Shear and compressive wave data acquisition using multicomponent vibrating source and landstreamer

2021 ◽  
Author(s):  
Andre Pugin ◽  
Barbara Dietiker ◽  
Kevin Brewer ◽  
Timothy Cartwright
Keyword(s):  
Leading Edge ◽  
Data Sets ◽  
Compressive Wave ◽  
Near Surface ◽  
Source Type ◽  
Receiver Array ◽  
Surface Data ◽  
Source Orientation ◽  
Refracted Waves ◽  
Wave Modes

<p>In the vicinity of Ottawa, Ontario, Canada, we have recorded many multicomponent seismic data sets using an in-house multicom­ponent vibrator source named Microvibe and a landstreamer receiver array with 48 3-C 28-Hz geophones at 0.75-m intervals. The receiver spread length was 35.25 m, and the near-offset was 1.50 m. We used one, two or three source and three receiver orientations — vertical (V), inline-horizontal (H1), and transverse-horizontal (H2). We identified several reflection wave modes in the field records — PP, PS, SP, and SS, in addition to refracted waves, and Rayleigh-mode and Love-mode surface waves. We computed the semblance spectra of the selected shot records and ascertained the wave modes based on the semblance peaks. We then performed CMP stacking of each of the 9-C data sets using the PP and SS stacking velocities to compute PP and SS reflection profiles.</p><p>Despite the fact that any source type can generate any combination of wave modes — PP, PS, SP, and SS, partitioning of the source energy depends on the source orientation and VP/VS ratio. Our examples demonstrate that the most prominent PP reflection energy is recorded by the VV source-receiver orientation, whereas the most prominent SS reflection energy is recorded by the H2H2 source-receiver orientation with possibility to obtain decent shear wave near surface data in all other vibrating and receiving directions.</p><p>Pugin, Andre and Yilmaz, Öz, 2019. Optimum source-receiver orientations to capture PP, PS, SP, and SS reflected wave modes. The Leading Edge, vol. 38/1, p. 45-52. https://doi.org/10.1190/tle38010045.1</p>

Optimum source-receiver orientations to capture PP, PS, SP, and SS reflected wave modes

2019 ◽  
Vol 38 (1) ◽  
pp. 45-52 ◽  
Author(s):  
Andre Pugin ◽  
Öz Yilmaz
Keyword(s):  
Seismic Source ◽  
Data Sets ◽  
S Wave ◽  
Reflection Mode ◽  
Near Surface ◽  
Reflected Wave ◽  
Source Type ◽  
Receiver Array ◽  
Soil Site ◽  
Wave Modes

We conducted a field experiment at the geotechnical research soil site #1 in Ottawa, Ontario, Canada, and recorded 9-C seismic data along a short line traverse 90 m in length using a multicomponent vibrator source named Microvibe and a landstreamer receiver array with 48 3-C 28-Hz geophones at 0.75-m intervals. The receiver spread length is 35.25 m, and the near-offset is 1.50 m. We used three source and three receiver orientations — vertical (V), inline-horizontal (H1), and transverse-horizontal (H2). We identified several reflection wave modes in the field records — PP, PS, SP, and SS, in addition to refracted waves, and Rayleigh-mode and Love-mode surface waves. We computed the semblance spectra of the selected shot records and ascertained the wave modes based on the semblance peaks. We then performed CMP stacking of each of the 9-C data sets using the PP, PS/SP, and SS stacking velocities. This field test convincingly demonstrates that there is no pure P- or S-wave land seismic source — any source type can generate any combination of wave modes — PP, PS, SP, and SS, and partitioning of the source energy depends on the source orientation and VP/VSratio. All three receiver orientations will capture all reflected wave modes — PP, PS, SP, and SS — but with varying strength. The magnitude of the reflection amplitude captured by one of the three receiver orientations will depend on the reflector depth, source-receiver offset, and the near-surface P- and S-wave velocities in the vicinity of the receiver location. The most prominent PP reflection energy is recorded by the VV source-receiver orientation, whereas the most prominent SS reflection energy is recorded by the H2H2 source-receiver orientation. Additionally, the optimum source-receiver orientation for PS reflection mode is VH1, and the optimum source-receiver orientation for SP reflection mode is H1V.

