3D description and inversion of reflection moveout of PS‐waves in anisotropic media

Common‐midpoint moveout of converted waves is generally asymmetric with respect to zero offset and cannot be described by the traveltime series t²(x²) conventionally used for pure modes. Here, we present concise parametric expressions for both common‐midpoint (CMP) and common‐conversion‐point (CCP) gathers of PS‐waves for arbitrary anisotropic, horizontally layered media above a plane dipping reflector. This analytic representation can be used to model 3D (multi‐azimuth) CMP gathers without time‐consuming two‐point ray tracing and to compute attributes of PS moveout such as the slope of the traveltime surface at zero offset and the coordinates of the moveout minimum. In addition to providing an efficient tool for forward modelling, our formalism helps to carry out joint inversion of P and PS data for transverse isotropy with a vertical symmetry axis (VTI media). If the medium above the reflector is laterally homogeneous, P‐wave reflection moveout cannot constrain the depth scale of the model needed for depth migration. Extending our previous results for a single VTI layer, we show that the interval vertical velocities of the P‐ and S‐waves (V_P0 and V_S0) and the Thomsen parameters ε and δ can be found from surface data alone by combining P‐wave moveout with the traveltimes of the converted PS(PSV)‐wave. If the data are acquired only on the dip line (i.e. in 2D), stable parameter estimation requires including the moveout of P‐ and PS‐waves from both a horizontal and a dipping interface. At the first stage of the velocity‐analysis procedure, we build an initial anisotropic model by applying a layer‐stripping algorithm to CMP moveout of P‐ and PS‐waves. To overcome the distorting influence of conversion‐point dispersal on CMP gathers, the interval VTI parameters are refined by collecting the PS data into CCP gathers and repeating the inversion. For 3D surveys with a sufficiently wide range of source–receiver azimuths, it is possible to estimate all four relevant parameters (V_P0, V_S0, ε and δ) using reflections from a single mildly dipping interface. In this case, the P‐wave NMO ellipse determined by 3D (azimuthal) velocity analysis is combined with azimuthally dependent traveltimes of the PS‐wave. On the whole, the joint inversion of P and PS data yields a VTI model suitable for depth migration of P‐waves, as well as processing (e.g. transformation to zero offset) of converted waves.     

Converted-wave imaging in anisotropic media: theory and case studies

Common‐conversion‐point binning associated with converted‐wave (C‐wave) processing complicates the task of parameter estimation, especially in anisotropic media. To overcome this problem, we derive new expressions for converted‐wave prestack time migration (PSTM) in anisotropic media and illustrate their applications using both 2D and 3D data examples. The converted‐wave kinematic response in inhomogeneous media with vertical transverse isotropy is separated into two parts: the response in horizontally layered vertical transverse isotrophy media and the response from a point‐scatterer. The former controls the stacking process and the latter controls the process of PSTM. The C‐wave traveltime in horizontally layered vertical transverse isotrophy media is determined by four parameters: the C‐wave stacking velocity V_C2, the vertical and effective velocity ratios γ₀ and γ_eff, and the C‐wave anisotropic parameter χ_eff. These four parameters are referred to as the C‐wave stacking velocity model. In contrast, the C‐wave diffraction time from a point‐scatterer is determined by five parameters: γ₀, V_P2, V_S2, η_eff and ζ_eff, where η_eff and ζ_eff are, respectively, the P‐ and S‐wave anisotropic parameters, and V_P2 and V_S2 are the corresponding stacking velocities. V_P2, V_S2, η_eff and ζ_eff are referred to as the C‐wave PSTM velocity model. There is a one‐to‐one analytical link between the stacking velocity model and the PSTM velocity model. There is also a simple analytical link between the C‐wave stacking velocities V_C2 and the migration velocity V_Cmig, which is in turn linked to V_P2 and V_S2. Based on the above, we have developed an interactive processing scheme to build the stacking and PSTM velocity models and to perform 2D and 3D C‐wave anisotropic PSTM. Real data applications show that the PSTM scheme substantially improves the quality of C‐wave imaging compared with the dip‐moveout scheme, and these improvements have been confirmed by drilling.     

