1

 

  1. Dai N, Vafidis A, Kanasewich ER. Wave propagation in heterogeneous, porous media; a velocity-stress, finite-difference method. Geophysics. 1995;60(2):327-340. doi: 10.1190/1.1443769

 

  1. Geertsma J, Smit DC. Some aspects of elastic wave propagation in fluid-saturated porous solids. Geophysics. 1961;26(2):169-181. doi: 10.1190/1.1438855

 

  1. Deresiewicz H, Skalak R. On uniqueness in dynamic poroelasticity. Bull Seismol Soc Am. 1963;53(4):783-788. doi: 10.1785/bssa0530040783

 

  1. Rokhlin SI, Wang YJ. Equivalent boundary conditions for thin orthotropic layer between two solids: Reflection, refraction, and interface waves. J Acoust Soc Am. 1992;91(4):1875-1887. doi: 10.1121/1.403717

 

  1. Tooley RD, Spencer TW, Sagoci HF. Reflection and transmission of plane compressional waves. Geophysics. 1965;30(4):552-570. doi: 10.1190/1.1439622

 

  1. Ursin B, Stovas A. Reflection and transmission responses of a layered isotropic viscoelastic medium. Geophysics. 2002;67(1):307-323. doi: 10.1190/1.1451803

 

  1. Mukerji T, Mavko G. Pore fluid effects on seismic velocity in anisotropic rocks. Geophysics. 1994;59(2):233-244. doi: 10.1190/1.1443585

 

  1. Zou G, Zeng H, Peng S, Zhou X, Satibekova S. Bulk density and bulk modulus of adsorbed coalbed methane. Geophysics. 2019;84(2):K11-K21. doi: 10.1190/geo2018-0081.1

 

  1. Saenger EH, Gold N, Shapiro SA. Modeling the propagation of elastic waves using a modified finite-difference grid. Wave Motion. 2000;31(1):77-92. doi: 10.1016/s0165-2125(99)00023-2

 

  1. Jianxiong L, Chunjiao M. An efficient FDTD implementation of the CFS-PML based on the ADE method and its validation along with the PLRC method in dispersive media. In: Hong W, Yang G, eds. 2008 International Conference on Microwave and Millimeter Wave Technology. IEEE; 2008:766-769. doi: 10.1109/icmmt.2008.4540510

 

  1. Komatitsch D, Martin R. An unsplit convolutional perfectly matched layer improved at grazing incidence for the seismic wave equation. Geophysics. 2007;72(5):SM155-SM167. doi: 10.1190/1.2757586

 

  1. Martin R, Komatitsch D. An unsplit convolutional perfectly matched layer technique improved at grazing incidence for the viscoelastic wave equation. Geophys J Int. 2009;179(1):333-344. doi: 10.1111/j.1365-246x.2009.04278.x
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