scholarly journals A Finescale Radar Examination of the Tornadic Debris Signature and Weak-Echo Reflectivity Band Associated with a Large, Violent Tornado

2016 ◽  
Vol 144 (11) ◽  
pp. 4101-4130 ◽  
Author(s):  
Jana Lesak Houser ◽  
Howard B. Bluestein ◽  
Jeffrey C. Snyder
Keyword(s):  
Cross Sections ◽  
Doppler Radar ◽  
Leading Edge ◽  
Doppler Velocity ◽  
Near Surface ◽  
High Resolution Data ◽  
Rapid Scan ◽  
Surface Data ◽  
X Band ◽  
Strong Gradient

Abstract High-resolution data of the tornadic debris signature (TDS) and weak-echo reflectivity band (WRB) associated with a large, violent tornado on 24 May 2011 in central Oklahoma are examined using a rapid-scan, X-band, polarimetric, mobile Doppler radar. Various characteristics of these features and their evolution are examined over time intervals of 20 s or less. The formation of the TDS, debris fallout, and inhomogeneities in the TDS structure, are analyzed from volumetric and single-elevation observations. Constant-radius vertical cross sections of Doppler velocity, reflectivity, and copolar cross-correlation coefficient are compared at various times during the tornado’s life cycle; from them it is found that the weak echo column (WEC) is considerably narrower than the TDS and the WEC is confined to the strong gradient of Doppler velocities in the tornado’s core. The TDS of the mature tornado extends radially outward, bound approximately by the 40 m s−1 radial isodop. Rapid-scan, near-surface data were collected for a period of 6 min, during which 2-s single-elevation PPI updates at 1° were available at heights below 100 m above radar level. During this period, a WRB associated with a visually observed horizontal vortex developed east of the tornado, along the leading edge of the secondary rear-flank gust front, as the tornado was rapidly intensifying. A relationship was noted between reduced radar-observed reflectivity and increased radar-observed radial convergence/divergence in the vicinity of the horizontal vortex as it strengthened. This feature is qualitatively analyzed and hypotheses explaining its generation and structure are discussed.

Comparison of ERA40 and NCEP/DOE near-surface data sets with other ISLSCP-II data sets

2006 ◽  
Vol 111 (D22) ◽  
Author(s):  
Alan K. Betts ◽  
Mei Zhao ◽  
P. A. Dirmeyer ◽  
A. C. M. Beljaars
Keyword(s):  
Data Sets ◽  
Near Surface ◽  
Surface Data

scholarly journals The influence of surface gravity waves on the injection of turbulence in the upper ocean

2014 ◽  
Vol 21 (3) ◽  
pp. 713-733 ◽  
Author(s):  
M. Bakhoday Paskyabi ◽  
I. Fer
Keyword(s):  
Gravity Waves ◽  
Surface Gravity ◽  
Data Sets ◽  
Langmuir Circulation ◽  
Data Set ◽  
Near Surface ◽  
Wave Forcing ◽  
Surface Gravity Waves ◽  
Surface Data ◽  
Closure Scheme

Abstract. Observations were made in the near-surface layer, at about 8 m depth in 132 m deep water off the coast of Ålesund in Norway, for a duration of 2.5 months in late 2011. The measurement period covers the passage of two low pressure systems with substantial wind and wave forcing. The time series of the dissipation rate of turbulent kinetic energy, ε, and the estimates of surface gravity waves are analysed. Dissipation rates varied by 5 orders of magnitude and reached 10-5–10-4 W kg−1 in conditions when wind speed exceeded 15 m s−1 and the significant wave height was of the order of 10 m. The data set suggests substantial injection of turbulence from breaking surface gravity waves and Langmuir turbulence. To support and interpret the observations, numerical calculations are conducted using a second-order turbulence closure scheme based on the Mellor–Yamada level 2.5 scheme, modified to incorporate the near-surface processes such as Langmuir circulation and wave breaking. The results from a run forced by observed wind and wave fields compare favourably with the observations. Comparisons with other near-surface data sets available from the literature lend confidence on our dissipation measurements and the wave-forced simulations.

