During the last decade, distributed acoustic sensing (DAS) has emerged as a new technology for seismic acquisition. DAS has the potential to reduce the cost of permanent monitoring operations over time as it offers long equipment survivability and requires minimum maintenance. However, broad adoption of DAS technology still faces some challenges, such as low sensitivity and high levels of noise compared to conventional seismic sensors. Recent developments in fiber-optic systems and cable designs aim to overcome these limitations. To understand how DAS can be used in monitoring applications, it is important to know how it behaves with varying offsets and incidence angles. An offset VSP survey was acquired, at the CO2CRC Otway Project, using a straight single-mode fiber, a straight "enhancedbackscatter" fiber, and a conventional three-component geophone tool. The results from this survey show that DAS has the potential to provide similar, or even superior, quality data sets as conventional geophones.

Vertical seismic profile (VSP) is one of the technologies for monitoring hydrocarbon production and CO2 geosequestration. However, quantitative interpretation of time‐lapse VSP is challenging due to its irregular distribution of source‐receiver offsets. One way to overcome this challenge is to use full waveform inversion (FWI), which does not require regular offsets. We present a workflow of elastic FWI applied to offset vertical seismic profile data for the purpose of identification and estimation of time‐lapse changes introduced by injection of 15,000 t of CO2‐rich gas mixture at 1.5 km depth. Application of this workflow to both synthetic and field data shows that elastic FWI is able to detect and quantify the time‐lapse anomaly in P wave velocity with the magnitude of 100–150 m/s.

The article considers the Information-analytical system of cardiographic information functional diagnostics, which allows expanding the functionality of using miniature medical devices for non-invasive diagnostics of parameters of complex dynamic biomedical systems, using the example of cardio-intervals of the cardiovascular system. The system is based on not only the methods of the deterministic-stochastic approach but also the methods of the theory of chaos-self-organization, as a new scientific approach in the natural sciences. The method is based on calculating the parameters of quasi attractors and analyzing matrices of pairwise comparisons of time series of complex biomedical systems, which allows quantitatively and qualitatively describing the chaotic dynamics of the system state vector behaviour, obtaining objective information about changes in the functional state of the system, and also warning about these changes in time (if pathologies), which creates conditions for the status of the functional systems of the human body physiological monitoring.

Distributed acoustic sensing (DAS) is a rapidly developing technology particularly useful for the acquisition of vertical seismic profile (VSP) surveys. DAS data are increasingly used for seismic imaging, but not for estimating rock properties. We propose a workflow for estimating elastic properties of the subsurface using full waveform inversion (FWI) of DAS VSP data. Whereas conventional borehole geophones usually measure three components of particle velocity, DAS measures a single quantity, which is an approximation of the strain or strain rate along the fiber. Standard FWI algorithms are developed for particle velocity data, and hence their application to DAS data requires conversion of these data to particle velocity along the fiber. This conversion can be accomplished by a specially designed filter. Field measurements show that the conversion result is close to vertical particle velocity as measured by geophones. Elastic time-domain FWI of a synthetic multi-offset VSP dataset for a vertical well shows that the inversion of the vertical component alone is sufficient to recover elastic properties of the subsurface. Application of the proposed workflow to a multioffset DAS dataset acquired at the CO2CRC Otway Project site in Victoria, Australia reveals salient subhorizontal layering consistent with known geology of the site. The inverted VP model at the well location matches the upscaled VP log with a correlation coefficient of 0.85.