The design and implementation of grouting treatments in rock masses are procedures that require continuous adjustment of parameters and criteria to optimize the results. In this proposal we describe a set of tools that enhance decision-making for this type of jobs particularly in dam projects. The methodology is focused on hydrogeological zoning of the site and its constant update combining engineer's experience with artificial intelligence techniques to integrate the site knowledge; as well as the evaluation of grouting results for different scrutiny scales, with special attention on the relationship between water absorption and grout consumption.


Several methodologies for design, implementation and evaluation for grouting rock masses have been developed for the solution of specific problems and tested in diverse geological conditions. Each of these methodologies is focused on results evaluation for different scrutiny scales (Table 1) and is employed to assist decision-making before or during the grouting process.

Some methods define specifications for grouting each stage of the borehole, making theoretical, semi empirical or experience-based considerations to define basic parameters as maximum pressure, maximum volume, grouting time, flow rate, etc. Ultimately each approach aim to optimize the injection process, adjusting volumes or the grouting time required to obtain satisfactory results, reducing risk of creating new flow paths or unnecessary grout travels, and enhancing the mixture properties to achieve adequate penetrability and long-term behaviour. Some of these criteria have been widely used in dam projects, for example the concept of Grouting Based on Facts to define the maximum pressure and volume (Ewert, 1997), the GIN method (Lombardi & Deere, 1993; El Tani, 2012), or the North American standards based on Apparent Lugeon measures (Naudts, 1995; Bruce 2011); on the other hand, there are relatively new criteria that have shown good results for dam grouting as the Aperture Control Method (Bonin et al., 2012; Carter et al., 2012) or the Real Time Grouting Control Method (Stille et al., 2012).

The results verification for a larger scale, taking into account the behavior of a group of holes located in areas with similar geological characteristics, has been presented by several authors as Deere (1982) and Ewert (1985, 1997), which require a statistical evaluation of the data and where generally a reduction in consumption is expected by decreasing the distance between boreholes. This evaluation allows the identification and correction of some results irregularities attributable to the geology or the grout curtain characteristics (e.g., karstic areas or inadequate drilling direction).

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