VECTOR WAVEFIELD-SEPARATION TECHNIQUES FOR IMPROVED MULTI-COMPONENT SEISMIC EXPLORATION

2002 ◽  
Vol 42 (1) ◽  
pp. 613
Author(s):  
N. Hendrick ◽  
S. Hearn
Keyword(s):  
Vertical Component ◽  
P Wave ◽  
Seismic Exploration ◽  
Ocean Bottom ◽  
Production Environment ◽  
S Wave ◽  
Reflection Data ◽  
Wavefield Separation ◽  
Polarisation Analysis ◽  
Vector Separation

Analysis of multi-component seismic data commonly involves scalar processing of the vertical component to provide a conventional P-wave image, and scalar processing of the horizontal component(s) to yield an Swave image. A number of convincing examples now exist where such S-wave imagery has significantly enhanced hydrocarbon exploration.There is potential to achieve cleaner P- and S-wave images by more fully exploiting the true vector nature of multi-component reflection data. The simplest form of vector analysis, termed polarisation analysis, allows identification of different wave types. It does not, however, generally lead to effective wavefield separation, due to significant interference between the different waves in a typical exploration-seismic recording.More effective vector separation is possible if the particle-motion information from polarisation analysis is coupled with the more familiar tools of frequency and velocity filtering. Three related separation algorithms, termed MUSIC, IWSA and PIM are considered here. These techniques all utilise a parametric approach whereby wavefield slowness and polarisation are modelled simultaneously in the frequency domain.Synthetic and ocean-bottom cable examples are used to demonstrate practical issues relating to the use of these tools. The PIM algorithm is considered to be the most generally useful of the three multi-component wavefield separation algorithms. Implementation of these tools in a highly automated production environment is considered non-trivial. Hence, it is envisaged that such vector separation schemes will have most application for specialised data processing over identified target zones. Vector wavefield separation has the potential to amplify the considerable success already achieved with integrated P- and S-wave exploration.

scholarly journals S-wave experiments for the exploration of a deep geothermal carbonate reservoir in the German Molasse Basin

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Britta Wawerzinek ◽  
Hermann Buness ◽  
Hartwig von Hartmann ◽  
David C. Tanner
Keyword(s):  
Upper Jurassic ◽  
Carbonate Reservoir ◽  
P Wave ◽  
Seismic Survey ◽  
Seismic Exploration ◽  
Molasse Basin ◽  
S Wave ◽  
Induced Earthquakes ◽  
Conversion Point ◽  
Facies Classification

AbstractThere are many successful geothermal projects that exploit the Upper Jurassic aquifer at 2–3 km depth in the German Molasse Basin. However, up to now, only P-wave seismic exploration has been carried out. In an experiment in the Greater Munich area, we recorded S-waves that were generated by the conventional P-wave seismic survey, using 3C receivers. From this, we built a 3D volume of P- to S-converted (PS) waves using the asymptotic conversion point approach. By combining the P-volume and the resulting PS-seismic volume, we were able to derive the spatial distribution of the vp/vs ratio of both the Molasse overburden and the Upper Jurassic reservoir. We found that the vp/vs ratios for the Molasse units range from 2.0 to 2.3 with a median of 2.15, which is much higher than previously assumed. This raises the depth of hypocenters of induced earthquakes in surrounding geothermal wells. The vp/vs ratios found in the Upper Jurassic vary laterally between 1.5 and 2.2. Since no boreholes are available for verification, we test our results against an independently derived facies classification of the conventional 3D seismic volume and found it correlates well. Furthermore, we see that low vp/vs ratios correlate with high vp and vs velocities. We interpret the latter as dolomitized rocks, which are connected with enhanced permeability in the reservoir. We conclude that 3C registration of conventional P-wave surveys is worthwhile.

scholarly journals Metode Seismik dalam Pemodelan Fisis Letusan Gunung Lumpur Bledug Kuwu

