Exploratory data analysis of the Large Scale Gas Injection Test (Lasgit) dataset, focusing on ‘second-order’ events around macro-scale gas flows

Abstract

AbstractThe Large Scale Gas Injection Test (Lasgit) is a field-scale experiment designed to study the impact of gas build-up and subsequent migration through an engineered barrier system (EBS). Lasgit has a substantial experimental dataset containing in excess of 26 million datum points. The dataset is anticipated to contain a wealth of information, ranging from long-term trends and system behaviours to small-scale or ‘second-order’ features. In order to interrogate the Lasgit dataset, a bespoke computational toolkit, designed to expose and quantify difficult to observe phenomena in large, non-uniform datasets, has been developed and applied. Presented results focus on the investigation and interpretation of second-order events occurring in close proximity (temporally and spatially) to a known macro-scale gas flow event that occurred during the second gas injection test. The similarity of the investigated event to dilatant flow observed in laboratory experiments is noted, as is the evidence for localized flow pathways in the bentonite EBS. The sensitivity of the toolkit's ability to highlight second-order events is also evaluated.