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Castagna empirical relation were used to estimate shear wave velocity (Vs). Because the target zones has a different AI’s cutoff value, the crossplot has been done for each zones. Linear equation between Density-Porosity log and AI log were used to predict porosity volume from AI inversion result. Beside it, the crossplot have also been done between AI and density-porosity log to aim linear equation. Neither TG_4 nor TG_5 could not be separated from the shale because the AI value were overlap. Each of them has a different cotoff value of AI. Only three from five zones which could be separated from the shale based on it’s AI value (TG_1 TG_2 and TG_3). The high AI value may were caused by high cementation. Crossplot between AI and Vclay log show that target zones have a higher AI value than it’s shale. Model Based Hard Constrain method used in either AI or EI inversion. EI inversion which consider Vs and angle component has been done to detect presence of hydrocarbon. AI inversion has been done in order to find porous zone. There were twelve well log data used which consist six deviated well and six vertical well. This research describe the application of acoustic impedance (AI) and elastic impedance (EI) seismic inversion to 3D seismic data in Muon field, Air Benakat formation Jambi sub-basin.
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Analisa terintegrasi hasil inversi AI dan EI menunjukan beberapa zona prospektif yang poros dan menunjukan adanya hidrokarbon pada lapangan Moun EI far akan mengalami penurunan yang lebih drastis dari EI near dengan keberadaan hidrokarbon, sehingga crossplot EI near dan far memberikan indikasi keberadaan hidrokarbon. Berdasarkan analisa trend amplitude ditentukan rentang sudut nilai EI near dan far sebesar 00-140 dan 120-220. Persamaan Biot-Gassmann untuk mendapatkan Vs dalam kodisi sebenarnya. Tersaturasi air 100%, maka dilakukan FRM menggunakan Karena persamaan tersebut hanya valid dalam keadaan Persamaan empirisĬastagna digunakan untuk estimasi kecepatan gelombang-S (Vs). Zona target memiliki nilai cutoff AI yang berbeda, crossplotpunĭilakukan untuk masing-masing zona. Volume porositas dari volume AI hasil inversi. Persamaan linier antara logĭensity-Porosity dengan AI digunakan untuk memprediksi Selain crossplot antara log AI dan Vclay,ĭilakukan juga crossplot antara log AI dan density-porosity untuk Tidak dapat dipisahkan karena memiliki nilai AI yang overlapĭengan lapisan shale. Lebih tinggi dari shale yang diakibatkan tingginya sementasi.ĭari kelima zona target, hanya tiga zona yang dapat dipisahkanīerdasarkan nilai AI (TG_1 TG_2 dan TG_3). Hasil crossplotĪntara log AI dan Vclay menunjukan zona target memiliki nilai AI Inversi AI dan EI dilakukanĭengan metode Model Based Hard Constrain. Inversi EI yang memasukan komponen Vs dan sudut digunakan Inversi AI dilakukan untuk mengetahui persebaran lapisan poros. Yang terdiri dari enam sumur vertikal dan enam sumur miring. Data sumur yang digunakan sebanyak dua belas sumur Seismik 3D di lapangan Muon, formasi Air Benakat sub-basin Rock physics processes for estimating elastic parameters, such as acoustic impedance, Vp/Vs ratio, Poisson’s ratio, Young’s modulus, and a complete suite of fluid substitution tools based on Gassmann’s equation.Penelitian ini memaparkan aplikasi metoda inversiĪcoustic Impedance (AI) dan Elastic Impedance (EI) pada data.Without leaving the Petrel platform, Petrel Quantitative Interpretation provides seamless seismic data conditioning, rock physics, fluid substitution, AVO/AVA analysis, and pre- and poststack deterministic and stochastic inversion to predict lithology, pore fluid content, and seismic pore pressure modeling. Petrel Quantitative Interpretation is a product development collaboration between Schlumberger and Ikon Science. This ensures complete description of reservoir properties and extends conventional qualitative interpretation to a quantitative interpretation workflow in the same canvas. Petrel Quantitative Interpretation enables true integration of multidisciplinary seismic with well and geological data.