5:15 PM - 6:45 PM
[SVC28-P08] Numerical model for permeability enhancement prediction of igneous rocks stimulated with chelating agents under geothermal conditions
Keywords:EGS, Chelating agent, Permeability enhancement, Igneous rocks, Selective mineral dissolution
Enhanced geothermal systems (EGS) are a proven and highly viable renewable energy source, especially in areas with high geothermal temperatures. Conventional stimulations aim to improve the permeability of geothermal reservoirs by hydraulic or chemical techniques. However, these techniques have issues during their implementation, such as induced seismicity, reduced penetration from boreholes, and high reactivity. In recent years, chelating agents have been investigated as an alternative method for chemical stimulation. It has been reported in previous studies that aqueous solutions of glutamic acid-L-diacetic acid (GLDA) can rapidly and significantly enhance the permeability of granitic and volcanic rocks under both acidic and alkaline conditions. However, these studies described the applicability of chelating agents to enhance the permeability of specific fractured rock samples without a quantitative analysis to generalize the permeability enhancement effect. In this study, we conducted various simulations using a 2D fracture model, the mode of minerals of both granitic and andesitic rocks, and the dissolution rate of minerals by GLDA aqueous solution in the range of pH 4 – 10 to estimate the permeability enhancement factor as a function of solution pH and the aerial distribution of the target minerals. The results indicate a clear correlation between the aerial distribution of the mineral target and the permeability enhancement effect since more local constraints of the fluid paths are eliminated as the area attacked by GLDA increases. Furthermore, quartz has the highest impact on permeability enhancement in alkaline conditions since it occupies the largest area of GLDA influence. This information can be utilized as a prior estimation of permeability enhancement factor in the field by knowing an estimated distribution of target minerals and selecting the appropriate solution pH to get the desired effect. This modeling is a valuable contribution to spreading the use of chelating agents in large-scale modeling and, finally, in the actual geothermal fields.