The Wara Sandstones formation is one of the main reservoirs of Greater Burgan field in Kuwait, producing under primary depletion since the late 1940s. A major water flood has recently begun and prior to this, a large-scale pilot (Early Wara Pressure Maintenance Project – EWPMP), has been initiated. As part of the scope of this study, representative geological models have been built to improve reservoir characterization to capture reservoir heterogeneities in the EWPMP area, which is crucial in building a dependable simulation model.

An innovative workflow combining geological (cores), petrophysical (RCAL, Rock-Types) and dynamic data (pressures), has been developed to generate a range of geological models, that will be later on screened and selected for dynamic simulation.

For a better representation of the sedimentological settings, five cored wells have been reviewed, to establish the main markers used for the geological modeling and to define core-based depositional environments. Six Rock-Types, calibrated on cores, and integrating RCA porosity-permeability data have identified in 56 wells to model the reservoir. The object-based modeling (OBM) approach combines aspect ratios and depositional trends to constrain the petrophysical properties distribution.

The Wara Formation has been deposited in tidally influenced fluvio-deltaic to estuarine environments. Six depositional environments have been defined on cores, dominated landward by bay head fluvial delta that laterally passes into tidal estuarine mouth bars and sandy estuarine bay. They have been extended to 111 wells in the area based on log signatures and patterns.

Based on analogs from similar ancient and modern deposits, aspect ratios for tidal bodies and sand body shapes were used in addition to the wells control to constrain the distribution of depofacies. Variations in sand body's size and shapes were used to generate poorly connected, fairly and highly connected sand bodies, giving a range of uncertainty to the models. The final sand body distributions have been validated using pressure data to match some pressure breaks related to shale barriers in the reservoir.

Once the geological framework has been built and validated, Rock-Types and petrophysical properties distributions were generated in the pre-defined geological framework, using a sequential indicator simulation approach.

The OBM approach allowed generating a range of models that reflects the geological settings and that better capture the reservoir heterogeneities and connectivity (assessed through the body geometry). The resulting generated petrophysical properties are then more geologically related.

Modeling complex reservoir heterogeneities in clastic environments is a challenge in the oil industry. An accurate sand body distribution is crucial for a good understanding and representation of the reservoir behavior in both static and dynamic models. The proposed innovative object-based modeling workflow that combines geological, dynamic and petrophysical data, used in this study may be a good alternative for geological models of similar depositional environments, to assess the complexity of such particular reservoirs.

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