Fracture properties estimation using distributed acoustic sensing recording of guided waves in unconventional reservoirs

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. M85-M95 ◽  
Author(s):  
Ariel Lellouch ◽  
Mark A. Meadows ◽  
Tamas Nemeth ◽  
Biondo Biondi
Keyword(s):  
Large Scale ◽  
Guided Waves ◽  
Geometric Analysis ◽  
Unconventional Reservoirs ◽  
Low Velocity ◽  
Sh Waves ◽  
Hydraulic Stimulation ◽  
Acoustic Sensing ◽  
Arrival Times ◽  
Distributed Acoustic Sensing

Perforation shots excite guided waves that propagate in a low-velocity unconventional shale reservoir. They have a frequency content of up to 700 Hz and are dispersive. We have analyzed horizontal crosswell perforation shots recorded by a distributed acoustic sensing (DAS) array. As guided waves propagate through a previously stimulated area, we observe a dramatic influence on the guided SH waves in the form of delayed arrival times, scattering, phase incoherency, and loss of amplitude and frequency. The leaky compressional waves undergo a gradual slowdown. Using a simple geometric analysis of the spatial locations of the distortions in the direct arrivals of the guided SH waves, we can estimate the half-lengths of the induced fractures, which range from 50% to 75% of the distance between the perforated and monitoring wells. Furthermore, we find that the propagation disturbances originate from the middle of the stimulated area. Other diffracted signals, notably from frac plugs, are clearly visible in the data. We report the first large-scale use of DAS records of guided waves. Their potential for high-resolution imaging and inversion of subsurface properties before and after hydraulic stimulation opens new possibilities for the use of seismology in optimizing production from unconventional reservoirs.

scholarly journals P-wave crustal tomography of Greece with use of an accurate two-point ray tracer

1997 ◽  
Vol 40 (1) ◽  
Author(s):  
G. Drakatos ◽  
G. Karantonis ◽  
G. N. Stavrakakis
Keyword(s):  
Large Scale ◽  
Velocity Structure ◽  
Three Dimensional ◽  
Seismic Energy ◽  
Aegean Sea ◽  
P Wave ◽  
Low Velocity ◽  
Aegean Area ◽  
Arrival Times ◽  
Horizontal Variations

The three-dimensional velocity structure of the crust in the Aegean sea and the surrounding regions (34.0º-42.OºN, 19.0ºE-29.0ºE) is investigated by inversion of about 10000 residuals of arrival times of P-wave from local events. The resulting velocity structure shows strong horizontal variations due to the complicated crustal structure and the variations of crustal thickness. The northern part of the region generally shows high velocities. In the inner part of the volcanic arc (Southern Aegean area), relatively low velocities are observed, suggesting a large-scale absorption of seismic energy as confirmed by the low seismicity of the region. A low velocity zone was observed along the subduction zone of the region, up to a depth of 4 km. The existence of such a zone could be due to granitic or other intrusions in the crust during the uplift of the region during Alpidic orogenesis.

scholarly journals Isochronal maps at Mt. Etna volcano (Italy): a simple and reliable tool for investigating large-scale heterogeneities

1997 ◽  
Vol 40 (5) ◽  
Author(s):  
G. Patanè ◽  
C. Centamore ◽  
S. La Delfa
Keyword(s):  
Large Scale ◽  
Volcanic Edifice ◽  
P Wave ◽  
Etna Volcano ◽  
Low Velocity ◽  
Seismic Stations ◽  
Arrival Times ◽  
Mt Etna ◽  
Wave Arrival ◽  
Feeding Systems

This paper analyses twelve etnean earthquakes which occurred at various depths and recorded at least by eleven stations. The seismic stations span a wide part of the volcanic edifice; therefore each set of direct P-wave arrival times at these stations can be considered appropriate for tracing isochronal curves. Using this simple methodology and the results obtained by previous studies the authors make a reconstruction of the geometry of the bodies inside the crust beneath Mt. Etna. These bodies are interpreted as a set of cooled magmatic masses, delimited by low-velocity discontinuities which can be considered, at present, the major feeding systems of the volcano.