2019 ◽  
Vol 2 (2) ◽  
pp. 61-66
Author(s):  
Ahmad Fauzi Pohan ◽  
Rusnoviandi Rusnoviandi
Keyword(s):  
Wave Velocity ◽  
Physical Modeling ◽  
Vertical Component ◽  
Dominant Frequency ◽  
P Wave ◽  
Physical Parameters ◽  
S Wave ◽  
Interesting Phenomenon ◽  
Central Java ◽  
P Wave Velocity

Aktivitas gunung lumpur Bledug Kuwu di Jawa  Tengah merupakan fenomena yang menarik dikaji menggunakan pemodelan fisis. Tujuan penelitian ini adalah mengetahui parameter dari medium gunung lumpur Bledug Kuwu. Adapun pemodelan fisis yang dilakukan dengan menggunakan media fisis akuarium berukuran 59 × 59 × 37,3 cm yang diisi material dari lumpur Bledug Kuwu. Sumber letusan dihasilkan dari tekanan kompresor yang dapat diatur kedalaman (10.5, 13, dan 15.5 cm) dan sudut (30o, 45o dan 60o) sumbernya. Sensor yang digunakan geophone komponen vertikal sebanyak 3 buah dengan durasi perekaman selama 5 dan 2,5 detik. Data diambil dengan frekuensi sampel 2 dan 4 kHz untuk masing-masing durasi perekaman. Konfigurasi sumber dan geophone dibuat sesuai dengan pemodelan fisisnya. Pengukuran desnsitas lumpur menunjukkan angka sebesar 1200 kg/m3. Berdasarkan hasil analisis seismogram model fisis diperoleh kecepatan perambatan gelombang-P pada medium lumpur Bledug Kuwu adalah sebesar 48,74 m/s,dan gelombang-S sebesar 28,14 m/s dengan frekuensi dominan antara 20 sampai 25 Hz.   Bledug Kuwu mud volcano activity in Central Java is an interesting phenomenon to be studied using both physical  modeling. The objective of this study was to determine the physical parameters of the medium of Bledug Kuwu. The Physical model was an aquarium with a dimension of 59 × 59 × 37.3 cm filled with Bledug Kuwu’s mud. The eruption source is generated by a compressor pressure that can be controled both the depth(10.5, 13, and 15.5 cm) and the angel of the source (30o, 45o and 60o). The resulting seismic signals were recorded by using 3 vertical component geophones for 10 and 5 seconds durations at a frequency of 2 and 4 kHz respectivel, mud density 1200 kg/m3 . The physical modeling shows that the P-wave velocity of the Bledug Kuwu’s medium is 48.7 m/s, S-wave velocity of Bledug Kuwu’s is 28,14 m/s  with a dominant frequency of 20 to 25 Hz.

P-wave and S-wave azimuthal anisotropy at a naturally fractured gas reservoir, Bluebell‐Altamont Field, Utah

Geophysics ◽  
1999 ◽  
Vol 64 (4) ◽  
pp. 1312-1328 ◽  
Author(s):  
Heloise B. Lynn ◽  
Wallace E. Beckham ◽  
K. Michele Simon ◽  
C. Richard Bates ◽  
M. Layman ◽  
...  
Keyword(s):  
Azimuthal Anisotropy ◽  
P Wave ◽  
Fracture Density ◽  
Wave Reflections ◽  
S Wave ◽  
Gas Reservoir ◽  
Green River ◽  
Wave Data ◽  
Reflection Data ◽  
Naturally Fractured

