Spatial and temporal properties of noise from the Aquistore CCS pilot permanent surface array

C. E. Birnie, A. Stork, L. Roach, D. Angus, S. Rost

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

2 Citations (Scopus)

Abstract

Synthetic datasets are commonly used to aid interpretation, test hypothesis and as a benchmarking tool for evaluating the robustness of seismic imaging algorithms and defining confidence limits under which an algorithm will perform. Noise within these datasets is often modelled as white and/or Gaussian and therefore does not account for the spatial and temporal variations and trends observed in noise present within field data. This study defines a noise classification scheme that systematically represents these temporal and spatial variations and trends. Noise signals identified at the Aquistore injection site were classified using the scheme defined into the noise categories: stationary, non-stationary and pseudo-nonstationary noise. Future studies will focus on creating a mathematical description of the signals focusing on non-stationary and non-linear aspects with the aim to build this into a synthetic seismic dataset as realistic noise.

Original languageEnglish
Title of host publication3rd Sustainable Earth Sciences Conference and Exhibition: Use of the Sub-Surface to Serve the Energy Transition
PublisherEuropean Association of Geoscientists and Engineers, EAGE
Pages161-165
Number of pages5
ISBN (Print)9781510814196
Publication statusPublished - 2015
Event3rd Sustainable Earth Sciences Conference and Exhibition: Use of the Sub-Surface to Serve the Energy Transition - Celle, Germany
Duration: 13 Oct 201515 Oct 2015

Conference

Conference3rd Sustainable Earth Sciences Conference and Exhibition: Use of the Sub-Surface to Serve the Energy Transition
CountryGermany
CityCelle
Period13/10/1515/10/15

Fingerprint Dive into the research topics of 'Spatial and temporal properties of noise from the Aquistore CCS pilot permanent surface array'. Together they form a unique fingerprint.

Cite this