Presenting an integrated strategy for porosity mapping in a genetic-based seismic inversion framework in a heterogeneous reservoir

نوع مقاله : مقاله پژوهشی‌

نویسندگان

1 Assistant Professor, Faculty of Engineering, Asia Pacific University of Technology & Innovation (APU), Kuala Lumpur, Malaysia

2 Associate professor, Faculty of Mining, petroleum and Geophysics, Shahrood University of technology, Shahrood, Iran

3 Professor, Faculty of Engineering, Asia Pacific University of Technology & Innovation (APU), Kuala Lumpur, Malaysia

4 Associate Professor, Faculty of Engineering, Asia Pacific University of Technology & Innovation (APU), Kuala Lumpur, Malaysia

چکیده

Seismic reservoir characterization is a state-of-the-art procedure in using various sources of data. Generally, seismic data, due to their low resolution, are randomly used in the final steps of reservoir characterization. However, extensive coverage of 3D seismic data, compared to well data, makes it possible to be applicable for the distribution of characters through the whole reservoir. In this regard, seismic data should be inverted to illustrate the desired characters throughout the media. Conventionally, seismic inversion uses well logs that have defects in its derivation steps, such as wavelet extraction and its propagation through media. The proposed strategy to resolve such deficiencies is the genetic inversion. However, genetic inversion has its own deficiency in accuracy. In this study, we propose an integrated strategy for using various sources of data in an iterative manner for resolving this obstacle. The proposed strategy uses a combined related attribute to evaluate initial acoustic impedance inverted model by genetic inversion. The model then would be updated to satisfy well data. The proposed strategy was applied to a heterogeneous reservoir from the southwest of Iran. Three seismic attributes were integrated to produce a unique attribute for initial model evaluation. The final model was then evaluated by well data. Results were also compared with the conventional method of seismic inversion. The result of the proposed strategy in the genetic inversion depicted improvement in the final acoustic impedance and the porosity distribution model.
 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Presenting an integrated strategy for porosity mapping in a genetic-based seismic inversion framework in a heterogeneous reservoir

نویسندگان [English]

  • Amin Shahbazi 1
  • Mehrdad Soleimani monfared 2
  • Vinesh Thiruchelvam 3
  • Thang Ka Fei 4
1 Assistant Professor, Faculty of Engineering, Asia Pacific University of Technology & Innovation (APU), Kuala Lumpur, Malaysia
2 Associate professor, Faculty of Mining, petroleum and Geophysics, Shahrood University of technology, Shahrood, Iran
3 Professor, Faculty of Engineering, Asia Pacific University of Technology & Innovation (APU), Kuala Lumpur, Malaysia
4 Associate Professor, Faculty of Engineering, Asia Pacific University of Technology & Innovation (APU), Kuala Lumpur, Malaysia
چکیده [English]

Seismic reservoir characterization is a state-of-the-art procedure in using various sources of data. Generally, seismic data, due to their low resolution, are randomly used in the final steps of reservoir characterization. However, extensive coverage of 3D seismic data, compared to well data, makes it possible to be applicable for the distribution of characters through the whole reservoir. In this regard, seismic data should be inverted to illustrate the desired characters throughout the media. Conventionally, seismic inversion uses well logs that have defects in its derivation steps, such as wavelet extraction and its propagation through media. The proposed strategy to resolve such deficiencies is the genetic inversion. However, genetic inversion has its own deficiency in accuracy. In this study, we propose an integrated strategy for using various sources of data in an iterative manner for resolving this obstacle. The proposed strategy uses a combined related attribute to evaluate initial acoustic impedance inverted model by genetic inversion. The model then would be updated to satisfy well data. The proposed strategy was applied to a heterogeneous reservoir from the southwest of Iran. Three seismic attributes were integrated to produce a unique attribute for initial model evaluation. The final model was then evaluated by well data. Results were also compared with the conventional method of seismic inversion. The result of the proposed strategy in the genetic inversion depicted improvement in the final acoustic impedance and the porosity distribution model.
 