Observation of shear‐wave splitting in the multicomponent node data from Atlantis field,Gulf of Mexico

In 2005, a multicomponent ocean bottom node data set was collected by BP and BHP Billiton in the Atlantis field in the Gulf of Mexico. Our results are based on data from a few sparse nodes with millions of shots that were analysed as common receiver azimuthal gathers. A first‐order look at P‐wave arrivals on a common receiver gather at a constant offset reveals variation of P‐wave arrival time as a function of azimuth indicating the presence of azimuthal anisotropy at the top few layers. This prompted us to investigate shear arrivals on the horizontal component data. After preliminary processing, including a static correction, the data were optimally rotated to radial (R) and transverse (T) components. The R component shows azimuthal variation of traveltime indicating variation of velocity with azimuth; the corresponding T component shows azimuthal variation of amplitude and phase (polarity reversal). The observed shear‐wave (S‐wave) splitting, previously observed azimuthal P‐wave velocity variation and azimuthal P‐wave amplitude variation, all indicate the occurrence of anisotropy in the shallow (just below the seafloor) subsea sediment in the area. From the radial component azimuthal gather, we analysed the PP‐ and PS‐wave amplitude variation for the first few layers and determined corresponding anisotropy parameter and V_P/V_S values. Since fracture at this depth is not likely to occur, we attribute the observed azimuthal anisotropy to the presence of microcracks and grain boundary orientation due to stress. The evidence of anisotropy is ubiquitous in this data set and thus it argues strongly in favour of considering anisotropy in depth imaging for obtaining realistic subsurface images, at the least.     

Receiver function method in reflection seismology

The receiver function method was originally developed to analyse earthquake data recorded by multicomponent (3C) sensors and consists in deconvolving the horizontal component by the vertical component. The deconvolution process removes travel path effects from the source to the base of the target as well as the earthquake source signature. In addition, it provides the possibility of separating the emergent P and PS waves based on adaptive subtraction between recorded components if plane waves of constant ray parameters are considered. The resulting receiver function signal is the local PS wave's impulse response generated at impedance contrasts below the 3C receiver.We propose to adapt this technique to the wide‐angle multi‐component reflection acquisition geometry. We focus on the simplest case of land data reflection acquisition. Our adapted version of the receiver function approach consists in a multi‐step procedure that first removes the P wavefield recorded on the horizontal component and next removes the source signature. The separation step is performed in the τ?p domain while the source designature can be achieved in either the τ?p or the t?x domain. Our technique does not require any a priori knowledge of the subsurface. The resulting receiver function is a pure PS‐wave reflectivity response, which can be used for amplitude versus slowness or offset analysis. Stack of the receiver function leads to a high‐quality S wave image.     

Inversion of multicomponent seismic time shifts for reservoir pressure and length: a feasibility study

Pressure drops associated with reservoir production generate excess stress and strain that cause travel‐time shifts of reflected waves. Here, we invert time shifts of P‐, S‐, and PS‐waves measured between baseline and monitor surveys for pressure reduction and reservoir length. The inversion results can be used to estimate compaction‐induced stress and strain changes around the reservoir. We implement a hybrid inversion algorithm that incorporates elements of gradient, global/genetic, and nearest neighbour methods and permits exploration of the parameter space while simultaneously following local misfit gradients. Our synthetic examples indicate that optimal estimates of reservoir pressure from P‐wave data can be obtained using the reflections from the reservoir top. For S‐waves, time shifts from the top of the reservoir can be accurately inverted for pressure if the noise level is low. However, if noise contamination is significant, it is preferable to use S‐wave data (or combined shifts of all three modes) from reflectors beneath the reservoir. Joint wave type inversions demonstrate improvements over any single pure mode. Reservoir length can be estimated using the time shifts of any mode from the reservoir top or deeper reflectors. We also evaluate the differences between the actual strain field and those corresponding to the best‐case inversion results obtained using P‐ and S‐wave data. Another series of tests addresses the inversion of the time shifts for the pressure drops in two‐compartment reservoirs, as well as for the associated strain field. Numerical testing shows that a potentially serious source of error in the inversion is a distortion in the strain‐sensitivity coefficients, which govern the magnitude of stiffness changes. This feasibility study suggests which wave types and reflector locations may provide the most accurate estimates of reservoir parameters from compaction‐induced time shifts.     

