Various techniques are used in industry to determine the reservoir connectivity. The rock-based methods such as seismic mapping and well-to-well correlations present some challenges in subsalt and salt overhang deposits. While fluid based methods such as pressure gradients are traditionally used to infer the lack of connectivity and oftentimes cannot confirm the presence of it. Recent advances in asphaltene science have made it possible to clarify asphaltene distribution mechanism in reservoir allowing to address reservoir connectivity.

The asphaltene distribution in the reservoir is characterized by an equation-of-state (EoS) proposed by Flory, Huggins and Zuo. The classical approach of estimating an asphaltene gradient of the reservoir fluid involves acquiring downhole samples and performing laboratory analysis. However, since the asphaltene content is associated with the coloration of hydrocarbons, a method has been proposed to delineate the asphaltene gradient at reservoir conditions by measuring the color differences of formation fluid with depth using optical fluid analyzer. Integrating the color data from optical fluid analyzer with the proposed equation-of-state, it is possible to elucidate the connectivity of the individual layers.

This paper presents the results of the well logging campaign conducted in the field located in Western Kazakhstan, where new oil deposits were discovered below the salt overhang in Triassic and Permo-Triassic sandstone formations. Several exploration wells were drilled in different blocks of the field. Advanced open hole logging suite comprised of standard logging methods, nuclear magnetic resonance and wireline formation tester was run in all the wells to characterize the reservoir. The wireline formation tester toolstring included an optical fluid analyzer module, which allowed to measure optical density values of an oil at different depths in each of the wells. The study shows how the asphaltene gradient of an oil column constructed from optical density data in conjunction with geological and petrophysical data can be used to delineate reservoir attribute such as lateral connectivity. The analysis confirmed the hypothesis on the lack of reservoir connectivity between the two blocks separated by faults.

The prediction of the asphaltene gradient based on the previously acquired data offers a new way to optimize wireline logging by comparing the predicted with the actual color gradient in real-time during downhole fluid analysis stations, while the tool is still in the well, to uncover the unknown source of reservoir complexity.

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