P‐wave azimuthal variations in attenuation, amplitude, and velocity in 3D field data: Implications for mapping horizontal permeability anisotropy

1998 ◽  
Author(s):  
Heloise Lynn ◽  
Wallace Beckham
Keyword(s):  
Field Data ◽  
P Wave ◽  
Permeability Anisotropy ◽  
Horizontal Permeability

The transversely isotropic poroelastic wave equation including the Biot and the squirt mechanisms: Theory and application

Geophysics ◽  
1997 ◽  
Vol 62 (1) ◽  
pp. 309-318 ◽  
Author(s):  
Jorge O. Parra
Keyword(s):  
Wave Equation ◽  
Fluid Flow ◽  
Analytical Solution ◽  
Seismic Waves ◽  
Transversely Isotropic ◽  
P Wave ◽  
Fluid Properties ◽  
Permeability Anisotropy ◽  
Attenuation And Dispersion ◽  
Maximum Permeability

The transversely isotropic poroelastic wave equation can be formulated to include the Biot and the squirt‐flow mechanisms to yield a new analytical solution in terms of the elements of the squirt‐flow tensor. The new model gives estimates of the vertical and the horizontal permeabilities, as well as other measurable rock and fluid properties. In particular, the model estimates phase velocity and attenuation of waves traveling at different angles of incidence with respect to the principal axis of anisotropy. The attenuation and dispersion of the fast quasi P‐wave and the quasi SV‐wave are related to the vertical and the horizontal permeabilities. Modeling suggests that the attenuation of both the quasi P‐wave and quasi SV‐wave depend on the direction of permeability. For frequencies from 500 to 4500 Hz, the quasi P‐wave attenuation will be of maximum permeability. To test the theory, interwell seismic waveforms, well logs, and hydraulic conductivity measurements (recorded in the fluvial Gypsy sandstone reservoir, Oklahoma) provide the material and fluid property parameters. For example, the analysis of petrophysical data suggests that the vertical permeability (1 md) is affected by the presence of mudstone and siltstone bodies, which are barriers to vertical fluid movement, and the horizontal permeability (1640 md) is controlled by cross‐bedded and planar‐laminated sandstones. The theoretical dispersion curves based on measurable rock and fluid properties, and the phase velocity curve obtained from seismic signatures, give the ingredients to evaluate the model. Theoretical predictions show the influence of the permeability anisotropy on the dispersion of seismic waves. These dispersion values derived from interwell seismic signatures are consistent with the theoretical model and with the direction of propagation of the seismic waves that travel parallel to the maximum permeability. This analysis with the new analytical solution is the first step toward a quantitative evaluation of the preferential directions of fluid flow in reservoir formation containing hydrocarbons. The results of the present work may lead to the development of algorithms to extract the permeability anisotropy from attenuation and dispersion data (derived from sonic logs and crosswell seismics) to map the fluid flow distribution in a reservoir.

scholarly journals Finite-difference modelling to evaluate seismic P-wave and shear-wave field data

Solid Earth ◽  
2015 ◽  
Vol 6 (1) ◽  
pp. 33-47 ◽  
Author(s):  
T. Burschil ◽  
T. Beilecke ◽  
C. M. Krawczyk
Keyword(s):  
Wave Field ◽  
Shear Wave ◽  
Field Data ◽  
P Wave ◽  
Sh Wave ◽  
Surface Shear ◽  
Near Surface ◽  
Reflection Seismic ◽  
Surface Shear Wave ◽  
Seismic Measurements

Abstract. High-resolution reflection seismic methods are an established non-destructive tool for engineering tasks. In the near surface, shear-wave reflection seismic measurements usually offer a higher spatial resolution in the same effective signal frequency spectrum than P-wave data, but data quality varies more strongly. To discuss the causes of these differences, we investigated a P-wave and a SH-wave seismic reflection profile measured at the same location on the island of Föhr, Germany and applied seismic reflection processing to the field data as well as finite-difference modelling of the seismic wave field. The simulations calculated were adapted to the acquisition field geometry, comprising 2 m receiver distance (1 m for SH wave) and 4 m shot distance along the 1.5 km long P-wave and 800 m long SH-wave profiles. A Ricker wavelet and the use of absorbing frames were first-order model parameters. The petrophysical parameters to populate the structural models down to 400 m depth were taken from borehole data, VSP (vertical seismic profile) measurements and cross-plot relations. The simulation of the P-wave wave-field was based on interpretation of the P-wave depth section that included a priori information from boreholes and airborne electromagnetics. Velocities for 14 layers in the model were derived from the analysis of five nearby VSPs (vP =1600–2300 m s-1). Synthetic shot data were compared with the field data and seismic sections were created. Major features like direct wave and reflections are imaged. We reproduce the mayor reflectors in the depth section of the field data, e.g. a prominent till layer and several deep reflectors. The SH-wave model was adapted accordingly but only led to minor correlation with the field data and produced a higher signal-to-noise ratio. Therefore, we suggest to consider for future simulations additional features like intrinsic damping, thin layering, or a near-surface weathering layer. These may lead to a better understanding of key parameters determining the data quality of near-surface shear-wave seismic measurements.

