INVERSI GEOSTATISTIK MENGGUNAKAN ANALISA MULTI-ATRIBUT STEPWISE REGRESSION UNTUK KARAKTERISASI RESERVOIR

Rahmat Catur Wibowo, Suci Ariska, Ordas Dewanto

Abstract


Eksplorasi dan produksi pada reservoir tight sand sampai saat ini masih memiliki tantangan tersendiri karena karakterisitik porositas dan permeabilitas yang rendah. Penelitian ini dilakukan untuk menganalisis karakteristik reservoir tight sand berdasarkan peta persebaran properti log menggunakan inversi impedansi akustik (IA) dan analisis multi-atribut. Analisis multi-atribut stepwise regression adalah suatu metode yang menggunakan atribut-atribut yang paling baik untuk memprediksi log target dengan melalui proses trial and error. Pemilihan atribut seismik yang tepat dapat memberikan penggambaran zona target yang lebih baik. Penelitian ini dilakukan untuk memperoleh peta struktur geologi bawah permukaan, volume impedansi akustik. Kemudian dilakukan analisis multi-atribut untuk mendapatkan prediksi volume property log yang mencakup pseudo gamma-ray, densitas, dan porositas dengan menggunakan metode stepwise regression. Hasil inversi seismik IA dan analisis multi-atribut stepwise regression menunjukkan reservoir dengan fluida berupa gas, serta litologi tight sand yang memiliki rentang nilai IA sebesar 22.000 ((ft/s)*(g/cc)) sampai dengan 45.000 ((ft/s)*(g/cc)), densitas 2,25 g/cc sampai dengan 2,6 g/cc, dan porositas 5% sampai 12%. Peta densitas dan porositas yang diperoleh dari analisa multi-atribut menunjang tahap eksplorasi dan produksi jangka panjang. Hal tersebut terkait upaya untuk meningkatkan pemahaman tentang perangkap stratigrafi, dan kemenerusan lapisan reservoir.

ABSTRACT – Geostatistical Inversion Using Multi-attribute Stepwise Regression for Reservoir Characterization. Exploration and production of tight sand reservoirs are still challenging due to their low porosity and permeability characteristics. This study used acoustic impedance inversion and multi-attribute analysis to analyze the tight sand reservoir characteristics based on the log property distribution map. Stepwise regression multi-attribute analysis is a method that uses the best attributes to predict the target log, which is carried out through a trial and error process. The ability to select a correct seismic attribution can provide a better depiction of the target zone. This research was conducted to obtain a subsurface geological structures map, acoustic impedance volumes. The multi-attribute analysis was performed to predict volume log properties such as pseudo-gamma-ray, density, and porosity, by using the stepwise regression method. The results of acoustic impedance seismic inversion and stepwise regression multi-attribute analysis show that the reservoir contains gas fluid with tight sand lithology, which has a range of acoustic impedance values of 22,000 ((ft/s)*(g/cc)) to 45,000 ((ft/s)*(g/cc)), the density of 2.25 g/cc to 2.6 g/cc, and porosity of 5% to 12%. The density and porosity maps obtained from the multi-attribute analysis can support the long-term exploration and production stages. The aims are to improve the primary recovery and tertiary recovery, understanding the stratigraphic traps, and the continuity of reservoir layers.


Keywords


acoustic impedance inversion, multi- attribute analysis, stepwise regression, reservoir characterization

References


Altowairqi, Y., Rezaee, R., Evans, B., Urosevic, M., 2017. A Quantitative Application of Seismic Inversion and Multi-Attribute Analysis based on Rock Physics Linear Relationships to identify High Total Organic Carbon Shale - A Case Study from the Perth Basin, in: Unconventional Resources Technology Conference. Austin, pp. 1807–1811. https://doi.org/10.15530/urtec-2017- 2671356

Asquith, G., Gibson, C., 1982. Basic Well Log Analysis for Geologist. AAPG, Tulsa.

Barber, P., Carter, P., Fraser, T., Baillie, P., Myers, K., 2003. Paleozoic and Mesozoic Petroleum Systems in the Timor and Arafura Seas, Eastern Indonesia. In: Indonesian Petroleum Association Twenty-Ninth Annual Convention & Exhibition, October 2003. Indonesian Petroleum Association, Jakarta. https://doi.org/10.29118/ipa.428.03.g.16 9

Bishop, M.G., 1999. Total petroleum systems of the Bonaparte Gulf Basin area, Australia; Jurassic, Early Cretaceous-Mesozoic; Keyling, Hyland Bay-Permian; Milligans-Carboniferous, Permian, Open-File Report 99-50-P, U.S. Geological Survey, Reston, VA. https://doi.org/10.3133/ofr9950P

Cadman, S.J., Temple, P.R., 2004. Bonaparte Basin, NT, WA, AC & JPDA, Australian Petroleum Accumulations Report 5, 2nd Edition. Canberra.