Reflection P- and S-wave data were used in an investigation to determine the relative merits and strengths of these two data sets to characterize a naturally fractured gas reservoir in the Tertiary Upper Green River formation. The objective is to evaluate the viability of P-wave seismic to detect the presence of gas‐filled fractures, estimate fracture density and orientation, and compare the results with estimates obtained from the S-wave data. The P-wave response to vertical fractures must be evaluated at different source‐receiver azimuths (travelpaths) relative to fracture strike. Two perpendicular lines of multicomponent reflection data were acquired approximately parallel and normal to the dominant strike of Upper Green River fractures as obtained from outcrop, core analysis, and borehole image logs. The P-wave amplitude response is extracted from prestack amplitude variation with offset (AVO) analysis, which is compared to isotropic‐model AVO responses of gas sand versus brine sand in the Upper Green River. A nine‐component vertical seismic profile (VSP) was also obtained for calibration of S-wave reflections with P-wave reflections, and support of reflection S-wave results. The direction of the fast (S1) shear‐wave component from the reflection data and the VSP coincides with the northwest orientation of Upper Green River fractures, and the direction of maximum horizontal in‐situ stress as determined from borehole ellipticity logs. Significant differences were observed in the P-wave AVO gradient measured parallel and perpendicular to the orientation of Upper Green River fractures. Positive AVO gradients were associated with gas‐producing fractured intervals for propagation normal to fractures. AVO gradients measured normal to fractures at known waterwet zones were near zero or negative. A proportional relationship was observed between the azimuthal variation of the P-wave AVO gradient as measured at the tops of fractured intervals, and the fractional difference between the vertical traveltimes of split S-waves (the “S-wave anisotropy”) of the intervals.

scholarly journals Evidence for deep icequakes in an Alpine glacier

2000 ◽  
Vol 31 ◽  
pp. 85-90 ◽  
Author(s):  
N. Deichmann ◽  
J. Ansorge ◽  
F. Scherbaum ◽  
A. Aschwanden ◽  
F. Bernard ◽  
...  
Keyword(s):  
Rayleigh Wave ◽  
Three Dimensional ◽  
Focal Depth ◽  
Vertical Component ◽  
Swiss Alps ◽  
P Wave ◽  
S Wave ◽  
Glacier Surface ◽  
Simultaneous Inversion ◽  
Wave Velocities

AbstractTo obtain more reliable information about the focal-depth distribution of icequakes, in April 1997 we operated an array of seven portable digital seismographs on Unteraargletscher, central Swiss Alps. Over 5000 events were detected by at least two instruments during the 9 day recording period. P-wave velocities (3770 m f) were determined from several calibration shots detonated at the glacier surface as well as in a 49 m deep borehole, whereas S-wave velocities (1860 ms–1) were derived from a simultaneous inversion for Vp/Vs6 applied to 169 icequakes. So far, hypocentral locations have been calculated for over 300 icequakes. Besides confirming the occurrence of shallow events associated with the opening of crevasses, our results show that a small but significant fraction of the hypocenters are located at or near the glacier bed. One event was found at an intermediate depth of about 120 m. Three-dimensional particle-motion diagrams of both explosions and icequakes clearly demonstrate that all vertical component seismograms from shallow sources are dominated by the Rayleigh wave. On the other hand, for events occurring at depths greater than about 40 m, the Rayleigh wave disappears almost entirely. Therefore, a qualitative analysis of the signal character provides direct information on the focal depth of an event and was used as an independent check of the locations obtained from traditional arrival-time inversions. Thus, our results demonstrate that deep icequakes do occur and that simple rheological models, according to which brittle deformation is restricted to the uppermost part of a glacier, may need revision.

Comparing P-P, P-SV, and SV-P mode waves in the Midland Basin, West Texas

2016 ◽  
Vol 4 (2) ◽  
pp. T183-T190 ◽  
Author(s):  
Michael V. De Angelo ◽  
Bob A. Hardage
Keyword(s):  
Vertical Component ◽  
P Wave ◽  
Seismic Survey ◽  
Vertical Force ◽  
S Wave ◽  
Converted Wave ◽  
Midland Basin ◽  
West Texas ◽  
Exploration Risk ◽  
Seismic Acquisition

We acquired 3D multicomponent data in Andrews County, Midland Basin, West Texas with a seismic survey. We extracted direct-SV modes generated by a vertical-force source (an array of three inline vertical vibrators) from the vertical component of multicomponent geophones. This seismic mode, SV-P, was created by reprocessing legacy 2D/3D P-wave seismic data to create converted-wave data and consequently forgoing the need for a multicomponent seismic acquisition program to obtain important S-wave information from the subsurface. We have compared P-P, P-SV, and SV-P traveltime and amplitude characteristics to determine which seismic mode provided better characterization of the targeted reservoirs and reduced exploration risk.

