Distributed Acoustic Sensing: Recent Field Data and Performance Validation

Abstracts ◽  
2013 ◽  
Author(s):  
T.R. Parker ◽  
S.V. Shatalin ◽  
M. Farhadiroushan ◽  
D. Miller
Keyword(s):  
Field Data ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing ◽  
And Performance ◽  
Performance Validation

scholarly journals Investigation of the Effects of Surrounding Media on the Distributed Acoustic Sensing of Helically-Wound Fiber-Optic Cable with Application to the New Afton Deposit, British Columbia

2020 ◽  
Author(s):  
Sepidehalsadat Hendi ◽  
Mostafa Gorjian ◽  
Gilles Bellefleur ◽  
Christopher D. Hawkes ◽  
Don White
Keyword(s):  
British Columbia ◽  
Numerical Modeling ◽  
Analytical Model ◽  
Field Data ◽  
Fiber Optic ◽  
Incident Angle ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing ◽  
Straight Fiber

Abstract. Fiber optic sensing technology has recently become popular for oil and gas, mining, geotechnical engineering, and hydrogeology applications. With a successful track record in many applications, distributed acoustic sensing using straight fiber optic cables has become a method of choice for seismic studies. However, distributed acoustic sensing using straight fiber optic cables is not able to detect off-axial strain, hence a helically wound cable design was introduced to overcome this limitation. The helically wound cable field data in New Afton deposit showed that the quality of the data is tightly dependent on the incident angle (the angle between the ray and normal vector of the surface) and surrounding media. We introduce a new analytical two-dimensional approach to determine the dynamic strain of a helically wound cable in terms of incident angle in response to elastic plane waves propagating through multilayered media. The method can be used to quickly and efficiently assess the effects of various materials surrounding a helically wound cable. Results from the proposed analytical model are compared with results from numerical modeling obtained with COMSOL Multiphysics, for scenarios corresponding to a real installation of helically wound cable deployed underground at the New Afton mine in British Columbia, Canada. Results from the analytical model are consistent with numerical modeling results. Our modeling results demonstrate the effects of cement quality, and casing installment on the quality of the helically-wound cable response. Numerical modeling results and field data suggest that, even if reasonably effective coupling achieved, the soft nature of the rocks in these intervals would result in low fiber strains for the HWC. The proposed numerical modeling workflow would be applied for more complicated scenarios (e.g., non-linear material constitutive behaviour, and the effects of pore fluids). The results of this paper can be used as a guideline for analyzing the effect of surrounding media and incident angle on the response of helically wound cable, optimizing the installation of helically wound cable in various conditions, and to validate boundary conditions of 3-D numerical model built for analyzing complex scenarios.

Distributed acoustic sensing coupling noise removal based on sparse optimization

2019 ◽  
Vol 7 (2) ◽  
pp. T373-T382 ◽  
Author(s):  
Jianyou Chen ◽  
Junrui Ning ◽  
Wenchao Chen ◽  
Xiaokai Wang ◽  
Wei Wang ◽  
...  
Keyword(s):  
Field Data ◽  
Noise Removal ◽  
Sparse Optimization ◽  
Quality Data ◽  
Data Set ◽  
Acoustic Sensing ◽  
Coupling Noise ◽  
Overcomplete Dictionary ◽  
Vsp Data ◽  
Distributed Acoustic Sensing

The industry treats the distributed acoustic sensing (DAS) system, which uses an optical fiber cable in vertical seismic profiling (VSP) data acquisition, as a new and fast-growing technology. The high-quality data set acquired from the DAS acquisition system can produce high-precision VSP images and obtain more detailed checkshots. However, in field data, the acquired VSP data set suffers from strong coherent DAS coupling noise. Many factors may cause coherent DAS coupling noise, such as the cable slapping and ringing due to the physical placement, the regular swing of the wireline in the well, and the uncoupling between the fiber cable and the casing. This DAS coupling noise reduces the signal-to-noise ratio and affects the subsequent processing and interpretation. Removing the DAS coupling noise can help to improve the quality of the VSP data set acquired with the DAS system. We have developed a sparse-optimization-based DAS coupling noise removing method. In the DAS-based VSP data set, the effective signal and the coupling noise have distinct morphological characteristics. The effective VSP signal has a wide bandwidth, whereas the DAS coupling noise appears in some narrow frequency bands in the frequency domain. The continuous wavelet transform and the discrete cosine transform can sparsely represent the effective VSP signal and DAS coupling noise, respectively. Therefore, we choose these two transforms as two sparse dictionaries and combine them to form an overcomplete dictionary. The morphological component analysis (MCA) can use the morphological difference between different components and the overcomplete dictionary to sparsely represent all components in the complicated signal. Based on the MCA theory, we use the block coordinate relaxation algorithm to separate the effective VSP signal and DAS coupling noise. Applications on a synthetic data set and two field data sets have validated the effectiveness of our method.

Combining Distributed Acoustic Sensing and Beamforming in a Volcanic Environment on Mount Meager, British Columbia.

2021 ◽  
Author(s):  
Sara Klaasen ◽  
Patrick Paitz ◽  
Jan Dettmer ◽  
Andreas Fichtner
Keyword(s):  
British Columbia ◽  
Power Distribution ◽  
High Frequency ◽  
Low Frequency ◽  
Volcanic Tremor ◽  
Extreme Environment ◽  
Volcanic Complex ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing ◽  
Volcanic Environment

<p>We present one of the first applications of Distributed Acoustic Sensing (DAS) in a volcanic environment. The goals are twofold: First, we want to examine the feasibility of DAS in such a remote and extreme environment, and second, we search for active volcanic signals of Mount Meager in British Columbia (Canada). </p><p>The Mount Meager massif is an active volcanic complex that is estimated to have the largest geothermal potential in Canada and caused its largest recorded landslide in 2010. We installed a 3-km long fibre-optic cable at 2000 m elevation that crosses the ridge of Mount Meager and traverses the uppermost part of a glacier, yielding continuous measurements from 19 September to 17 October 2019.</p><p>We identify ~30 low-frequency (0.01-1 Hz) and 3000 high-frequency (5-45 Hz) events. The low-frequency events are not correlated with microseismic ocean or atmospheric noise sources and volcanic tremor remains a plausible origin. The frequency-power distribution of the high-frequency events indicates a natural origin, and beamforming on these events reveals distinct event clusters, predominantly in the direction of the main peaks of the volcanic complex. Numerical examples show that we can apply conventional beamforming to the data, and that the results are improved by taking the signal-to-noise ratio of individual channels into account.</p><p>The increased data quantity of DAS can outweigh the limitations due to the lower quality of individual channels in these hazardous and remote environments. We conclude that DAS is a promising tool in this setting that warrants further development.</p>

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