Energy & Fuels, Vol.30, No.11, 9097-9105, 2016
Experimental Investigation on Imbibition-Front Progression in Shale Based on Nuclear Magnetic Resonance
Spontaneous imbibition is the main mechanism responsible for the retention of large amounts of fracturing fluid during the flowback period in shale gas development. Studying the mechanism of imbibition will help optimize flowback design and improve the accuracy of production prediction. Previous experiments have mainly focused on studying the relationship between the amount of liquid imbibed into shale samples and the time. However, these experiments could not describe visually the liquid saturation distribution along rock samples. In this paper, a chemical potential-dominated flow mechanism model is presented, and nuclear magnetic resonance is adopted to obtain the water saturation distribution curve in the shale rock sample during spontaneous imbibition. The tight sandstone sample is also investigated for comparison. The effects of clay mineral content, fluid salt concentration, and surfactant solution on the water saturation distribution curve are systematically investigated. Results show that the advancing distance of the water saturation front in shale rock is shorter than that in tight sandstone at the same time. Furthermore, the slope of the curve in shale rock is higher. A positive correlation also exists between the front forward distance and clay content. Front forward distance is longer in sample with high clay content. Given the existence of osmotic pressure, the shale rock sample imbibed with water has longer front forward distance than the one imbibed with 10 wt % KCL solution. The shale rock samples imbibed with surfactant solution have a shorter water saturation front advancing distance because of lower capillary pressure. This study aims to provide a new method for the analysis of spontaneous imbibition in shale rock. The water saturation distribution curves can be used as target-match data to get fitted capillary pressure curves in a numerical simulation model of shale gas and obtain an accurate production prediction.