Inflight icing data gathering during routine flight operations — a case study

2001 ◽  
Vol 105 (1051) ◽  
pp. 501-516 ◽  
Author(s):  
A. P. Brown
Keyword(s):  
Data Gathering ◽  
Winter Season ◽  
Leading Edge ◽  
General Aviation ◽  
Data Sets ◽  
Large Droplet ◽  
Event Data ◽  
Flight Operations ◽  
Lower Corner

Abstract For the purpose of the design and certification of inflight icing protection systems for transport and general aviation aircraft, the eventual re-definition/expansion of the icing environment of FAR 25/JAR 25, Appendix C is under consideration. Such a re-definition will be aided by gathering as much inflight icing event data as reasonably possible, from widely-different geographic locations. The results of a 12-month pilot programme of icing event data gathering are presented. Using non-instrumented turboprop aircraft flying upon mid-altitude routine air transport operations, the programme has gathered observational data from across the British Isles and central France. By observing a number of metrics, notably windscreen lower-corner ice impingement limits, against an opposing corner vortex-flow, supported by wing leading edge impingement limits, the observed icing events have been classified as ‘small’, ‘medium’ or ‘large’ droplet. Using the guidance of droplet trajectory modelling, MVD values for the three droplet size bins have been conjectured to be 15, 40 and 80mm. Hence, the ‘large’ droplet category would be in exceedance of FAR/JAR 25, Appendix C. Data sets of 117 winter-season and 55 summer-season icing events have been statistically analysed. As defined above, the data sets include 11 winter and five summer large droplet icing encounters. Icing events included ‘sandpaper’ icing from short-duration ‘large’ droplets, and a singular ridge formation icing event in ‘large’ droplet. The frequency of ‘large’ droplet icing events amounted to 1 in 20 flight hours in winter and 1 in 35 flight hours in summer. These figures reflect ‘large’ droplet icing encounter probabilities perhaps substantially greater than previously considered. The ‘large’ droplet events were quite localised, mean scale-size being about 6nm.

scholarly journals Initiation and Maintenance Mechanisms for Heavy Precipitation System over a Mountainous Island under a Prevailing Monsoon Current

2016 ◽  
Vol 5 (2) ◽  
pp. 90
Author(s):  
Y.-L. Lin ◽  
K.-Y. Lee ◽  
C.-S. Chen ◽  
F.-Y. Cheng ◽  
P.-L. Lin ◽  
...  
Keyword(s):  
Heavy Rainfall ◽  
Mesoscale Model ◽  
Convective Available Potential Energy ◽  
Leading Edge ◽  
Western Slope ◽  
Mountain Range ◽  
Unstable Flow ◽  
Near Surface ◽  
Precipitation System ◽  
Early Afternoon

In this study, the initiation and maintenance mechanisms of two long-lived, summer heavy rainfall systems over Taiwan are investigated by performing observational data analyses and numerical simulations using a mesoscale model. For both cases of 9-10 July 2008 (Case A) and 18-19 August 2006 (Case B), the heavy rainfall system developed over the western slope of the Central Mountain Range (CMR) under low-level prevailing southwesterly and westerly flows in early afternoon, respectively. These heavy rainfall systems were moving westward toward Taiwan Strait from CMR, while the embedded individual cells were moving in the opposite direction, behaving like a multicell storm. It was also found these individual cells were initiated, enhanced, and then maintained at the leading edge of the near-surface cool outflow and merged with the heavy rainfall systems which became long-lived. These heavy rainfall systems were classified as an upstream propagating precipitation system in a low Froude-number, conditionally unstable flow with high convective available potential energy (CAPE) or Regime I as proposed in a previous study.