Separation of P- and S-wavefields from wide-angle multicomponent OBC data for a basalt model

Wide-angle multicomponent ocean-bottom cable (OBC) data should further enhance sub-basalt imaging by using both compressional and converted shear wavefields. The first step in analysing multicomponent OBC data is to decompose the recorded wavefields into pure P- and pure S-wavefields, and extract the upgoing P- and S-waves. This paper presents a new scheme to separate P- and S-wavefields from wide-angle multicomponent OBC data in the τ–p domain. By considering plane-wave components with a known horizontal slowness, the P- and S-wavefields are separated into the directions of observed P- and S-wave oscillations using the horizontal and vertical components of the data. The upgoing P- and S-waves are then extracted from the separated P- and S-wavefields. The parameters used in the separation are the seismic wave velocities and the density at the receiver location, which can be estimated from the first reflection phase observed on the horizontal and vertical components. Numerical tests on synthetic data for a plane-layered model show good performance and demonstrate the accuracy of the scheme. Separation of wavefields from a basalt model is performed using synthetic wide-angle multicomponent OBC data. The results show that both near-offset and wide-angle reflections and conversions from within and below basalt layers are enhanced and clearly identified on the separated wavefields.     

Lithology and hydrocarbon mapping from multicomponent seismic data

Elastic rock properties can be estimated from prestack seismic data using amplitude variation with offset analysis. P‐wave, S‐wave and density ‘reflectivities’, or contrasts, can be inverted from angle‐band stacks. The ‘reflectivities’ are then inverted to absolute acoustic impedance, shear impedance and density. These rock properties can be used to map reservoir parameters through all stages of field development and production. When P‐wave contrast is small, or gas clouds obscure reservoir zones, multicomponent ocean‐bottom recording of converted‐waves (P to S or Ps) data provides reliable mapping of reservoir boundaries. Angle‐band stacks of multicomponent P‐wave (Pz) and Ps data can also be inverted jointly. In this paper Aki‐Richards equations are used without simplifications to invert angle‐band stacks to ‘reflectivities’. This enables the use of reflection seismic data beyond 30° of incident angles compared to the conventional amplitude variation with offset analysis. It, in turn, provides better shear impedance and density estimates. An important input to amplitude variation with offset analysis is the V_s/V_p ratio. Conventional methods use a constant or a time‐varying V_s/V_p model. Here, a time‐ and space‐varying model is used during the computation of the ‘reflectivities’. The V_s/V_p model is generated using well log data and picked horizons. For multicomponent data applications, the latter model can also be generated from processing V_s/V_p models and available well data. Reservoir rock properties such as λρ, μρ, Poisson's ratio and bulk modulus can be computed from acoustic impedance, shear impedance and density for pore fill and lithology identification. λ and μ are the Lamé constants and ρ is density. These estimations can also be used for a more efficient log property mapping. V_p/V_s ratio or Poisson's ratio, λρ and weighted stacks, such as the one computed from λρ and λ/μ, are good gas/oil and oil/water contact indicators, i.e., pore fill indicators, while μρ mainly indicates lithology. μρ is also affected by pressure changes. Results from a multicomponent data set are used to illustrate mapping of gas, oil and water saturation and lithology in a Tertiary sand/shale setting. Whilst initial log crossplot analysis suggested that pore fill discrimination may be possible, the inversion was not successful in revealing fluid effects. However, rock properties computed from acoustic impedance, shear impedance and density estimates provided good lithology indicators; pore fill identification was less successful. Neural network analysis using computed rock properties provided good indication of sand/shale distribution away from the existing wells and complemented the results depicted from individual rock property inversions.     

