Amplitude Variation with Offset (AVO) Inversion for Reservoir Visualization: A Case Study of Taje Field, Niger Delta, Nigeria
Source: By:Ebiegberi Oborie, Omonefe Francis, Desmond Eteh
DOI: https://doi.org/10.30564/agger.v6i1.6158
Abstract:Amplitude Variation with Offset (AVO) inversion analysis was performed on pre-stack seismic data and well information gathered from the shallow offshore area of the Niger Delta. This analysis aimed to improve reservoir visualization and employed the Hampson Russell Geoview, AVO, and STRATA software tools. The seismic data were provided in Seg-Y format, covering an in-line range from 4503 to 5569, an x line range from 1434 to 2026, and an angle of incidence range of 0 to 45°. The study centered on the Taje well_026. Within the subsurface, the authors identified five distinct reservoirs, labeled A to E, located at various depths ranging from 3057.50 to 3115.00 m, 3115.00 to 3157.50 m, 3157.50 to 3190.00 m, 3190.00 to 3200.00 m, and 3200.00 to 3239.00 m, respectively. These reservoirs exhibited different fluid compositions. Reservoir A, primarily composed of sandstone, contained brine, whereas Reservoirs B and D, dominated by shale, contained gas. On the other hand, Reservoirs C and E, both comprised of sandstone, held oil. Reservoir C is distinguished by its clean sandstone unit. The inversion results revealed that both Reservoirs C and E consisted of low impedance sand layers surrounded by higher impedance shale layers. The gas migrated from the reservoir and was trapped within the shale units due to deformation of the lithological units, likely induced by stress accumulation. This migration process was facilitated by the shale’s inability to undergo smearing, possibly as a result of faulting mechanisms.
References:[1] Oumarou, S., Mabrouk, D., Tabod, T.C., et al., 2021. Seismic attributes in reservoir characterization: An overview. Arabian Journal of Geosciences. 14, 402. DOI: https://doi.org/10.1007/s12517-021-06626-1 [2] Farfour, M., El-Ghali, M.A., Gaci, S., et al., 2021. Seismic attributes for hydrocarbon detection and reservoir characterization: A case study from Poseidon field, Northwestern Australia. Arabian Journal of Geosciences. 14, 2814. DOI: https://doi.org/10.1007/s12517-021-08853-y [3] Ilozobhie, A.J., Egu, D.I., 2021. Dynamic reservoir sand characterization of an oil field in the Niger Delta from seismic and well log data. Arabian Journal of Geosciences. 14, 853. DOI: https://doi.org/10.1007/s12517-021-06542-4 [4] Etuk, N.O., Aka, M.U., Agbasi, O.E., et al., 2020. Evaluation of seismic attributes for reservoircharacterization over Edi field, Niger delta, Nigeria using 3d seismic data. International Journal of Advanced Geosciences. 8(2). DOI: https://doi.org/10.14419/ijag.v8i2.31043 [5] Li, J., 2021. Vibration response test method of curtain wall under seismic coupling. Arabian Journal of Geosciences. 14, 468. DOI: https://doi.org/10.1007/s12517-021-06849-2 [6] Chen, H., Sacchi, M.D., Haghshenas Lari, H., et al., 2023. Nonstationary seismic reflectivity inversion based on prior-engaged semisupervised deep learning method. Geophysics. 88(1), WA115–WA128. DOI: https://doi.org/10.1190/geo2022-0057.1 [7] Li, C., Liu, X., 2022. Sparse seismic reflectivity inversion using an adaptive fast iterative shrinkage‐thresholding algorithm. Geophysical Prospecting. 70(6), 1003–1015. DOI: https://doi.org/10.1111/1365-2478.13211 [8] Luo, C., Ba, J., Carcione, J.M., et al., 2020. Joint PP and PS pre-stack seismic inversion for stratified models based on the propagator matrix forward engine. Surveys in Geophysics. 41, 987–1028. DOI: https://doi.org/10.1007/s10712-020-09605-5 [9] Xiao, S., Ba, J., Guo, Q., et al., 2020. Seismic pre-stack AVA inversion scheme based on lithology constraints. Journal of Geophysics and Engineering. 17(3), 411–428. DOI: https://doi.org/10.1093/jge/gxaa001 [10] Luo, C., Li, X., Huang, G., 2019. Pre-stack AVA inversion by using propagator matrix forward modeling. Pure and Applied Geophysics. 176, 4445–4476. DOI: https://doi.org/10.1007/s00024-019-02157-9 [11] Luengo, D., Martino, L., Bugallo, M., et al., 2020. A survey of Monte Carlo methods for parameter estimation. EURASIP Journal on Advances in Signal Processing. (1), 25. DOI: https://doi.org/10.1186/s13634-020-00675-6 [12] Omonefe, F., Ejaita, E., 2020. AVO fluid inversion (AFI) technique as a tool to predict reservoir fluid content using data from FD field, onshore Niger Delta Nigeria. International Journal of Creative and Innovative Research in All Studies. 3(2). [13] Zhou, D., Wen, X., He, X., et al., 2022. Second-order approximate expressions of P-and SV-plane-wave reflection coefficients at the solid/solid media interface. Geophysics. 