Elliptic Airfoil Stall Analysis With Trailing Edge Slots

2010 ◽  
Author(s):  
Jonathan Kweder ◽  
Mary Ann Clarke ◽  
James E. Smith
Keyword(s):  
Lift Coefficient ◽  
Leading Edge ◽  
Surface Velocity ◽  
Circulation Control ◽  
West Virginia University ◽  
Trailing Edge ◽  
Near Surface ◽  
Wind Speeds ◽  
Edge Location ◽  
Stall Angle

Circulation control (CC) is a high-lift methodology that can be used on a variety of aerodynamic applications. This technology has been in the research and development phase for over sixty years primarily for fixed wing aircraft where the early models were referred to as “blown flaps”. Circulation control works by increasing the near surface velocity of the airflow over the leading edge and/or trailing edge of a lifting surface This phenomenon keeps the boundary layer jet attached to the wing surface thus increasing the lift generated on the surface. The circulation control airflow adds energy to the lift force through conventional airfoil lift production and by altering the circulation of stream lines around the airfoil. For this study, a 10:1 aspect ratio elliptical airfoil with a chord length of 11.8 inches and a span of 31.5 inches was inserted into the West Virginia University Closed Loop Wind Tunnel and was tested at varying wind speeds (80, 100, and 120 feet per second), angle of attack (zero to sixteen degrees), and blowing coefficients, ranging from 0.0006 to 0.0127 depending on plenum pressure. By comparing the non-circulation controlled wing with the active circulation control data, a trend was found as to the influence of circulation control on the stall characteristics of the wing for trailing edge active control. For this specific case, when the circulation control is in use on the 10:1 elliptical airfoil, the stall angle decreased, from eight degrees to six degrees, while providing a 70% increase in lift coefficient. It should be noted that due to the trailing edge location of the circulation control exit jet, a “virtual” camber is created with the free stream air adding length to the overall airfoil. Due to this phenomena, the actual stall angle measured increased from eight degrees on the un-augmented airfoil, to a maximum of twelve degrees.

Quaternion-based anisotropic inversion for flexural waves in horizontal transverse isotropic formations with unmatched sources: A synthetic example

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. A69-A74 ◽  
Author(s):  
Fuqiang Zeng ◽  
Wenzheng Yue ◽  
Chao Li
Keyword(s):  
Structural Information ◽  
Amplitude Ratio ◽  
Flexural Wave ◽  
Data Sets ◽  
Flexural Waves ◽  
P Waves ◽  
Source Type ◽  
Transverse Isotropic ◽  
Sonic Logging ◽  
Incident Waves

The anisotropy of elastic waves has been widely used to obtain structural information on formations in geosciences research. Flexural wave splitting is generally applied to evaluate anisotropy with geophysical inversion methods. Cross-dipole sonic logging has been widely used for anisotropic inversions in horizontal transverse isotropic formations. Traditional methods assume that fast and slow flexural waves are similar in shape and are not dispersive and that the radiation characteristics of the two orthogonal dipole sources are identical. The two above assumptions cannot be satisfied in field conditions. Therefore, the methods used in anisotropy inversion based on these assumptions will lead to inaccurate results. The introduction of the amplitude ratio (AR), the ratio of slow to fast flexural waves, which is not dependent on the source type, can eliminate the wave-shape assumption. Two data sets from orthogonally oriented receivers can be constructed as a quaternion array. Fast and slow flexural waves are the two main incident waves, and other arrivals such as P-waves can be taken as noise. The AR and a quaternion multiple signal classification algorithm are used to demonstrate how to improve the anisotropic inversion and avoid these assumptions. Compared with the traditional method, the new method presents better inversion results for the synthetic example with two different sources. We have determined that the inversion residual from the new objective function can be used to indicate the inversion quality.

