ABSTRACT

The studied area is the Umm Gudair field located onshore, in the South West of Kuwait. Wells drilled in this field have proven the presence of oil in the Ratawi Limestone Formation. One of the biggest challenges in this field is to understand the porosity heterogeneity in the limestone. Some wells drilled in this field had good initial production but declined dramatically. It is assumed that the declining production is controlled by porosity distribution of Ratawi limestone. In order to assess the porosity distribution and its associated uncertainty in this field, a geostatistical inversion was performed followed by porosity co-simulation. Geostatistical inversion using Bayesian inference combined with a Markov Chain Monte Carlo (MCMC) sampling algorithm robustly integrates the information of well logs, geological constraints, geostatistical parameters and seismic data, creating models which honor all of the input data. Multiple realizations were created, resulting in highly detailed models of acoustic impedance (P-impedance) and lithotype which were then used to co-simulate porosity volumes. These results were used to assess the uncertainty in the porosity distribution of the Ratawi limestone to enable a better drilling campaign.

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