Coherence methods in mapping AVO anomalies and predicting P-wave and S-wave impedances

Filters for migrated offset substacks are designed by partial coherence analysis to predict ‘normal’ amplitude variation with offset (AVO) in an anomaly free area. The same prediction filters generate localized prediction errors when applied in an AVO‐anomalous interval. These prediction errors are quantitatively related to the AVO gradient anomalies in a background that is related to the minimum AVO anomaly detectable from the data. The prediction‐error section is thus used to define a reliability threshold for the identification of AVO anomalies. Coherence analysis also enables quality control of AVO analysis and inversion. For example, predictions that are non‐localized and/or do not show structural conformity may indicate spatial variations in amplitude–offset scaling, seismic wavelet or signal‐to‐noise (S/N) ratio content. Scaling and waveform variations can be identified from inspection of the prediction filters and their frequency responses. S/N ratios can be estimated via multiple coherence analysis. AVO inversion of seismic data is unstable if not constrained. However, the use of a constraint on the estimated parameters has the undesirable effect of introducing biases into the inverted results: an additional bias‐correction step is then needed to retrieve unbiased results. An alternative form of AVO inversion that avoids additional corrections is proposed. This inversion is also fast as it inverts only AVO anomalies. A spectral coherence matching technique is employed to transform a zero‐offset extrapolation or near‐offset substack into P‐wave impedance. The same technique is applied to the prediction‐error section obtained by means of partial coherence, in order to estimate S‐wave velocity to P‐wave velocity (V_S/V_P) ratios. Both techniques assume that accurate well ties, reliable density measurements and P‐wave and S‐wave velocity logs are available, and that impedance contrasts are not too strong. A full Zoeppritz inversion is required when impedance contrasts that are too high are encountered. An added assumption is made for the inversion to the V_S/V_P ratio, i.e. the Gassmann fluid‐substitution theory is valid within the reservoir area. One synthetic example and one real North Sea in‐line survey illustrate the application of the two coherence methods.     

P- and S-wave velocities of consolidated sediments from a seafloor seismic survey in the North Celtic Sea Basin, offshore Ireland

A geophysical survey was conducted over a hydrocarbon prospect in the North Celtic Sea Basin using a small array of ocean‐bottom seismographs (OBSs). The purpose of this study was to determine the ratio of compressional (P)‐ to shear (S)‐wave velocity of consolidated sedimentary rocks in order to constrain possible subsurface variations in pore‐fluid content. The ratio of V_P and V_S is known to be particularly sensitive to lithology, porosity and pore‐fluid content, making it a useful parameter for evaluating hydrocarbon prospects. OBSs offer a relatively cheap and time‐effective means of acquiring multi‐component data compared with ocean‐bottom cables. In this contribution, we demonstrate the ability of an OBS survey comprising three pairs of two OBSs spaced at 1.6 km to recover lateral variations in the V_P/V_S ratio. A key requirement of this type of study is that S waves will be generated by mode conversions in the subsurface, since they cannot be generated in nor travel through fluids. In this survey, the contrast in physical properties of the hard seabed of the North Celtic Sea Basin provided a means of generating converted S waves. Two‐dimensional ray‐tracing and forward modelling was used to create both V_P and V_S models along a profile crossing the Blackrock prospect in the North Celtic Sea Basin. These models comprise four layers and extend to a maximum depth of 1.1 km. The observed northward decrease in the V_P/V_S ratio at depths of 500–1000 m below the seafloor in the study area is interpreted to represent lateral variation in the amount of gas present in the pore space of Upper Cretaceous chalks and shales overlying the prospective reservoir.     

