Gas Saturated Sandstone Reservoir Modeling Using Bayesian Stochastic Seismic Inversion

Rahmat Catur Wibowo (Geophysical Engineering Department, Engineering Faculty, Universitas Lampung, Lampung, Indonesia)
Ditha Arlinsky Ar (Geophysical Engineering Department, Engineering Faculty, Universitas Lampung, Lampung, Indonesia)
Suci Ariska (Geophysical Engineering Department, Engineering Faculty, Universitas Lampung, Lampung, Indonesia)
Muhammad Budisatya Wiranatanagara (Lemigas R & D Centre for Oil and Gas Technology, South Jakarta, Indonesia)
Pradityo Riyadi (Lemigas R & D Centre for Oil and Gas Technology, South Jakarta, Indonesia)

Journal of Geoscience, Engineering, Environment, and Technology
Vol. 5 No. 1 (2020): JGEET Vol 05 No 01: March 2020

This study has been done to map the distribution of gas saturated sandstone reservoir by using stochastic seismic inversion in the “X” field, Bonaparte basin. Bayesian stochastic inversion seismic method is an inversion method that utilizes the principle of geostatistics so that later it will get a better subsurface picture with high resolution. The stages in conducting this stochastic inversion technique are as follows, (i) sensitivity analysis, (ii) well to seismic tie, (iii) picking horizon, (iv) picking fault, (v) fault modeling, (vi) pillar gridding, ( vii) making time structure maps, (viii) scale up well logs, (ix) trend modeling, (x) variogram analysis, (xi) stochastic seismic inversion (SSI). In the process of well to seismic tie, statistical wavelets are used because they can produce good correlation values. Then, the stochastic seismic inversion results show that the reservoir in the study area is a reservoir with tight sandstone lithology which has a low porosity value and a value of High acoustic impedance ranging from 30,000 to 40,000 ft /s*g/cc.