Analysis of signal to noise and directivity characteristics of DAS VSP at near and far offsets — A CO2CRC Otway Project data example

Correa, Julia; Egorov, Anton; Tertyshnikov, K.; Bóna, Andrej; Pevzner, Roman; Dean, Tim; Freifeld, Barry; Marshall, Stephen W.

doi:10.1190/tle36120994a1.1

Cited by 102 publications

(37 citation statements)

References 11 publications

(13 reference statements)

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“…After conversion to acceleration, the DAS data displays the same polarity as the geophone data, also for the 190 upgoing reflections. This is in line with previous results obtained by Correa et al (2017).…”

Section: Comparison Of Das and Borehole Geophone Data 165supporting

confidence: 94%

Vertical seismic profiling with distributed acoustic sensing images the Rotliegend geothermal reservoir in the North German Basin down to 4.2 km depth

Henninges¹,

Martuganova²,

Stiller³

et al. 2020

Preprint

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Abstract. We performed vertical seismic profiling at the Groß Schönebeck site in order to gain more detailed information on the structural setting and geometry of the geothermal reservoir, which is comprised of volcanic rocks and sediments of Lower Permian age. During the four-day survey, we acquired data for 61 source positions with the novel method of distributed acoustic sensing (DAS), using hybrid wireline fiber-optic sensor cables deployed in two 4.3 km deep wells. We show that wireline cable tension has a significant effect on data quality. While most of the recorded data has a very good signal-to-noise ratio, individual sections of the profiles are affected by characteristic coherent noise patterns. This ringing noise is a result of how the sensor cable is mechanically coupled to the borehole wall, and it can be suppressed to a large extent using suitable filtering methods. After conversion to strain rate, the DAS data exhibits a high similarity to the vertical component data of a conventional borehole geophone. Upgoing reflections are nevertheless recorded with opposite polarity, which needs to be taken into account during further seismic processing and interpretation. We derived accurate time-depth relationships, interval velocities, and corridor stacks from the recorded data. Based on integration with other well data and geological information, we show that the top of a porous and permeable sandstone interval of the geothermal reservoir can be identified by a positive reflection event. Overall, the sequence of reflection events shows a different character for both wells, which is explained by lateral changes in lithology. The top of the volcanic rocks has a somewhat different seismic response, and no stronger reflection event is obvious at the postulated top of the Carboniferous. The thickness of the volcanic rocks can therefore not be inferred from individual reflection events in the seismic data alone. The DAS method has enabled measurements at elevated temperatures up to 150 °C over extended periods and has led to significant time and cost savings compared to deployment of a conventional geophone chain.

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Section: Comparison Of Das and Borehole Geophone Data 165supporting

confidence: 94%

Vertical seismic profiling with distributed acoustic sensing images the Rotliegend geothermal reservoir in the North German Basin down to 4.2 km depth

Henninges¹,

Martuganova²,

Stiller³

et al. 2020

Preprint

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show abstract

“…For permanent monitoring applications, due to the inherent robustness of the fibre-optic cable and affordability, DAS provides a significantly more economical alternative than the conventional seismic sensors. VSP data acquired with DAS on CRC-3 well present high signal to noise ratio with a potential to image the injection interval (Correa et al, 2017).…”

Section: Field Experiments Setupmentioning

confidence: 99%

Assessment of the permanent seismic sources for borehole seismic monitoring applications: CO2CRC Otway Project

Yavuz

Correa

Pevzner

et al. 2019

ASEG Extended Abstracts

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“…Several case studies have illustrated successful detection of microseismic events with DAS technology (Webster et al ., 2013; Farhadiroushan, 2018; Karrenbach et al ., 2019). The signal‐to‐noise ratio (SNR) in DAS is generally smaller than in geophones while using standard telecommunications fibre (Correa et al ., 2017), but recently, engineered enhanced backscatter fibre technology has shown an SNR similar to geophones (Richter et al ., 2019).…”

Section: Introductionmentioning

confidence: 99%

Convolutional neural networks for automated microseismic detection in downhole distributed acoustic sensing data and comparison to a surface geophone array

Binder

Tura

2020

Geophysical Prospecting

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Distributed acoustic sensing is a growing technology that enables affordable downhole recording of strain wavefields from microseismic events with spatial sampling down to ∼1 m. Exploiting this high spatial information density motivates different detection approaches than typically used for downhole geophones. A new machine learning method using convolutional neural networks is described that operates on the full strain wavefield. The method is tested using data recorded in a horizontal observation well during hydraulic fracturing in the Eagle Ford Shale, Texas, and the results are compared to a surface geophone array that simultaneously recorded microseismic activity. The neural network was trained using synthetic microseismic events injected into real ambient noise, and it was applied to detect events in the remaining data. There were 535 detections found and no false positives. In general, the signalto-noise ratio of events recorded by distributed acoustic sensing was lower than the surface array and 368 of 933 surface array events were found. Despite this, 167 new events were found in distributed acoustic sensing data that had no detected counterpart in the surface array. These differences can be attributed to the different detection threshold that depends on both magnitude and distance to the optical fibre. As distributed acoustic sensing data quality continues to improve, neural networks offer many advantages for automated, real-time microseismic event detection, including low computational cost, minimal data pre-processing, low false trigger rates and continuous performance improvement as more training data are acquired.

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Analysis of signal to noise and directivity characteristics of DAS VSP at near and far offsets — A CO2CRC Otway Project data example

Cited by 102 publications

References 11 publications

Vertical seismic profiling with distributed acoustic sensing images the Rotliegend geothermal reservoir in the North German Basin down to 4.2 km depth

Vertical seismic profiling with distributed acoustic sensing images the Rotliegend geothermal reservoir in the North German Basin down to 4.2 km depth

Assessment of the permanent seismic sources for borehole seismic monitoring applications: CO2CRC Otway Project

Convolutional neural networks for automated microseismic detection in downhole distributed acoustic sensing data and comparison to a surface geophone array

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