Advances in surface-wave tomography for near-surface applications

2021 ◽  
Vol 40 (8) ◽  
pp. 567-575
Author(s):  
Myrto Papadopoulou ◽  
Farbod Khosro Anjom ◽  
Mohammad Karim Karimpour ◽  
Valentina Laura Socco
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
P Wave ◽  
Seismic Exploration ◽  
S Wave ◽  
Data Set ◽  
Near Surface ◽  
Processing Times ◽  
Spatial Coverage ◽  
Wave Tomography

Surface-wave (SW) tomography is a technique that has been widely used in the field of seismology. It can provide higher resolution relative to the classical multichannel SW processing and inversion schemes that are usually adopted for near-surface applications. Nevertheless, the method is rarely used in this context, mainly due to the long processing times needed to pick the dispersion curves as well as the inability of the two-station processing to discriminate between higher SW modes. To make it efficient and to retrieve pseudo-2D/3D S-wave velocity (VS) and P-wave velocity (VP) models in a fast and convenient way, we develop a fully data-driven two-station dispersion curve estimation, which achieves dense spatial coverage without the involvement of an operator. To handle higher SW modes, we apply a dedicated time-windowing algorithm to isolate and pick the different modes. A multimodal tomographic inversion is applied to estimate a VS model. The VS model is then converted to a VP model with the Poisson's ratio estimated through the wavelength-depth method. We apply the method to a 2D seismic exploration data set acquired at a mining site, where strong lateral heterogeneity is expected, and to a 3D pilot data set, recorded with state-of-the-art acquisition technology. We compare the results with the ones retrieved from classical multichannel analysis.

Realtime detection and location of very local seismicity using SeisComp3

2020 ◽  
Author(s):  
Marcelo Bianchi ◽  
Lucas Schirbel ◽  
Alexandre Ausgusto
Keyword(s):  
Real Time ◽  
Earthquake Swarm ◽  
Regional Scale ◽  
Vertical Component ◽  
Operation Time ◽  
Window Size ◽  
P Wave ◽  
Local Network ◽  
Ocean Bottom ◽  
S Waves

<p>We put SeisComp3 to test by using it to analyze a very dense (9 squared kilometers) local network of 712, four components sensors (stations). Each station had a 3-component accelerometer and a pressure sensor deployed at the ocean bottom, close to the Brazilian platform near an oil exploration field. Noise levels were extreme. During the two months of the operation time, the network recorded an earthquake swarm sequence, and later analysis indicated more than 1000 earthquakes detected in a one-hour interval employing a coherency stacking method. While still not a common practice, real-time earthquake detection and location in this situation would be beneficial since this could support decisions while drilling or oil recovering is in place. Traditional tools as SeisComp3 are routinely used and allows for real-time detection and location along with the rapid revision of regional and teleseismic events, but are not widely adapted to work in a very local environment. Our experience so far showed that SeisComp3 efficiently handled the data volume (4 components at 500 samples per second times 712 stations) with a modern average workstation. Traditional SEG-Y data can be routinely converted and fed in real-time to SeedLink FIFO using ObsPy. Still, data must be correctly rotated since SeisComp3 needs at least a vertical component. Processing workflow included parallel picking using scautopick with STA/LTA, nucleation of origins using scautoloc, and location using Locsat and Hypo71 tools. In this harsh environment, the optimal window size for STA is about the size of the P-wave (0.05-0.1 s) and, LTA is about 30-60 times the S-P times (60-120 s). Using those parameters, SeisComp3 managed to generate from 400-1200 readings per data channel. We fed all picks into scautoloc that handled origin nucleation and location. Despite parameters supplied to scautoloc, the tool has many limits and relations hardcoded that inhibit it from respecting maximum requested residuals. In other words, its nucleation algorithm is adapted to work on the teleseismic and regional scale. Actual results indicate that we were able to nucleate and locate only 10-20% of known origins. Due to the flexibility of the tool, we also developed a pipeline using S-waves only. S-waves had a higher SNR for the events of interest and, due to lower velocities, presents a larger moveout on the small array easing the location. Manually picked and relocated detections returned an RMS lower as 0.04 s. Additional tests performed using the Scanloc module (GEMPA closed source nucleator) showed a higher performance during the nucleation of new origins. In this case, Hypo71 was the used locator. We did not observe any clear difference between LocSat and Hypo71 performance once the earthquake source is nucleated, and a proper velocity model is supplied.</p>