Danish earthquake recorded by distributed acoustic sensing (DAS)

2020 ◽  
Author(s):  
Camilla Rasmussen ◽  
Peter H. Voss ◽  
Trine Dahl-Jensen
Keyword(s):  
Field Test ◽  
Signal To Noise Ratio ◽  
Field Tests ◽  
Small Subset ◽  
Fibre Optic ◽  
Data Set ◽  
Acoustic Sensing ◽  
Arrival Times ◽  
Fibre Optic Cable ◽  
Distributed Acoustic Sensing

<p>On September 16th 2018 a Danish earthquake of local magnitude 3.7 was recorded by distributed acoustic sensing (DAS) in a ~23 km long fibre-optic cable. The data are used to study how well DAS can be used as a supplement to conventional seismological data in earthquake localisation. One of the goals in this study is extracting a small subset of traces with clear P and S phases to use in an earthquake localisation, from the 11144 traces the DAS system provide. The timing in the DAS data might not be reliable, and therefore differences in arrival times of S and P are used instead of the exact arrival times. <br>The DAS data set is generally noisy and with a low signal-to-noise ratio (SNR). It is examined whether stacking can be used to improve SNR. The SNR varies a lot along the fibre-optic cable, and at some distances, it is so small that the traces are useless. Stacking methods for improving SNR are presented.</p><p>A field test at two location sites of the fibre-optic cable was conducted with the purpose of comparing DAS data with seismometer data. At the field sites, hammer shots were recorded by a small array of three STS-2 sensors located in a line parallel to the fibre-optic cable. The recordings generally show good consistency between the two data sets. <br>In addition, the field tests are used to get a better understanding of the noise sources in the DAS recording of the earthquake. There are many sources of noise in the data set. The most prominent are a line of windmills that cross the fibre-optic cable and people walking in the building where the detector is located. Also, the coupling between the fibre-optic cable and the ground varies along the cable length due to varying soil type and wrapping around the fibre-optic cable, which is also evident in field test data. Furthermore, the data from the field tests are used to calibrate the location of the fibre-optic cable, which is necessary for using the DAS data in an earthquake localisation. <br>Data processing is done in Matlab and SEISAN.</p>

Large-scale multiplexed weak reflector array fabricated with a femtosecond laser for a fiber-optic quasi-distributed acoustic sensing system

2020 ◽  
Vol 45 (13) ◽  
pp. 3685 ◽  
Author(s):  
Mengshi Wu ◽  
Chi Li ◽  
Xinyu Fan ◽  
Changrui Liao ◽  
Zuyaun He
Keyword(s):  
Femtosecond Laser ◽  
Large Scale ◽  
Fiber Optic ◽  
Acoustic Sensing ◽  
Sensing System ◽  
Distributed Acoustic Sensing

scholarly journals Towards Detecting Red Palm Weevil Using Machine Learning and Fiber Optic Distributed Acoustic Sensing

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1592
Author(s):  
Biwei Wang ◽  
Yuan Mao ◽  
Islam Ashry ◽  
Yousef Al-Fehaid ◽  
Abdulmoneim Al-Shawaf ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Early Detection ◽  
Large Scale ◽  
Fiber Optic ◽  
Red Palm Weevil ◽  
Healthy Tree ◽  
Acoustic Sensing ◽  
Palm Weevil ◽  
Distributed Acoustic Sensing

Red palm weevil (RPW) is a detrimental pest, which has wiped out many palm tree farms worldwide. Early detection of RPW is challenging, especially in large-scale farms. Here, we introduce the combination of machine learning and fiber optic distributed acoustic sensing (DAS) techniques as a solution for the early detection of RPW in vast farms. Within the laboratory environment, we reconstructed the conditions of a farm that includes an infested tree with ∼12 day old weevil larvae and another healthy tree. Meanwhile, some noise sources are introduced, including wind and bird sounds around the trees. After training with the experimental time- and frequency-domain data provided by the fiber optic DAS system, a fully-connected artificial neural network (ANN) and a convolutional neural network (CNN) can efficiently recognize the healthy and infested trees with high classification accuracy values (99.9% by ANN with temporal data and 99.7% by CNN with spectral data, in reasonable noise conditions). This work paves the way for deploying the high efficiency and cost-effective fiber optic DAS to monitor RPW in open-air and large-scale farms containing thousands of trees.