87(5), N85–N94. DOI: https://doi.org/10.1190/geo2021-0627.1 [14] Russell, B.H., Gray, D., Hampson, D.P., 2011. Linearized AVO and poroelasticity. Geophysics. 76(3), C19–C29. DOI: https://doi.org/10.1190/1.3555082 [15] Russell, B.H., Lines, L.R., Hirsche, K.W., et al., 2001. The AVO modelling volume. Exploration Geophysics. 32(4), 264–270. DOI: https://doi.org/10.1071/EG01264 [16] Durrani, M.Z.A., Rahman, S.A., Talib, M., et al., 2023. Discrimination of lithofacies in tight gas reservoir using field-specific rock physics modeling scheme. A case study from a mature field of middle Indus Basin, Pakistan. Acta Geophysica. 71, 2763–2780. DOI: https://doi.org/10.1007/s11600-023-01069-6 [17] Francis, O., Oborie, E., 2022. History and reviews on amplitude variation with offset (AVO) technology. International Journal of Advances in Engineering and Management (IJAEM). 4(6), 2437–2449. [18] Kumar, D., Zhao, Z., Foster, D.J., et al., 2020. Frequency-dependent AVO analysis using the scattering response of a layered reservoir. Geophysics. 85(2), N1–N16. DOI: https://doi.org/10.1190/geo2019-0167.1 [19] Zhao, Z., Kumar, D., Foster, D.J., et al., 2021. Frequency-dependent AVO analysis: A potential seismic attribute for thin-bed identification. Geophysics. 86(4), N1–N17. DOI: https://doi.org/10.1190/geo2020-0777.1 [20] Skopintseva, L., Aizenberg, A., Ayzenberg, M., et al., 2012. The effect of interface curvature on AVO inversion of near-critical and postcritical PP-reflections. Geophysics. 77(5), N1–N16. DOI: https://doi.org/10.1190/geo2011-0298.1 [21] Santoso, D., Kadir, W.G.A., Alawiyah, S., 2000. Delineation of reservoir boundary using AVO analysis. Exploration Geophysics. 31(1–2), 409–412. DOI: https://doi.org/10.1071/eg00409 [22] Beretta, M.M., Bernasconi, G., Drufuca, G., 2002. AVO and AVA inversion for fractured reservoir characterization. Geophysics. 67(1), 300–306. DOI: https://doi.org/10.1190/1.1451802 [23] Ohaegbuchu, H.E., Igboekwe, M.U., 2016. Determination of subsurface rock properties from AVO analysis in Konga oil field of the Niger Delta, Southeastern Nigeria. Modeling Earth Systems and Environment. 2, 124. DOI: https://doi.org/10.1007/s40808-016-0184-9 [24] Adeoti, L., Ikoro, C.O., Adesanya, O.Y., et al., 2019. On the effectiveness of using quantitative avo analysis in fluid and lithology discrimination in an offshore Niger Delta Field, Nigeria. Ife Journal of Science. 21(1), 1–12. DOI: https://doi.org/10.4314/ijs.v21i1.1 [25] Nwokoma, E., Agbasi, O.E., Dinneya, O.C., 2022. Prediction of litho-porosity using incompressibility and rigidity, offshore Niger Delta, Nigeria. Geoinformatica Polonica. 21, 31–42. DOI: https://doi.org/10.4467/21995923gp.22.003.17081 [26] Adeoti, L., Adeleye, K.O., Itsemode, A., et al., 2015. Fluid prediction using AVO analysis and forward modelling of deep reservoirs in Faith Field, Niger Delta, Nigeria. Arabian Journal of Geosciences. 8, 4057–4074. DOI: https://doi.org/10.1007/s12517-014-1476-x [27] Allo, O.J., Bako, M.E., Esan, D., 2022. Seismic attribute analysis for prospect delineation in ‘TMB’ field, Niger Delta Basin, Nigeria. Journal of Applied Sciences and Environmental Management. 26(3), 487–494. DOI: https://doi.org/10.4314/jasem.v26i3.17 [28] Agbasi, O.E., Igboekwe, M.U., Chukwu, G.U., et al., 2018. Discrimination of pore fluid and lithology of a well in X Field, Niger Delta, Nigeria. Arabian Journal of Geosciences. 11, 274. DOI: https://doi.org/10.1007/s12517-018-3610-7 [29] Onyena, A.P., Sam, K., 2020. A review of the threat of oil exploitation to mangrove ecosystem: Insights from Niger Delta, Nigeria. Global Ecology and Conservation. 22, e00961. DOI: https://doi.org/10.1016/j.gecco.2020.e00961 [30] Ogbe, O.B., 2020. Sequence stratigraphic controls on reservoir characterization and architectural analysis: A case study of Tovo field, coastal swamp depobelt, Niger Delta Basin, Nigeria. Marine and Petroleum Geology. 121, 104579. DOI: https://doi.org/10.1016/j.marpetgeo.2020.104579 [31] Ogbe, O.B., 2021. Reservoir sandstone grain-size distributions: Implications for sequence stratigraphic and reservoir depositional modelling in Otovwe field, onshore Niger Delta Basin, Nigeria. Journal of Petroleum Science and Engineering. 203, 108639. DOI: https://doi.org/10.1016/j.petrol.2021.108639 [32] Ugbor, C.C., Ugwuoke, C.I., Odong, P.O., 2023. Hydrocarbon prospectivity and risk assessment of “Bob” field central swamp depobelt, onshore Niger Delta Basin, Nigeria. Open Journal of Geology. 13(8), 847–882. DOI: https://doi.org/10.4236/ojg.2023.138038 [33] Unukogbon, N.O., Asuen, G.O., Emofurieta, W.O., 2008. Sequence stratigraphic appraisal: Coastal swamp depobelt in the Niger Delta Basin Nigeria. Global Journal of Geological Sciences. 6(2), 129–137. DOI: https://doi.org/10.4314/gjgs.v6i2.18762