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

Rahmat Catur Wibowo; Suci Ariska; Ordas Dewanto

doi:10.14203/risetgeotam2020.v30.1088

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

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