DAS observations and modeling of perforation-induced guided waves in a shale reservoir

2019 ◽  
Vol 38 (11) ◽  
pp. 858-864 ◽  
Author(s):  
Ariel Lellouch ◽  
Steve Horne ◽  
Mark A. Meadows ◽  
Stuart Farris ◽  
Tamas Nemeth ◽  
...  
Keyword(s):  
Guided Waves ◽  
Low Velocity ◽  
S Waves ◽  
Velocity Models ◽  
Shale Formation ◽  
Shale Reservoir ◽  
Distributed Acoustic Sensing ◽  
Induced Changes ◽  
Synthetic Modeling ◽  
High Frequency Content

Perforation shots can be recorded by downhole distributed acoustic sensing (DAS) arrays. In this study, we demonstrate that guided waves induced by perforation shots propagate in a low-velocity shale reservoir layer. Such guided waves have a high frequency content of up to 700 Hz and are dispersive, with lower frequencies propagating faster than higher frequencies. They can propagate as P- and S-waves, and their group velocity is higher than their phase velocity. The high temporal and spatial resolution of the DAS array enables unaliased recording despite short wavelengths. The guided waves disappear from the records when the well exits the shale formation. Synthetic modeling predicts their existence for acoustic and elastic cases in simple velocity models. We show that perforation shots from an offset well at a distance of about 270 m can be recorded by the DAS array. Induced guided S-waves undergo significant disturbances while propagating through previously stimulated zones. These disturbances manifest as kinematic and dynamic changes of the recorded wavefield and as scattered events. The nature of the stimulation-induced changes is interpreted as a combination of unknown spatial and temporal effects linked to fluid-filled fractures. Guided waves hold tremendous potential for high-resolution reservoir imaging and should be used in conjunction with conventional DAS arrays and state-of-the-art DAS interrogators.

scholarly journals Teleseismic P-residual study in the Italian region - inferences on large scale anisotropic structure of the subcrustal lithosphere

1998 ◽  
Vol 41 (1) ◽  
Author(s):  
J. Plomerová ◽  
V. Babuska ◽  
R. Scarpa
Keyword(s):  
Travel Time ◽  
Upper Mantle ◽  
Large Scale ◽  
Velocity Structure ◽  
P Wave ◽  
Anisotropic Structure ◽  
Low Velocity ◽  
Arrival Times ◽  
Station Corrections ◽  
Lateral Variations

Jeffreys-Bullen (absolute) and relative P-wave travel-time residuals were analyzed over Italy and its surrounding using P arrival times from the ISC bulletins supplemented by the data from local observatories. We analyzed the travel-time station corrections by two independent methods to obtain information on lateral variations of the velocity structure over the area and a view of possible upper mantle anisotropy. In the first method, the station corrections are computed as a constant and two cosine terms with appropriate phase shifts. Besides a static term, the second method allows us to study the relative residuals in dependence both on azimuths and incidence angles and thus to investigate their spatial variations and to map lateral variations of anisotropic structure of the subcrustal lithosphere. The high and low-velocity directions inferred from the spatial distribution of the relative residuals as well as the high- and low-velocity upper mantle heterogeneities reflect the geodynamic development of the region, governed by the collision between the African and Eurasian plates

Detecting Leaks in Abandoned Gas Wells with Fibre-Optic Distributed Acoustic Sensing

2014 ◽  
Author(s):  
K. Boone ◽  
A. Ridge ◽  
R. Crickmore ◽  
D. Onen
Keyword(s):  
Fibre Optic ◽  
Gas Wells ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing
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