Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Phenomena exposure from the large scale gas injection test (Lasgit) dataset using a bespoke data analysis toolkit

Bennett, Daniel, Cuss, R. J., Vardon, P. J., Harrington, J. F. and Thomas, Hywel Rhys 2014. Phenomena exposure from the large scale gas injection test (Lasgit) dataset using a bespoke data analysis toolkit. Geological Society Special Publication 400 (1) , pp. 497-505. 10.1144/SP400.5

[img]
Preview
PDF - Accepted Post-Print Version
Download (605kB) | Preview

Abstract

The Large Scale Gas Injection Test (Lasgit) is a field-scale experiment designed to study the impact of gas buildup and subsequent migration through an engineered barrier system. Lasgit has a substantial experimental dataset containing in excess of 21 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 difficult to observe phenomena, has been developed and applied to the dataset. The preliminary application of the toolkit, presented here, has resulted in a large number of phenomena being indicated/quantified, including highlighting of second-order events (small gas flows, perturbations in stress/pore-water sensors, etc.) and quantification of temperature record frequency content. Localized system behaviour has been shown to occur along with systematic aberrant behaviours that remain unexplained.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Additional Information: Pdf uploaded in accordance with publisher's policies at http://www.sherpa.ac.uk/romeo/issn/0305-8719/ (accessed 2.7.15).
Publisher: Geological Society of London
ISSN: 0305-8719
Date of First Compliant Deposit: 30 March 2016
Last Modified: 21 Feb 2019 15:02
URI: http://orca.cf.ac.uk/id/eprint/66338

Citation Data

Cited 1 time in Google Scholar. View in Google Scholar

Cited 1 time in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics