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Silicate Gel for In-depth Placement - Gelation Kinetics and Pre-flush DesignNormal access

Authors: A. Omekeh, A. Hiorth, A. Stavland and A. Lohne
Event name: IOR 2017 - 19th European Symposium on Improved Oil Recovery
Session: Conformance
Publication date: 24 April 2017
DOI: 10.3997/2214-4609.201700282
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 876.16Kb )
Price: € 20

Sodium silicate gel has historically been used in the oil industry for near wellbore water shut-off. Relatively recent application of Sodium silicate gel for in-depth water diversion have generated some interest. Its main advantage is that its mobility is water-like before it gels. For in-depth diversion purposes, the gelation kinetics need to be appropriately modeled for better prediction of gel placement. This paper makes a review of different gel kinetics models found in the literature. To our knowledge, the models presented in the literature are fit-for-purpose, i.e. they are based on correlations that are fitted to the lab data. Although they describe the lab data well, it is challenging to use them to predict field scale operations, where there are significant temperature, pH, and salinity gradients throughout the reservoir. In this paper, we present an improved silicate gel model. Our model takes into account two important rate step in the formation of silica gel from a sodium silicate solution: the nucleation rate of monosilisic acid to form critical nucleus of nanosized colloids and an aggregation rate of the nano-colloids to form a pore blocking gel. It is important to allow for nano sized colloids as these are small enough to be transported a significant distance from the well before they aggregate into larger clusters that can block the pores. The model explains well the experimental observations where the gelation time is sensitive to pH, temperature, silicate concentration and brine composition. We also investigate the preflush volume and concentration that is needed to minimize the indirect rock-brine interaction that can alter the designed gelation time. Results from this simulation shows that the Cation Exchange Capacity (CEC), Mineral distribution and Temperature profile are critical design criteria for the preflush volume and concentration.

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