Caineng, Z., Guangya, Z., Shizhen, T., Suyun, H.,Xiaodi, L., Jianzhong, L., Dazhong, D., Rukai, Z., Xuanjun, Y., Lianhua, H., Hui, Q., Xia, Z., Jinhua, J., Xiaohui, G., Qiulin, G., Lan, W., Xinjing, L., 2010. Geological features, major discoveries, and unconventional petroleum geology in the global petroleum exploration. Pet. quantitative reservoir characterization. Lead. Edge 19, 878–881. https://doi.org/https://doi.org/10.1190/1. 1438735

Deng, J.M., Liu, X.P., Wu, X.M., Hu, X.X., 2013. Estimation of porosity and permeability from conventional logs in tight sandstone reservoirs of north Ordos basin. Soc. Pet. Eng. - SPE Middle East Unconv. Gas Conf. Exhib. 2013, UGAS 2013 - Unconv. Tight Gas Bridg. Gaps Sustain. Econ. Dev. 34–41. https://doi.org/10.2118/163953-ms

Gong, L., Zeng, L., Gao, Z., Zhu, R., Zhang, B., 2016. Reservoir characterization and origin of tight gas sandstones in the Upper Triassic Xujiahe formation, Western Sichuan Basin. J. Pet. Explor. Prod. Technol. 6, 319–329. https://doi.org/10.1007/s13202-015- 0203-9

Hampson, D.P., Schuelke, J.S., Quirein, J.A., 2001. Use of multiattribute transforms to predict log properties from seismic data. Geophysics 66, 220–236. https://doi.org/10.1190/1.1444899

Keep, M., Clough, M., Langhi, L., 2002. Neogene tectonic and structural evolution of the Timor Sea region, NW Australia, in: Proceedings of the West Australian Basins Symposium 2. Perth, pp. 341– 352.

Khoshdel, H., Riahi, M.A., 2007. 3D Porosity Estimation Using Multi-attribute Analysis Methods in One of the Persian Gulf Oil Fields, in: SPE International. SPE, London, p. 12.

Liu, H., 2017. Principles and Applications of Well Logging, Principles and Applications of Well Logging. Springer Mineralogy, Beijing. https://doi.org/10.1007/978-3- 662-54977-3

Riel, P. van, 2000. The past, present, and future of

quantitative reservoir characterization. The Leading Edge 19, 878–881. https://doi.org/https://doi.org/10.1190/1. 1438735

Russel, B.H., D., Schuelke, J., Quirein, J., 1997. Multiattribute seismic analysis. The Leading Edge 16 (10), 1439-1444. https://doi.org/10.1190/1.1437486

Russell, B.H., 1988. Introduction to Seismic Inversion Methods, Second. ed. Society of Exploration Geophysicists, Tulsa. https://doi.org/10.1190/1.9781560802303

Schober, P., Schwarte, L.A., 2018. Correlation coefficients: Appropriate use and interpretation. Anesth. Analg. 126, 1763–1768. https://doi.org/10.1213/ANE.000000000 0002864

Setiawan, M.H.F., Asy’ari, M.R., Wibowo, R.C., Amijaya, D.H., Aspari, A.A., 2015. Parasequence Concepts, Problems, And Solutions In Cbm Exploration Using Seismic Data Case Study: Muara Enim Formation, South Sumatra Basin. In: Indonesian Petroleum Association Thirty-Ninth Annual Convention & Exhibition. Indonesian Petroleum Association, Jakarta, p. 10.

Suwatjanapornpong, S., Jaruwattanasakul, C., Kreeprasertkul, K., Suwanruji, P., 2016. Multi-Attributes Analysis and Neural Network : A New Approach of Reservoir Characterisation in Thap Raet and Greater Sirikit East, Phitsanulok Basin, in: International Petroleum Technology Conference. IPTC, Bangkok, p. 10.

Wibowo, R.C., Mulyatno, B.S., 2012. Karakterisasi Reservoar Menggunakan Metode Inversi Impedansi Akustik dan Neural Network Pada Lapangan “ ICL ” Cekungan Sumatera Selatan, in: Proceedings PIT HAGI 2012. HAGI, Palembang, pp. 2–4.

Wibowo, R.C., Arlinsky, D., Ariska, S., Wiranatanegara, B.W., Riyadi, P., 2020a. Gas Saturated Sandstone Reservoir Modeling Using Bayesian Stochastic Seismic Inversion. J. Geosci. Eng. Environ. Technol. 05, 25–31. https://doi.org/10.25299/jgeet.2020.5.1. 4503

Wibowo, R.C., Sarkowi, M., Mulyatno, B.S., Dewanto, O., Zaenudin, A., Amijaya, D.H., Aspari, A.A., 2020b. Thinned coal distribution modeling based on integrated geological and geophysical data: Case study CBM resources in Central Palembang Sub-Basin. In: 2nd International Conference on Earth Science, Mineral, and Energy. AIP Publishing, Yogyakarta, pp. 1–9. https://doi.org/https://doi.org/10.1063/5. 0006962

Zou, C., Zhu, R., Liu, K., Su, L., Bai, B., Zhang, X., Yuan, X., Wang, J., 2012. Tight gas sandstone reservoirs in China: Characteristics and recognition criteria. J. Pet. Sci. Eng. 88–89, 82–91. https://doi.org/10.1016/j.petrol.2012.02. 001




DOI: http://dx.doi.org/10.14203/risetgeotam2020.v30.1088

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