Key challenges to seismic imaging of shallow heavy oil recovery in North Kuwait include how to acquire high quality seismic data, and how to carry out seismic inversion and quantitative interpretation (QI) for reservoir characterization. Kuwait Oil Company acquired a high resolution baseline 3D seismic survey over an area of 700m × 700m in January 2017, followed by a six week time-lapse 4D seismic survey, as part of geophysical monitoring project for studying the reservoir and associated steam flood pilot performance. This paper presents the technical methodology and interpretation results of these 3D and 4D seismic surveys.

Highly pressurized and heated steam injected into a reservoir will move in all directions to drive out in situ heavy oil. It is important to understand where the steam has traveled to, which is controlled by reservoir properties such as formation pressure, porosity, and permeability. Seismic inversion and quantitative Interpretation (QI) are proven tools that can extract information about reservoir properties such as sand probability and porosity, which can be used to estimate steam chamber size, optimize the steam injection strategies and update the geological static modeling.

The 3D and 4D seismic inversions have confirmed that the data quality meets the QI requirement for such a shallow reservoir. The main outcomes from the pre and post stack inversions are the sand porosity and sand probability. Due to steam injection in the reservoir, seismic amplitude anomalies and time-shifts were observed from seismic slices and time-delay processing, which could be used for estimation of steam injection size. Sand porosity and probability maps were created of the upper zone overlying the lower steamed reservoir, and clearly indicate that steam from the lower reservoir passed through the intervening baffle and spread to the upper zone, which means that the thin baffle in this area could not prevent steam from traveling upwards.

The key enabler for proper seismic quantitative interpretation is the rock physical modeling, which searches and establishes the relationship between reservoir properties (i.e. sand probability and porosity) and seismic attributes such as P-Impedance and Poisson's Ratio (Vp/Vs). Inputs into the rock modeling process include bulk density logs, compressional and shear sonic logs, and interpreted porosity and clay volume petrophysical logs. A sand probability function is first established using P-impedance and Poisson's Ratio, and then reservoir properties are extracted from the seismic inversion.

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