scholarly journals Investigation of ULF magnetic pulsations, air conductivity changes, and infra red signatures associated with the 30 October Alum Rock M5.4 earthquake

2009 ◽  
Vol 9 (2) ◽  
pp. 585-603 ◽  
Author(s):  
T. Bleier ◽  
C. Dunson ◽  
M. Maniscalco ◽  
N. Bryant ◽  
R. Bambery ◽  
...  
Keyword(s):  
Field Data ◽  
Low Frequency ◽  
Field Tests ◽  
P Wave ◽  
Electromagnetic Signal ◽  
San Jose ◽  
Data Set ◽  
Bay Area ◽  
Conductivity Sensor ◽  
Magnetic Pulsations

Abstract. Several electromagnetic signal types were observed prior to and immediately after 30 October 2007 (Local Time) M5.4 earthquake at Alum Rock, Ca with an epicenter ~15 km NE of San Jose Ca. The area where this event occurred had been monitored since November 2005 by a QuakeFinder magnetometer site, unit 609, 2 km from the epicenter. This instrument is one of 53 stations of the QuakeFinder (QF) California Magnetometer Network-CalMagNet. This station included an ultra low frequency (ULF) 3-axis induction magnetometer, a simple air conductivity sensor to measure relative airborne ion concentrations, and a geophone to identify the arrival of the P-wave from an earthquake. Similar in frequency content to the increased ULF activity reported two weeks prior to the Loma Prieta M7.0 quake in 1989 (Fraser-Smith, 1990, 1991), the QF station detected activity in the 0.01–12 Hz bands, but it consisted of an increasing number of short duration (1 to 30 s duration) pulsations. The pulsations peaked around 13 days prior to the event. The amplitudes of the pulses were strong, (3–20 nT), compared to the average ambient noise at the site, (10–250 pT), which included a component arising from the Bay Area Rapid Transit (BART) operations. The QF station also detected different pulse shapes, e.g. negative or positive only polarity, with some pulses including a combination of positive and negative. Typical pulse counts over the previous year ranged from 0–15 per day, while the count rose to 176 (east-west channel) on 17 October, 13 days prior to the quake. The air conductivity sensor saturated for over 14 h during the night and morning prior to the quake, which occurred at 20:29 LT. Anomalous IR signatures were also observed in the general area, within 50 km of the epicenter, during the 2 weeks prior to the quake. These three simultaneous EM phenomena were compared with data collected over a 1–2-year period at the site. The data was also compared against accounts of air ionization reported to be associated with radon emission from the ground (Ouzounov, 2007), and a series of laboratory rock stressing experiments (Freund, 2006, 2007a, b, c) to determine if field data was consistent either of these accounts. We could not find a data set with pre-earthquake radon measurements taken near the Alum Rock epicenter to compare against our field data. However, based on the Alum Rock data set example and another data set at Parkfield, the field tests are at least consistent with the lab experiments showing currents, magnetic field disturbances, air conductivity changes, and IR signatures. This is encouraging, but more instrumented earthquake examples are needed to prove a repeating pattern for these types of pre-earthquake EM signatures. For more information on QuakeFinder please view http://www.quakefinder.com.

Integration of surface-based tomographic models for zonation and multimodel guided extrapolation of sparsely known petrophysical parameters

Geophysics ◽  
2013 ◽  
Vol 78 (4) ◽  
pp. EN43-EN53 ◽  
Author(s):  
Barbara Hachmöller ◽  
Hendrik Paasche
Keyword(s):  
Cluster Analysis ◽  
Field Data ◽  
Spectral Cluster ◽  
P Wave ◽  
Fuzzy Membership ◽  
Geophysical Model ◽  
Natural Gamma ◽  
Refraction Seismic ◽  
Spatially Varying ◽  
Membership Information

We integrate the information of multiple tomographic models acquired from the earth’s surface by modifying a statistical approach recently developed for the integration of cross-borehole tomographic models. In doing so, we introduce spectral cluster analysis as the new core of the model integration procedure to capture the spatial heterogeneity present in all considered tomographic models and describe this heterogeneity in a fuzzy sense. Because spectral cluster algorithms analyze model structure locally, they are considered relatively robust with regard to systematically and spatially varying imaging capabilities typical for geophysical tomographic surveys conducted on the earth’s surface. Using a synthetic aquifer example, a fuzzy spectral cluster algorithm can be used to integrate the information provided by 2D tomographic refraction seismic and DC resistivity surveys. The integrated information in the fuzzy membership domain is then used to derive an integrated zonal geophysical model outlining the major structural units present in both input models. We also explain how the fuzzy membership information can be used to identify optimal locations for sparse logging of additional target parameters, i.e., porosity information in our synthetic example. We demonstrate how this sparse porosity information can be extrapolated based on all tomographic input models. The resultant 2D porosity model matches the original porosity distribution reasonably well within the spatial resolution limits of the underlying tomographic models. Consecutively, we apply this approach to a field data base acquired over a former river channel. Sparse information about natural gamma radiation is available and extrapolated on the basis of the fuzzy membership information obtained by spectral cluster analysis of 2D P-wave velocity and electrical resistivity models. This field data shows that the presented parameter extrapolation procedure is robust, even if the locations of target parameter acquisition have not been optimized with regard to the fuzzy membership information.