Non-hyperbolic moveout inversion of wide-azimuth P-wave data for orthorhombic media

The azimuthally varying non‐hyperbolic moveout of P‐waves in orthorhombic media can provide valuable information for characterization of fractured reservoirs and seismic processing. Here, we present a technique to invert long‐spread, wide‐azimuth P‐wave data for the orientation of the vertical symmetry planes and five key moveout parameters: the symmetry‐plane NMO velocities, V⁽¹⁾_nmo and V⁽²⁾_nmo , and the anellipticity parameters, η⁽¹⁾, η⁽²⁾ and η⁽³⁾ . The inversion algorithm is based on a coherence operator that computes the semblance for the full range of offsets and azimuths using a generalized version of the Alkhalifah–Tsvankin non‐hyperbolic moveout equation. The moveout equation provides a close approximation to the reflection traveltimes in layered anisotropic media with a uniform orientation of the vertical symmetry planes. Numerical tests on noise‐contaminated data for a single orthorhombic layer show that the best‐constrained parameters are the azimuth ? of one of the symmetry planes and the velocities V⁽¹⁾_nmo and V⁽²⁾_nmo , while the resolution in η⁽¹⁾ and η⁽²⁾ is somewhat compromised by the trade‐off between the quadratic and quartic moveout terms. The largest uncertainty is observed in the parameter η⁽³⁾ , which influences only long‐spread moveout in off‐symmetry directions. For stratified orthorhombic models with depth‐dependent symmetry‐plane azimuths, the moveout equation has to be modified by allowing the orientation of the effective NMO ellipse to differ from the principal azimuthal direction of the effective quartic moveout term. The algorithm was successfully tested on wide‐azimuth P‐wave reflections recorded at the Weyburn Field in Canada. Taking azimuthal anisotropy into account increased the semblance values for most long‐offset reflection events in the overburden, which indicates that fracturing is not limited to the reservoir level. The inverted symmetry‐plane directions are close to the azimuths of the off‐trend fracture sets determined from borehole data and shear‐wave splitting analysis. The effective moveout parameters estimated by our algorithm provide input for P‐wave time imaging and geometrical‐spreading correction in layered orthorhombic media.     

Joint cross-well and single-well seismic studies of CO2 injection in an oil reservoir

A series of time‐lapse seismic cross‐well and single‐well experiments were conducted in a diatomite reservoir to monitor the injection of CO₂ into a hydrofracture zone, based on P‐ and S‐wave data. A high‐frequency piezo‐electric P‐wave source and an orbital‐vibrator S‐wave source were used to generate waves that were recorded by hydrophones as well as 3‐component geophones. During the first phase the set of seismic experiments was conducted after the injection of water into the hydrofractured zone. The set of seismic experiments was repeated after a time period of seven months during which CO₂ was injected into the hydrofractured zone. The questions to be answered ranged from the detectability of the geological structure in the diatomic reservoir to the detectability of CO₂ within the hydrofracture. Furthermore, it was intended to determine which experiment (cross‐well or single‐well) is best suited to resolve these features. During the pre‐injection experiment, the P‐wave velocities exhibited relatively low values between 1700 and 1900 m/s, which decreased to 1600–1800 m/s during the post‐injection phase (?5%). The analysis of the pre‐injection S‐wave data revealed slow S‐wave velocities between 600 and 800 m/s, while the post‐injection data revealed velocities between 500 and 700 m/s (?6%). These velocity estimates produced high Poisson's ratios between 0.36 and 0.46 for this highly porous (～50%) material. Differencing post‐ and pre‐injection data revealed an increase in Poisson's ratio of up to 5%. Both velocity and Poisson's ratio estimates indicate the dissolution of CO₂ in the liquid phase of the reservoir accompanied by an increase in pore pressure. The single‐well data supported the findings of the cross‐well experiments. P‐ and S‐wave velocities as well as Poisson's ratios were comparable to the estimates of the cross‐well data. The cross‐well experiment did not detect the presence of the hydrofracture but appeared to be sensitive to overall changes in the reservoir and possibly the presence of a fault. In contrast, the single‐well reflection data revealed an arrival that could indicate the presence of the hydrofracture between the source and receiver wells, while it did not detect the presence of the fault, possibly due to out‐of‐plane reflections.     

