Detection of Thin Sandstone Distribution Using Geostatistical Inversion Approach, Case Study: Central X Field, South Sumatra Basin


The main Reservoir in Central X Field is sandstone from
Talang Akar Formation. Reservoir thickness varies from
1.5m to 20m. In addition to thin layer under tunning
thickness issues also a strong acoustic impedance overlaaps
between sand and shale. Geostatistical inversion approach
is used to accommodate all the information to produce a
geologically plausible features and has a high resolution.
There are three main components in the geostatistical
inversion of statistical modeling, Bayesian inference and
Markov Chain Monte Carlo. Statistical modeling determine
the probability density function associated with input data
sources. Bayesian inference merge the probability density
function into a global probability density function.
Customized Markov Chain Monte Carlo algorithm to
sample the posterios probability density function. The
combination of these three components generate multiple
plausible detailed realization of thin sand and insight into
related uncertainty.