Integrated Well Log Electrofacies and Seismic Facies Modeling for Stratigraphic Trap Identification in Carbonate Reservoirs, North Oman
Authors: Lertlamnaphakul Patraporn , Thanatit Suppakarn , Al Busaidi Salam Mohammed , Seusutthiya Krongpol 
Published: May 2016

One of the key approaches to look for a stratigraphic prospect in the carbonate reservoir is to map out areas that have changes in the rock facies laterally. A workflow of the 2009–2010 exploration study focuses on four key components: Regional new play concepts, Well log electrofacies, Seismic facies classification, and Prospect evaluation. This helps to predict stratigraphic traps and lithofacies changes within the study area. The electrofacies analysis calibrated to a reprocessed high resolution 3D seismic has been carried out in conjunction with Natih and Shuaiba prospecting concept and analogue fields compilation.

The aim of this integration of well log electrofacies and Seismic facies is to generate a 3D lithofacies model in the known areas where many wells had been drilled, and then use 3D seismic facies classification to predict lithofacies in the areas where no wells drilled. Moreover, this integration will provide an understanding of lateral and vertical facies changes of reservoirs and seals within target intervals, which are critical elements for defining stratigraphic traps.

The electrofacies analysis was carried out by integrating core data and well log to build a rock type model. This correlation allows rockfacies to be classified in the cored wells and predict those facies in the uncored wells. The results of this electrofacies analysis have demonstrated reservoir property predictions in terms of porosity and permeability distribution associated with each rock facies for all wells. On the other hand, the seismic facies classification was analyzed using Neural Network approach based on multiple calibration of seismic attributes, such as High resolution 3D seismic (AMP), Far offset angle stack (FAR), and Acoustic impedance (AI). The first pass of seismic facies classification was performed without well data input, so called "unsupervised model". The model will determine a possibility of seismic facies from all input attributes, and generate multiple 3D facies output for both Natih and Shuaiba Formations.

The most important part of the workflow is the merging between well log electrofacies and the 3D seismic facies model. The electrofacies derived from well log provide a detailed specific rock types at well locations, and the seismic facies would fill the gap in the areas without well control. Initially, the seismic facies were calibrated to the electrofacies rock types at each well location, and the prediction was extended laterally throuh out the area following the defined structural framework. The final product of this workflow is a "Most Likely" 3D lithofacies within the target intervals. A 3D probability volume was also generated to quantify the level of uncertainty, especially in the areas lacking of well control.

The resulting 3D lithofacies model has reasonably demonstrated the ability to predict rock facies distribution within the Natih and Shuaiba Formations. The output model has provided a key element to identify prospective areas for stratigraphic traps within the study area. The 3D lithofacies model based on this integrated workflow was also useful for the prospect evaluation and the ranking process of the Natih truncation and Shuaiba clinoform prospects identified in the exploration study. The results have confirmed the presence of the Natih-C1 reservoir and also the predicted rock facies distribution in the upper part of Shuaiba Clinoform called "shoal" anticipated to be good reservoir quality in each prospect. In addition, the results of this work have been utilized for development activities, such as the updated 2011 3D static and dynamic reservoir models, which have demonstrated an improvement in terms of production history matching, reserves determination, and production forecast.