Dispersion and radial depth of investigation of borehole modes

Sonic techniques in geophysical prospecting involve elastic wave velocity measurements that are performed by placing acoustic transmitters and receivers in a fluid‐filled borehole. The signals recorded at the receivers are processed to obtain compressional‐ and shear‐wave velocities in the surrounding formation. These velocities are generally used in seismic surveys for the time‐to‐depth conversion and other formation parameters, such as porosity and lithology. Depending upon the type of transmitter used (e.g. monopole or dipole) and as a result of eccentering, it is possible to excite axisymmetric (n= 0) , flexural (n= 1) and quadrupole (n= 2) families of modes propagating along the borehole. We present a study of various propagating and leaky modes that includes their dispersion and attenuation characteristics caused by radiation into the surrounding formation. A knowledge of propagation characteristics of borehole modes helps in a proper selection of transmitter bandwidth for suppressing unwanted modes that create problems in the inversion for the compressional‐ and shear‐wave velocities from the dispersive arrivals. It also helps in the design of a transmitter for a preferential excitation of a given mode in order to reduce interference with drill‐collar or drilling noise for sonic measurements‐while‐drilling. Computational results for the axisymmetric family of modes in a fast formation with a shear‐wave velocity of 2032 m/s show the existence of Stoneley, pseudo‐Rayleigh and anharmonic cut‐off modes. In a slow formation with a shear‐wave velocity of 508 m/s, we find the existence of the Stoneley mode and the first leaky compressional mode which cuts in at approximately the same normalized frequency ωa/V_S= 2.5 (a is the borehole radius) as that of the fast formation. The corresponding modes among the flexural family include the lowest‐order flexural and anharmonic cut‐off modes. For both the fast and slow formations, the first anharmonic mode cuts in at a normalized frequency ωa/V_S= 1.5 approximately. Cut‐off frequencies of anharmonic modes are inversely proportional to the borehole radius in the absence of any tool. The borehole quadrupole mode can also be used for estimating formation shear slownesses. The radial depth of investigation with a quadrupole mode is marginally less than that of a flexural mode because of its higher frequency of excitation.     

Three‐dimensional VS profiling using microtremors in Kushiro,Japan

A practical method is presented for determining three‐dimensional S‐wave velocity (V_S) profile from microtremor measurements. Frequency–wave number (f–k) spectral analyses of microtremor array records are combined, for this purpose, with microtremor horizontal‐to‐vertical (H/V) spectral ratio techniques. To demonstrate the effectiveness of the proposed method, microtremor measurements using arrays of sensors were conducted at six sites in the city of Kushiro, Japan. The spectral analyses of the array records yield dispersion characteristics of Rayleigh waves and H/V spectra of surface waves, and joint inversion of these data results in V_S profiles down to bedrock at the sites. Conventional microtremor measurements were performed at 230 stations within Kushiro city, resulting in the H/V spectra within the city. Three‐dimensional V_S structure is then estimated from inversion of the H/V spectra with the V_S values determined from the microtremor array data. This reveals three‐dimensional V_S profile of Kushiro city, together with an unknown hidden valley that crosses the central part of the city. The estimated V_S profile is consistent with available velocity logs and results of subsequent borings, indicating the effectiveness of the proposed method. Copyright © 2008 John Wiley & Sons, Ltd.     

Ultrasonic velocities of North Sea chalk samples: influence of porosity, fluid content and texture