Extraction of P‐ and S‐waves from the vertical component of the particle velocity at the sea floor

Geophysics ◽  
1995 ◽  
Vol 60 (1) ◽  
pp. 231-240 ◽  
Author(s):  
Lasse Amundsen ◽  
Arne Reitan
Keyword(s):  
Particle Velocity ◽  
Synthetic Data ◽  
Vertical Component ◽  
Transversely Isotropic ◽  
Vertical Axis ◽  
Elastic Stiffness ◽  
P Wave ◽  
S Wave ◽  
Sea Floor ◽  
S Waves

At the boundary between two solid media in welded contact, all three components of particle velocity and vertical traction are continuous through the boundary. Across the boundary between a fluid and a solid, however, only the vertical component of particle velocity is continuous while the horizontal components can be discontinuous. Furthermore, the pressure in the fluid is the negative of the vertical component of traction in the solid, while the horizontal components of traction vanish at the interface. Taking advantage of this latter fact, we show that total P‐ and S‐waves can be computed from the vertical component of the particle velocity recorded by single component geophones planted on the sea floor. In the case when the sea floor is transversely isotropic with a vertical axis of symmetry, the computation requires the five independent elastic stiffness components and the density. However, when the sea floor material is fully isotropic, the only material parameter needed is the local shear wave velocity. The analysis of the extraction problem is done in the slowness domain. We show, however, that the S‐wave section can be obtained by a filtering operation in the space‐frequency domain. The P‐wave section is then the difference between the vertical component of the particle velocity and the S‐wave component. A synthetic data example demonstrates the performance of the algorithm.

scholarly journals OBS Data Analysis to Quantify Gas Hydrate and Free Gas in the South Shetland Margin (Antarctica)

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3290 ◽  
Author(s):  
Sha Song ◽  
Umberta Tinivella ◽  
Michela Giustiniani ◽  
Sunny Singhroha ◽  
Stefan Bünz ◽  
...  
Keyword(s):  
Velocity Field ◽  
Wave Velocity ◽  
Gas Hydrate ◽  
P Wave ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
S Wave ◽  
Free Gas ◽  
Hydrate Reservoir ◽  
Gas Hydrate Reservoir

The presence of a gas hydrate reservoir and free gas layer along the South Shetland margin (offshore Antarctic Peninsula) has been well documented in recent years. In order to better characterize gas hydrate reservoirs, with a particular focus on the quantification of gas hydrate and free gas and the petrophysical properties of the subsurface, we performed travel time inversion of ocean-bottom seismometer data in order to obtain detailed P- and S-wave velocity estimates of the sediments. The P-wave velocity field is determined by the inversion of P-wave refractions and reflections, while the S-wave velocity field is obtained from converted-wave reflections received on the horizontal components of ocean-bottom seismometer data. The resulting velocity fields are used to estimate gas hydrate and free gas concentrations using a modified Biot‐Geertsma‐Smit theory. The results show that hydrate concentration ranges from 10% to 15% of total volume and free gas concentration is approximately 0.3% to 0.8% of total volume. The comparison of Poisson’s ratio with previous studies in this area indicates that the gas hydrate reservoir shows no significant regional variations.

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