Field assessment of elastic full-waveform inversion of combined accelerometer and distributed acoustic sensing data in a vertical seismic profile configuration

检波器 地质学 分布式声传感 垂直地震剖面 环境地质学 加速度计 反演(地质) 区域地质 钻孔 声学 遥感 计算机科学 地震学 光纤传感器 光纤 电信 岩土工程 构造学 末端学 变质岩石学 物理 操作系统
作者
Matthew Eaid,Scott Keating,K. A. Innanen,Marie Macquet,Don C. Lawton
出处
期刊:Geophysics [Society of Exploration Geophysicists]
卷期号:88 (6): WC163-WC180 被引量:13
标识
DOI:10.1190/geo2023-0066.1
摘要

ABSTRACT Seismic data are a significant facilitator for monitoring in carbon capture and sequestration projects, providing high-resolution images of fluid migration, using, for example, full-waveform inversion (FWI). Distributed acoustic sensing (DAS), a relatively novel technology for wavefield sampling, is well suited for this type of monitoring. Using noninvasive optical fibers, DAS allows for dense spatial sampling along the entire length of the wellbore, without disrupting operations. Permanently installed in the wellbore, typically behind casing, DAS offers highly repeatable and dense sampling of the transmitted wave modes crucial to seismic monitoring of injected carbon dioxide (CO2). However, the DAS data consist of measurements of strain along the tangent of the fiber and therefore do not transfer directly to conventional FWI algorithms. Incorporation of DAS data in their native strain (or strain-rate) form in standard FWI algorithms, requires changing the definition of the receiver sampling operator to use geometric information about the fiber to supply tangential strain measurements to the FWI residual. The theoretical developments are applied to invert field vertical seismic profile data acquired with DAS fiber and accelerometers at a CO2 sequestration site in Newell Country, Alberta. Our method incorporates DAS data and accelerometer data in one objective function and allows us to tune the relative importance we wish to place on each data set. This method also transfers to noncollocated sensors, for example, surface-deployed geophones and borehole fiber. The inverted models contain features expected from the geology of the field site, and data modeled in the inverted models compare favorably with the field data for these sensor types. The models are derived from data acquired prior to CO2 injection, representing baseline models for future time-lapse studies planned at the field research station.

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