We have studied 56 unfractured chalk samples of the Upper Cretaceous Tor Formation of the Dan, South Arne and Gorm Fields, Danish North Sea. The samples have porosities of between 14% and 45% and calcite content of over 95%. The ultrasonic compressional‐ and shear‐wave velocities (V_P and V_S) for dry and water‐saturated samples were measured at up to 75 bar confining hydrostatic pressure corresponding to effective stress in the reservoir. The porosity is the main control of the ultrasonic velocities and therefore of the elastic moduli. The elastic moduli are slightly higher for samples from the South Arne Field than from the Dan Field for identical porosities. This difference may be due to textural differences between the chalk at the two locations because we observe that large grains (i.e. filled microfossils and fossil fragments) that occur more frequently in samples from the Dan Field have a porosity‐reducing effect and that samples rich in large grains have a relatively low porosity for a given P‐wave modulus. The clay content in the samples is low and is mainly represented by either kaolinite or smectite; samples with smectite have a lower P‐wave modulus than samples with kaolinite at equal porosity. We find that ultrasonic V_P and V_S of dry chalk samples can be satisfactorily estimated with Gassmann's relationships from data for water‐saturated samples. A pronounced difference between the V_P/V_S ratios for dry and water‐saturated chalk samples indicates promising results for seismic amplitude‐versus‐offset analyses.     

Elastic full waveform inversion of multi‐component OBC seismic data

Elastic full waveform inversion of seismic reflection data represents a data‐driven form of analysis leading to quantification of sub‐surface parameters in depth. In previous studies attention has been given to P‐wave data recorded in the marine environment, using either acoustic or elastic inversion schemes. In this paper we exploit both P‐waves and mode‐converted S‐waves in the marine environment in the inversion for both P‐ and S‐wave velocities by using wide‐angle, multi‐component, ocean‐bottom cable seismic data. An elastic waveform inversion scheme operating in the time domain was used, allowing accurate modelling of the full wavefield, including the elastic amplitude variation with offset response of reflected arrivals and mode‐converted events. A series of one‐ and two‐dimensional synthetic examples are presented, demonstrating the ability to invert for and thereby to quantify both P‐ and S‐wave velocities for different velocity models. In particular, for more realistic low velocity models, including a typically soft seabed, an effective strategy for inversion is proposed to exploit both P‐ and mode‐converted PS‐waves. Whilst P‐wave events are exploited for inversion for P‐wave velocity, examples show the contribution of both P‐ and PS‐waves to the successful recovery of S‐wave velocity.     

S‐Doped Magnetic Mesoporous Carbon for Efficient Adsorption of Methyl Orange from Aqueous Solution

A simple and rapid soft‐templating coupled with one‐pot solvent thermal method is developed to synthesize S‐doped magnetic mesoporous carbon (S‐doped MMC). In this method, phenolic resin is used as a carbon precursor and Pluronic copolymer P123 is used as a template and 2,5‐dimercapto‐1,3,4‐thiadiazole is used as sulfur source. Prepared S‐doped MMC processes a high specific surface area, the Fe₃O₄ particles are well embedded in the mesoporous carbon walls that exhibit a strong magnetic response, and the hydrated iron nitrate loading amount of 0.808 g is the best. Batch adsorption experiments are carried out at different pH, initial concentration, temperature, and contact time on the adsorption of methyl orange (MO) by S‐doped MMC. The kinetic data of the adsorption process are better fitted with pseudo‐second‐order model than the pseudo‐first‐order model. Langmuir model is more suitable for the equilibrium data than Freundlich model. The thermodynamic parameters including ΔG⁰, ΔH⁰, and ΔS⁰ indicate that the adsorption is a feasible, spontaneous, and endothermic process. Finally, it is found that the coexistence of PO₄^3?, NO₃^?, SO₄^2?, Cl^?, and CO₃^2? does not influence the adsorption process. These results illustrate S‐doped MMC can be an efficient adsorbent for the removal of MO from wastewater.     

