Quantitative quality of distributed acoustic sensing vertical seismic profile data

Abstract

Great advances have been made in distributed acoustic sensing (DAS) vertical seismic profile (VSP) data acquisition hardware and software. Here, we capture a quantitative assessment of the quality of DAS data at a single point in time. We apply comprehensive testing methods to determine the reliability of the data and its suitability as a supplement to geophone data or to gain access to wells where it would be difficult to deploy geophones. The test measurements are made on DAS and geophone data, which were collected at the same time and in the same well. We analyze the first breaks for waveform consistency, signal-to-noise (S/N) ratio, and slowness. Then, we examine the corridor stacks for waveform consistency and S/N ratio. Finally, we test the properties of the measurement, including linearity, repeatability, reliability, and response, as a function of the angle of incidence of a seismic wave to the fiber. The results show that the DAS VSP data provide accurate formation slowness logs and reliable amplitude information suitable for creating seismic images and corridor stacks.

A Survey on Distributed Fibre Optic Sensor Data Modelling Techniques and Machine Learning Algorithms for Multiphase Fluid Flow Estimation

“…The physical values, when accurately estimated, can provide high accuracy multiphase flow information as depicted in Figure 10 . However, prediction uncertainties are expected due to factors such as volatilities of the surrounding physical environment, sensor noise, systematic errors in the measurement method, corruptions within the data, and other problems during value extraction process that might arise [ 94 ]. Thus, including error estimations and uncertainty values, when providing the multiphase information for realtime monitoring solution is often a requirement.…”

Urban Near‐Surface Seismic Monitoring Using Distributed Acoustic Sensing

“…These requirements are met by a passive system enabled by distributed acoustic sensing (DAS) that we present in this paper. DAS arrays can measure strain along kilometers of optical fiber, producing large data sets with kilohertz time sampling and at submeter channel spacing (Parker et al, 2014 recording in oil and gas reservoirs (Willis et al, 2016). Recent success of DAS applications using existing telecommunication infrastructures Jousset et al, 2018;Yu et al, 2019) demonstrates its cost effectiveness in deployment and maintenance.…”

“…DAS arrays can measure strain along kilometers of optical fiber, producing large data sets with kilohertz time sampling and at submeter channel spacing (Parker et al, 2014). Over the past decade, DAS has been a rapidly evolving technology for downhole recording in oil and gas reservoirs (Willis et al, 2016). Recent success of DAS applications using existing telecommunication infrastructures (Ajo-Franklin et al, 2019;Jousset et al, 2018;Yu et al, 2019) demonstrates its cost effectiveness in deployment and maintenance.…”

Correcting wavefield gradients for the effects of local small-scale heterogeneities

“…Nowadays, rotations can be measured using liquid-based motion sensors (Egorov et al 2015;Huang et al 2013), magneto-hydrodynamic sensors (Pierson et al 2016), ring laser gyroscopes (Schreiber et al 2009; Correcting wavefield gradients for the effects of local small-scale heterogeneities 3 Pancha et al 2000;McLeod et al 1998), mechanical sensors (Brokešová & Málek 2013) and more recently, using fiber-optic gyroscopes (Bernauer et al 2018;Lindner et al 2016;Kurzych et al 2014). Similarly, strains can be measured using Distributed Acoustic Sensing (DAS) (Willis et al 2016) and Distributed Vibration Sensing (DVS) (Dean et al 2017).…”