کلیدواژه‌ها [English]

  • Seismic reservoir characterization
  • Genetic inversion
  • Seismic attributes
  • Porosity distribution

مراجع

Abdel-Rasoul RR. Daoud A. El-Tayeb E.S.A. (2014) Production allocation in multi-layers gas producing wells using temperature measurements with the application of a genetic algorithm, Pet. Sci. Tech. 2014; 25-28 https://doi.org/10.1080/10916466.2011.586958 
Ahmadi MA. Soleimani R. Lee M. Kashiwao T. Bahadori AR. (2015) Determination of oil well production performance using artificial neural network (ANN) linked to the particle swarm optimization (PSO) tool. Pet., 1(2), 118-132; https://doi.org/10.1016/j.petlm.2015.06.004
Al-Bulushi, N.I., King, P.R., Blunt, M.J., Kraaijveld, M., (2012) Artificial neural networks workflow and its application in the petroleum industry: Neural Comp and Appl, 21 (3), 409-421 https://doi.org/10.1007/s00521-010-0501-6
Balouchi, S., Moradi, S., Masihi, M., Erfaninia, A.A., (2013) A Novel combinatorial approach to discrete fracture network modeling in heterogeneous media. Iranian Journal of Oil and Gas Sci and Tech, 2(1), 42-56. https://doi.org/10.22050/IJOGST.2013.3037
Benisch, K., Köhn, D., al Hagrey, S., Rabbel, W., Bauer, S., (2015) A combined seismic and geoelectrical monitoring approach for CO2 storage using a synthetic field site. Environ Earth Sci. 73(7) 3077–3094, https://doi.org/10.1007/s12665-014-3603-0
Chen, Y., Durlofsky, L.J., (2006) Adaptive local-global upscaling for general flow scenarios in heterogeneous formations, Tran Por Med, 62(2), 157-185. https://doi.org/10.1007/ s11242-005-0619-7
Daraei M, Bayet-Golla A, Ansari M, (2017) An integrated reservoir zonation in sequence stratigraphic framework: A case from the Dezful Embayment, Zagros, Iran. J of Petro Sci and Eng. 154, 389-404, https://doi.org/10.1016/j.petrol.2017.04.038
Dehkar, A., Sajjadian, V.A., Noora, M.R., and Shabani Goorji, K., (2018). Microfacies analysis and depositional environment of the Fahliyan Formation (Lower Cretaceus), Abadan plain, West South of Iran (Arvand-feld). Geosciences, 106, 45-52.
Derikvand B, Alavi A, Abdollahie Fard I, Hajialibeigi H, (2018) Folding style of the Dezful Embayment of Zagros Belt: Signatures of detachment horizons, deep-rooted faulting and syn-deformation deposition. Mar and Petr Geo. 91, 501-518. https://doi.org/10.1016/j.marpetgeo. 2018.01.030
Farshi M, Moussavi-Harami, R, Mahboubi A, Khanehbad M, Golafshani T, (2019) Reservoir rock typing using integrating geological and petrophysical properties for the Asmari Formation in the Gachsaran oil field, Zagros basin. J of Petr Sci and Eng.176, 161-171. https://doi.org/ 10.1016/j.petrol.2018.12.068
Galvis I, Villa Y, Duarte C, Sierra D, Agudelo W., (2017) Seismic attribute selection and clustering to detect and classify surface waves in multi-component seismic data by using k-means algorithm. The Leading Edge, 33(6), 239–248. http://dx.doi.org/10.1190/tle36030239.1.
Gao J, Wang J, Yun M, Huang B, Zhang G, (2006) Seismic attributes optimization and application in reservoir prediction. Applied Geophysics. 3, 243–247. http://dx.doi.org/10.1007/s11770-006-4007-z
Ghanadian M, Faghih A, Abdollahie Fard I, Kusky T, Maleki M, (2017) On the role of incompetent strata in the structural evolution of the Zagros Fold-Thrust Belt, Dezful Embayment, Iran. Mar and Petr Geo. 81, 320-333, https://doi.org/10.1016/j.marpetgeo.2017.01.010
Guerriero V, Mazzoli S, Iannace A, Vitale S, Carravetta A, Straussc C. A., (2012), Permeability model for naturally fractured carbonate reservoirs. Mar petrol Geol. 40, 115-134, https://doi.org/10.1016/j.marpetgeo.2012.11.002
Hu, Y., Li, Z., Zhao, J., Tao, Z., Gao, P., (2017) Prediction and analysis of the stimulated reservoir volume for shale gas reservoirs based on rock failure mechanism. Environ Earth Sci. 76:546, https://doi.org/10.1007/s12665-017-6830-3
Iliev O. Rybak I. (2008) On numerical upscaling for flows in heterogeneous porous media. Comp. Meth. In App. Math. 8(1), 60-76, https://doi.org/10.2478/cmam-2008-0004.
