Developing High Resolution Static and Dynamic Models for Waterflood History Matching and EOR Evaluation of Giant Middle Eastern Carbonate Reservoir

Masalmeh, Shehadeh K. (Shell Technology Oman) | Wei, Lingli (Shell International Exploration & Production B.V.) | Hillgartner, Heiko (Petroleum Development Oman) | Al-Mjeni, Rifaat (Shell) | Blom, Carl P.A. (Shell Intl E&P)

OnePetro 

Enhanced oil recovery (EOR) has become increasingly important to maintain and extend the production plateaus of existing oil reservoirs. Simulation models for EOR studies require the right level of spatial resolution to capture reservoir heterogeneity. Data acquired from the dedicated observation wells are essential in defining the required resolution to capture reservoir heterogeneity. For giant reservoirs with long production history, their full field models usually have grid block sizes that are of similar scale as the distance between injectors and observation wells, with the consequence of losing the value of the time lapse saturation logs from dedicated observation wells. Therefore, using high resolution sector models, especially from the part of the reservoir where static and dynamic data sets are rich, is a must.

The objective of this paper is to present an improved and integrated reservoir characterization, modelling and water and gas injection history matching procedure of a giant Cretaceous carbonate reservoir in the Middle East. The applied workflow integrates geological, petrophysical, and dynamic data in order to understand the production history and the remaining oil saturation distribution in the reservoir. Large amounts of field data, including time lapse saturation logs from observation wells, have been collected over the last decades to provide insight into the sweep efficiency and flow paths of the injected water.

Iterative simulations were performed to investigate different scenarios and various sensitivities with each iteration involving an update of the static model to honor both the dynamic and core/log data. While applying this iterative process it was also acknowledged that conventional core data (e.g. 1 plug per foot) may not capture the high permeability streaks in these heterogeneous reservoirs that control much of the reservoir flow behaviour, hence much denser plugging and core examination is required. In addition, permeability upscaling procedures need to take into account the fact that core plugs may not represent the effective permeability of the larger connected vuggy pore systems.

The improved understanding of reservoir heterogeneity, the more robust reservoir characterization, and the improved history matching demonstrates that a better representation of reservoir dynamics is achieved. This provides a solid platform for designing and planning future EOR schemes.

1. Introduction

Carbonate reservoirs contain more than 50% of world's remaining conventional hydrocarbon reserves and on average have relatively low recovery factors. With the insight that the era of "easy oil?? (conventional oil and natural gas that are relatively easy to extract) is phasing out, enhanced oil recovery (EOR) becomes increasingly important to maintain and extend the production plateaus from existing oil reservoirs. EOR technologies, however, require a refined understanding of reservoir heterogeneities and dynamic field performance. Simulation models for EOR studies need to have the right level of resolution and details. Often, we find that for a giant reservoir with a long waterflood history, working with full field models with coarse simulation grids is not adequate to understand the reservoir performance and calibrate the static model. Therefore, using high resolution sector models, especially from the part of the reservoir where static and dynamic data sets are rich, is a must.