AVO investigations of shallow marine sediments

Amplitude‐variation‐with‐offset (AVO) analysis is based on the Zoeppritz equations, which enable the computation of reflection and transmission coefficients as a function of offset or angle of incidence. High‐frequency (up to 700 Hz) AVO studies, presented here, have been used to determine the physical properties of sediments in a shallow marine environment (20 m water depth). The properties that can be constrained are P‐ and S‐wave velocities, bulk density and acoustic attenuation. The use of higher frequencies requires special analysis including careful geometry and source and receiver directivity corrections. In the past, marine sediments have been modelled as elastic materials. However, viscoelastic models which include absorption are more realistic. At angles of incidence greater than 40°, AVO functions derived from viscoelastic models differ from those with purely elastic properties in the absence of a critical angle of incidence. The influence of S‐wave velocity on the reflection coefficient is small (especially for low S‐wave velocities encountered at the sea‐floor). Thus, it is difficult to extract the S‐wave parameter from AVO trends. On the other hand, P‐wave velocity and density show a considerably stronger effect. Attenuation (described by the quality factor Q) influences the reflection coefficient but could not be determined uniquely from the AVO functions. In order to measure the reflection coefficient in a seismogram, the amplitudes of the direct wave and the sea‐floor reflection in a common‐midpoint (CMP) gather are determined and corrected for spherical divergence as well as source and streamer directivity. At CMP locations showing the different AVO characteristics of a mud and a boulder clay, the sediment physical properties are determined by using a sequential‐quadratic‐programming (SQP) inversion technique. The inverted sediment physical properties for the mud are: P‐wave velocity α=1450±25 m/s, S‐wave velocity β=90±35 m/s, density ρ=1220±45 kg/m³, quality factor for P‐wave Q_P=15±200, quality factor for S‐wave Q_S=10±30. The inverted sediment physical properties for the boulder clay are: α=1620±45 m/s,β=360±200 m/s,ρ=1380±85 kg/m³,Q_P=790±660,Q_S=25±10.     

Migration of seismic activity during the 1998 volcanic unrest at Iwate volcano,northeastern Japan,with reference to P and S wave velocity anomaly and crustal deformation

We describe the seismicity at Iwate volcano, northeastern Japan, during the volcanic unrest of 1998 with reference to a three-dimensional P and S wave velocity model from tomographic analysis. The abnormal seismic activity beneath Iwate volcano started under the caldera in February, 1998 and migrated westward in the period February to August, 1998. Previous geodetic modeling [Sato and Hamaguchi, Chikyu Monthly 21 (1999) 312–317] suggested the growth of a dike in the time of the seismic activity. Comparing the seismicity and dike extension with the tomographic images of the P and S wave velocity structure, we find that the trace of the growing dike coincides with the region of the high V_p and high V_p/V_s ratio beneath the volcano. The seismic and geodetic data are consistent with an intrusion of magma or other fluid under the caldera in 1998. Another pressure source causing the predominant crustal deformation at Iwate volcano was detected from geodetic data, which was located in the region with high V_p/V_s ratio under the western end of the volcano through the period from February to August. It is suggested that the activation of the point pressure source probably associated with the inflation of a hot fluid reservoir relate to a geothermal region adjacent to the western edge of the volcano.     

Vp‐Vs relationship and amplitude variation with offset modelling of glauconitic greensand‡

The relationship between V_p and V_s may be used to predict V_s where only V_p is known. V_p/V_s is also used to identify pore fluids from seismic data and amplitude variation with offset analysis. Theoretical, physical, as well as statistical empirical V_p‐V_s relationships have been proposed for reservoir characterization when shear‐wave data are not available. In published work, the focus is primarily on the V_p‐V_s relationship of quartzitic sandstone. In order to broaden the picture we present V_p‐V_s relationships of greensand composed of quartz and glauconite by using data from the Paleocene greensand Nini oil field in the North Sea. A V_p‐V_s relationship derived from modelling is compared with empirical V_p‐V_s regressions from laboratory data as well as from log data. The accuracy of V_s prediction is quantified in terms of root‐mean‐square error. We find that the V_p‐V_s relationship derived from modelling works well for greensand shear‐wave velocity prediction. We model the seismic response of glauconitic greensand by using laboratory data from the Nini field. Our studies here reveal that brine‐saturated glauconitic greensand can have a similar seismic response to that from oil‐saturated quartzitic sandstone and that oil‐saturated strongly cemented greensand can have a similar amplitude variation with offset response to that from brine‐saturated weakly cemented greensand.