Distributed Acoustic Sensing in Geophysics. Группа авторов

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СКАЧАТЬ r(z) distribution of reflection/scattering coefficient along fiber axis with optical phase shift included Re Z real part of interference output t′ “fast” optical time scale t “slow” acoustic time scale u(z, t) ground displacement u parameter of function v(z) fiber local speed along its axis and also ground speed V(z) interference visibility along fiber x parameter of integration: coordinate along fiber axis z coordinate along fiber axis z ₁ parameter of function z ₂ parameter of function β optical wave propagation constant of fiber β ₀ unperturbed optical wave propagation constant of fiber ΔΩ(z) distance variation of Doppler shift along fiber Δv distance variation of ground speed ΔF geophone bandwidth δ the Dirac delta function ε ₁ maximum recoverable strain for first order algorithm ε ₂ maximum recoverable strain for second order algorithm ε _min minimum strain level Φ_min phase noise Γ incident angle of seismic wave λ laser wavelength Λ spacing of geophones μ flicker noise coefficient ω circular frequency of light Ω(z) Doppler frequency shift of light ψ ₀ phase shift between delayed optical fields in interferometer Φ shift of backscattered light ρ backscattering intensity coefficient θ(z) Heaviside step function τ(z) input pulse τ optical pulsewidth

2 Important Aspects of Acquiring Distributed Acoustic Sensing (DAS) Data for Geoscientists

       Mark E. Willis1, Andreas Ellmauthaler1, Xiang Wu2, and Michel J. LeBlanc1

       1Halliburton, Houston, Texas, USA

       2Halliburton Far East Pte. Ltd., Singapore

      ABSTRACT

      Fiber‐optic distributed acoustic sensing (DAS) is a technology used for many strain measurement applications, including seismic monitoring. Because it is relatively new to the market, most geoscientists are unfamiliar with the details of the technology, but nevertheless are required to make important acquisition parameter decisions such as the type of fiber‐optic glass to use, the deployment method for the fiber‐optic cable, the gauge length, and how to diminish the effect of optical noise. This chapter provides a non‐theoretical, practical approach to making these decisions in order to obtain high‐quality DAS data sets.

2.1. INTRODUCTION

      The exciting and rapidly evolving technology of DAS, which uses optical fibers to sense local changes in strain, acquires seismic data for many applications, such as vertical seismic profiling (VSP) (Barfoot, 2013; Mestrayer et al., 2011; Mateeva et al., 2017), earthquake monitoring (Martin et al., 2017), hydraulic‐fracture geometry characterization (Jin & Roy, 2017), and microseismic monitoring (Hull et al., 2017). Improvements in the interrogator design (Hartog, 2017) and deployment methods (Ellmauthaler et al., 2020) have increased the signal‐to‐noise ratio (SNR) of the raw measurements, while processing improvements (Ellmauthaler et al., 2017; Chen et al., 2019; Willis et al., 2020) have allowed the removal of specific fiber‐optic noise patterns in the data.

      Acquiring seismic data using accelerometers, geophones, and seismometers is a well‐developed and understood practice. Ironically, because it is so common, we rarely stop to question the actual field hardware used to acquire data or the software to process it; thus, it is frequently treated as a trusted commodity. In contrast, DAS technology is not as widely understood by the geophysics community, just as the requirements and applications of seismic data might not be generally grasped by fiber‐optic engineers and physicists who build and maintain DAS hardware and software. This situation creates the potential for degradations in the quality of seismic data acquired by DAS. This chapter describes the practical aspects for obtaining quality borehole seismic data using DAS to bridge the gap between fiber‐optic technologists and the geophysics community.

2.2. FIBER‐OPTIC SENSOR

      2.2.1. Sensing from Backscattered Light

At the center of СКАЧАТЬ