Maffucci R, Bigi S, Corrado S, Chiodi A, Di Paolo L, Giordano G, Invernizzi C, (2015) Quality assessment of reservoirs by means of outcrop data and discrete fracture network models: The case history of Rosario de La Frontera (NW Argentina) geothermal system. Tectonophysics, https://doi.org/10.1016/j.tecto.2015.02.016
Movahed Z, Junin R, Amiri Bakhtiari H, Safarkhanlou Z, Movahed AA, Alizadeh, M, (2015) Introduction of sealing fault in Asmari reservoir by using FMI and RFT in one of the Iranian naturally fractured oil fields. Arab J Geosci, 8(12), 10919-10936. https://doi.org/10.1007/s12517-015-1951-z
Motamedi H, Sherkati S, Sepehr M, (2012) Structural style variation and its impact on hydrocarbon traps in central Fars, southern Zagros folded belt, Iran. J of Stru Geo. 37, 124-133, https://doi.org/10.1016/j.jsg.2012.01.021
Noorbakhsh SS, Rasaei MR, Heydarian A, Behnaman H, (2014) Single-phase near-well permeability upscaling and productivity index calculation methods. Iranian J of Oil and Gas Sci and Tech, 3(4), 55-66. https://doi.org/10.22050/IJOGST.2014.7522
Norden, B., Förster, A., Behrends, K., Krause, K., Stecken, L., Meyer, R., (2012) Geological 3-D model of the larger Altensalzwedel area, Germany, for temperature prognosis and reservoir simulation. Environ Earth Sci. 67(2), 511–52. https://doi.org/10.1007/s12665-012-1709-9
Nozohour-leilabady, B. Fazelabdolabad, B. (2015), On the application of Artificial Bee Colony (ABC) algorithm for optimization of well placements in fractured reservoirs; efficiency comparison with the Particle Swarm Optimization (PSO) methodology. Petroleum, 2(1), 79-82. https://doi.org/10.1016/j.petlm.2015.11.004
Oyeyemi KD, Olowokere MT, Aizebeokhai AP (2019). Prospect analysis and hydrocarbon reservoir volume estimation in an exploration field, shallow offshore Depobelt, western Niger delta, Nigeria. Nat Resour Res., 28(1), 173-185. https://doi.org/10.1007/s11053-018-9377-4
Presho M, Woc S, Ginting V. (2011) Calibrated dual porosity, dual permeability modeling of fractured reservoirs. J Petrol Sci Eng., 77(3-4), 326-337, https://doi.org/10.1016/j.petrol.2011.04.007
Qi X, Zhang S, (2012) Application of seismic multi-attribute fusion method based on D-S evidence theory in prediction of CBM-enriched area. App. Geoph. 9, 80–86. http://dx.doi.org/10.1007/s11770-012-0317-5
Sentenac, P., Benes, V., Keenan, H., (2018) Reservoir assessment using non-invasive geophysical techniques. Environ Earth Sci. 77:293 https://doi.org/10.1007/s12665-018-7463-x
Soleimani, M., Jodeiri, B., (2015) 3D static reservoir modeling by geostatistical techniques used for reservoir characterization and data integration. Environ. Earth Sci, 74, 1403–1414. http://dx.doi.org/10.1007/s12665-015-4130-3
Soleimani M, Jodeiri B, Rafie M, (2016), Integrated petrophysical modeling for a strongly heterogeneous and fractured reservoir, Sarvak Formation, SW Iran. Nat Reso Res. 26(1) 75-88. http://dx.doi.org/10.1007/s11053-016-9300-9
Soleimani M, (2017a), Well performance optimization for gas lift operation in a heterogeneous reservoir by fine zonation and different well type integration. J of Nat Gas Sci and Eng, 40, 277-287. http://dx.doi.org/10.1016/j.jngse.2017.02.017
Soleimani M, (2017b), Naturally fractured hydrocarbon reservoir simulation by elastic fractures modeling. Petro Sci, 14, 286–301. https://doi.org/10.1007/s12182-017-0162-5 
Tenzer, H., Park, C.H., Kolditz, O., McDermott, CI., (2010) Application of the geomechanical facies approach and comparison of exploration and evaluation methods used at Soultz-sous-Forêts (France) and Spa Urach (Germany) geothermal sites. Environ Earth Sci. 61(4) 853–880, https://doi.org/10.1007/s12665-009-0403-z
Vatandoust M, Farzipour Saein A, (2019) Fracture analysis of hydrocarbon reservoirs by static and dynamic well data, case study: The Aghajari oil field (the Zagros Fold-Thrust Belt). Develop in Struc Geol and Tect, 3, 1-16. https://doi.org/10.1016/B978-0-12-815048-1.00001-9
Zhao, H., Ma, F., Liu, G., Feng, X., Guo, J., (2018) Analytical investigation of hydraulic  fracture-induced   seismicity
and fault activation, Environ Earth Sci. 77:526, https://doi.org/10.1007/s12665-018-7708-8
مجله ژئوفیزیک ایران
دوره 14، شماره 4
دی 1399
صفحه 41-65

فایل ها

هم رسانی

ارجاع به این مقاله

آمار