Seismic diffraction separation in the near-surface: Detection of high contrast voids in unconsolidated soils

Geophysics ◽  
2021 ◽  
pp. 1-72
Author(s):  
Parsa Bakhtiari Rad ◽  
Craig J. Hickey
Keyword(s):  
Soft Soil ◽  
Processing Parameters ◽  
Imaging Method ◽  
Data Sets ◽  
High Contrast ◽  
Near Surface ◽  
Time Migration ◽  
Diffraction Imaging ◽  
Dip Angle ◽  
Scattering Time

Seismic diffractions carry the signature of near-surface high-contrast anomalies and need to be extracted from the data to complement the reflection processing and other geophysical techniques. Since diffractions are often masked by reflections, surface waves and noise, a careful diffraction separation is required as a first step for diffraction imaging. A multiparameter time-imaging method is employed to separate near-surface diffractions. The implemented scheme makes use of the wavefront attributes that are reliable fully data-derived processing parameters. To mitigate the effect of strong noise and wavefield interference in near-surface data, the proposed workflow incorporates two wavefront-based parameters, dip angle and coherence, as additional constraints. The output of the diffraction separation is a time trace-based stacked section that provides the basis for further analysis and applications such as time migration. To evaluate the performance of the proposed wavefront-based workflow, it is applied to two challenging field data sets that were collected over small culverts in very near-surface soft soil environments. The results of the proposed constrained workflow and the existing unconstrained approach are presented and compared. The proposed workflow demonstrates superiority over the existing method by attenuating more reflection and noise, leading to improved diffraction separation. The abundance of unmasked diffractions reveal that the very near-surface is highly scattering. Time migration is carried out to enhance the anomaly detection by focusing of the isolated diffractions. Although strong diffractivity is observed at the approximate location of the targets, there are other diffracting zones observed in the final sections that might bring uncertainties for interpretation.

Data Sets

2013 ◽  
Author(s):  
James B. Elsner ◽  
Thomas H. Jagger
Keyword(s):  
Model Building ◽  
Careful Analysis ◽  
Logical Structure ◽  
Fortran Program ◽  
Data Sets ◽  
Data Set ◽  
Near Surface ◽  
Wind Speeds ◽  
The North ◽  
The One

Hurricane data originate from careful analysis of past storms by operational meteorologists. The data include estimates of the hurricane position and intensity at 6-hourly intervals. Information related to landfall time, local wind speeds, damages, and deaths, as well as cyclone size, are included. The data are archived by season. Some effort is needed to make the data useful for hurricane climate studies. In this chapter, we describe the data sets used throughout this book. We show you a work flow that includes importing, interpolating, smoothing, and adding attributes. We also show you how to create subsets of the data. Code in this chapter is more complicated and it can take longer to run. You can skip this material on first reading and continue with model building in Chapter 7. You can return here when you have an updated version of the data that includes the most recent years. Most statistical models in this book use the best-track data. Here we describe these data and provide original source material. We also explain how to smooth and interpolate them. Interpolations are needed for regional hurricane analyses. The best-track data set contains the 6-hourly center locations and intensities of all known tropical cyclones across the North Atlantic basin, including the Gulf of Mexico and Caribbean Sea. The data set is called HURDAT for HURricane DATa. It is maintained by the U.S. National Oceanic and Atmospheric Administration (NOAA) at the National Hurricane Center (NHC). Center locations are given in geographic coordinates (in tenths of degrees) and the intensities, representing the one-minute near-surface (∼10 m) wind speeds, are given in knots (1 kt = .5144 m s−1) and the minimum central pressures are given in millibars (1 mb = 1 hPa). The data are provided in 6-hourly intervals starting at 00 UTC (Universal Time Coordinate). The version of HURDAT file used here contains cyclones over the period 1851 through 2010 inclusive. Information on the history and origin of these data is found in Jarvinen et al (1984). The file has a logical structure that makes it easy to read with a FORTRAN program. Each cyclone contains a header record, a series of data records, and a trailer record.

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