Data integration in three-dimensional geostatistical porosity modeling of Hanifa Reservoir in Berri Field, Saudi Arabia

Understanding the spatial distribution of reservoir properties such as lithology and porosity is essential for development drilling, reserve estimation and fluid flow simulation. Data come from various sources at various scales with varying degrees of reliability. Data from wells alone have limitations and they are not enough to produce an accurate view of the reservoir. Geostatistics provides a toolbox for geologists and engineers to use in analyzing data and transferring such analysis and interpretations to the task of reservoir modeling and forecasting.; The objective of this thesis is to evaluate the added value of integrating different data types such as facies and seismic impedance in 3-D geostatistical porosity models. To achieve this goal four porosity models were built. The first porosity model was generated based on porosity logs from wells only. The other three porosity models were generated by different combination of porosity logs, facies and seismic impedance. These models have been evaluated by using qualitative and quantitative methods.; The results of this study showed that facies-based porosity models yield better definition of porosity in vertical and lateral directions than other models. This is due to the use of the facies model as constraint for porosity distribution. The accuracy of the seismic controlled model was better than all other models. This is due to the fact that seismic has a more dense spatial samples density than wells. Porosity from the wells-only model has the lowest accuracy compared to the other models, which shows the importance of introducing other type of data in porosity modeling.