Seismic imaging of the carbon dioxide gas cloud at Sleipner using 3D elastic time-lapse full waveform inversion

Abstract

a b s t r a c tA solution to the increasing greenhouse gas emissions is carbon capture and storage. At the Sleipner field, offshore Norway, carbon dioxide is separated from the produced gas and injected into the Utsira formation at approximately 1000 m depth. The Utsira formation is a high porosity saline aquifer that is 200-300 m thick in the injection area. In 1994, two years before the injection started, a seismic survey was acquired. The survey has been followed up by several seismic surveys acquired to monitor the migration of the injected gas. The full waveform inversion (FWI) method is a non-linear inverse method for estimating subsurface elastic parameters. Time-lapse FWI has recently been suggested as a monitoring tool for resolving time-lapse changes directly in the elastic parameter models. This paper presents an application of a three dimensional implementation of isotropic elastic time-lapse FWI applied on time-lapse field data from the Sleipner area. The baseline dataset is the 1994 dataset, whereas the monitor dataset is the survey acquired in 2006 after ten years of injection. Time-lapse FWI is used to estimate separate elastic parameter models for both the baseline and the monitor datasets. The results show that FWI is able to estimate detailed elastic parameter models that produce synthetic data that match the field data. The inverted models are used in a pre-stack depth migration method to yield detailed seismic images of the Sleipner before and after the injection of the gas. The gas cloud after ten years of injection is clearly visible on the monitor seismic images. The baseline and monitor seismic images show events and discontinuities that can explain the migration pathways of the injected gas through the Utsira formation.

Simultaneous joint migration inversion for high‐resolution imaging/inversion of time‐lapse seismic datasets

“…Regarding the first question, least‐squares migration (LSM) and full‐waveform inversion (FWI) are two popular time‐lapse processing methods Ayeni and Biondi (); Routh et al . (); Raknes and Arntsen (); Raknes, Weibull and Arntsen (); Yang et al . (); Kazei and Alkhalifah ().…”

Real‐time deep‐learning inversion of seismic full waveform data for CO2 saturation and uncertainty in geological carbon storage monitoring

“…Compared to partial waveform inversion such as first‐arrival travel time inversion, FWI minimizes misfits between recorded and predicted full seismograms in an iterative manner (Virieux & Operto, 2009; Fichtner, 2010; Virieux et al ., 2017), reconstructing a high‐resolution velocity model. Time‐lapse FWI is capable of monitoring subtle changes in reservoir properties associated with CO 2 migration and leakage (Raknes et al ., 2015; Li et al ., 2021).…”

Target-Oriented Time-Lapse Elastic Full-Waveform Inversion Constrained by Deep Learning-Based Prior Model

“…[8], [9]. However, the inverse problem suffers from high illposedness because seismic observations do not contain enough information to define the unknown model parameters [10].…”