Overcoming The Challenges Of Building 3D Stochastic Reservoir Models Using Conceptual Geological Models: A Case Study

Abstract

Abstract Construction of reliable 3-D geological models for reservoir simulation requires a detailed understanding of facies distribution and connectivity within the interval of interest. In particular, it relies on lateral and vertical variabilities in reservoir quality within and between different flow units. Despite thorough data integration and interpretation, several challenges were encountered while integrating geological knowledge into a 3-D stochastic geological model. Some unconventional approaches had to be taken in order to best reflect the geological understanding of the reservoirs while using commercially available software. For example, the 3-D stochastic facies modelling of the reservoir units was based on conceptual geological models. Models were constructed for each reservoir zone through the analysis and integration of core and log data from 50 wells in the study area. However, it was seen that utilising either object modelling or pixel-based modelling methods alone would not generate stochastic models that adequately honoured the conceptual geological model. Consequently, the two modelling methods were used together to generate combined models. A further challenge was to determine adequate facies proportions for each reservoir zone. The direct use of facies statistics from well logs in stochastic modeling lead to unrealistic facies distributions. To overcome this, dummy wells were added to make facies proportions matches the conceptual models rather than basing it on the existing wireline logs alone. Taking these unconventional approaches lead to a greater accuracy of reservoir and porosity distribution around the reservoir. Moreover, the methodology used in this study provides new ideas that can be used in modeling other fields with fluvial depositional settings. Introduction Field development projects involve substantial financial investment and are typically designed around predictions of future reservoir performance. These predictions are generated from a reservoir simulation model, which is based on a geological model. Consequently, the reliability of the simulation model is highly dependent on the accuracy of the geological model (Jian et al., 2002). Several challenges are encountered in the creation of a reliable geological model. One is to build a model with a very limited amount of subsurface information available. Other challenges include defining flow units in the reservoir and identifying reservoir heterogeneities that effect fluid flow (i.e. channels in a fluvial system) (Jian et al., 2002). A flow unit is defined as a volume of reservoir rock that has very similar geological and petrophysical properties, and is distinctly different from the fluid flow properties of the other flow units (Aminian et al., 2002). To overcome these challenges, geoscientists conduct integrated reservoir characterisation studies. The literature contains well documented integrated reservoir studies which have helped in selecting the appropriate workflow for reservoir development by improving the quality of the geological model (Marquez et al., 2001; Tye and Hickey, 2001; Gilman et al., 2002; Meng et al., 2002; Ates et al., 2003). Such studies have demonstrated their importance in reservoir management and future development. One of the important breakthroughs in reservoir characterisation in recent years is the use of high-resolution sequence stratigraphy, 3-D seismic and geological analogues to construct a realistic 3-D conceptual reservoir model which helps in exploration and development (Lang et al., 2002; Strong et al., 2002). Reservoir characterisation studies are usually undertaken to address existing reservoir problems such as unexpected water production or optimisation of future development plans.