Feasibility of estimating vertical transverse isotropy from microseismic data recorded by surface monitoring arrays

Geophysics ◽  
2011 ◽  
Vol 76 (6) ◽  
pp. WC117-WC126 ◽  
Author(s):  
Davide Gei ◽  
Leo Eisner ◽  
Peter Suhadolc
Keyword(s):  
Vertical Velocity ◽  
Field Data ◽  
P Wave ◽  
Time Inversion ◽  
Source Depth ◽  
Effective Anisotropy ◽  
Arrival Times ◽  
Microseismic Data ◽  
Surface Monitoring ◽  
Wave Arrival

Microseismic data recorded by surface monitoring arrays can be used to estimate the effective anisotropy of the overburden and reservoir. In this study we used the inversion of picked P-wave arrival times to estimate the Thomsen parameter [Formula: see text] and the anellipticity coefficient [Formula: see text]. This inversion employs an analytic equation of P-wave traveltimes as a function of offset in homogeneous, transversely isotropic media with a vertical axis of symmetry. We considered a star-like distribution of receivers and, for this geometry, we analyzed the sensitivity of the inversion method to picking noise and to uncertainties in the P-wave vertical velocity and source depth. Long offsets, as well as a high number of receivers per line, improve the estimation of [Formula: see text] and [Formula: see text] from noisy arrival times. However, if we do not use the correct value of the P-wave vertical velocity or source depth, the long-offset may increase the inaccuracy in the estimation of the anisotropic parameters. Such inaccuracy cannot be detected from time residuals. We also applied this inversion to field data acquired during the hydraulic fracturing of a gas shale reservoir and compared the results with the anisotropic parameters estimated from synthetic arrival times computed for an isotropic layered medium. The effective anisotropy from the inversion of the field data cannot be explained by layering only and is partially due to the intrinsic anisotropy of the reservoir and/or overburden. This study emphasizes the importance of using accurate values of the vertical velocity and source depth in the P-wave arrival time inversion for estimating anisotropic parameters from passive seismic data.

Experimental and texture-derived P-wave anisotropy of principal rocks from the TRANSALP traverse: An aid for the interpretation of seismic field data

2006 ◽  
Vol 414 (1-4) ◽  
pp. 97-116 ◽  
Author(s):  
Klaus Ullemeyer ◽  
Siegfried Siegesmund ◽  
Patrick N.J. Rasolofosaon ◽  
Jan H. Behrmann
Keyword(s):  
Field Data ◽  
P Wave

scholarly journals Seismic interferometry using multidimensional deconvolution and crosscorrelation for crosswell seismic reflection data without borehole sources

Geophysics ◽  
2011 ◽  
Vol 76 (1) ◽  
pp. SA19-SA34 ◽  
Author(s):  
Shohei Minato ◽  
Toshifumi Matsuoka ◽  
Takeshi Tsuji ◽  
Deyan Draganov ◽  
Jürg Hunziker ◽  
...  
Keyword(s):  
Seismic Reflection ◽  
Field Data ◽  
Time Lapse ◽  
P Wave ◽  
Source Distribution ◽  
Seismic Interferometry ◽  
Imaging Method ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Receiver Arrays

Crosswell reflection method is a high-resolution seismic imaging method that uses recordings between boreholes. The need for downhole sources is a restrictive factor in its application, for example, to time-lapse surveys. An alternative is to use surface sources in combination with seismic interferometry. Seismic interferometry (SI) could retrieve the reflection response at one of the boreholes as if from a source inside the other borehole. We investigate the applicability of SI for the retrieval of the reflection response between two boreholes using numerically modeled field data. We compare two SI approaches — crosscorrelation (CC) and multidimensional deconvolution (MDD). SI by MDD is less sensitive to underillumination from the source distribution, but requires inversion of the recordings at one of the receiver arrays from all the available sources. We find that the inversion problem is ill-posed, and propose to stabilize it using singular-value decomposition. The results show that the reflections from deep boundaries are retrieved very well using both the CC and MDD methods. Furthermore, the MDD results exhibit more realistic amplitudes than those from the CC method for downgoing reflections from shallow boundaries. We find that the results retrieved from the application of both methods to field data agree well with crosswell seismic-reflection data using borehole sources and with the logged P-wave velocity.

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