首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 94 毫秒
1.
Seismic inversion plays an important role in reservoir modelling and characterisation due to its potential for assessing the spatial distribution of the sub‐surface petro‐elastic properties. Seismic amplitude‐versus‐angle inversion methodologies allow to retrieve P‐wave and S‐wave velocities and density individually allowing a better characterisation of existing litho‐fluid facies. We present an iterative geostatistical seismic amplitude‐versus‐angle inversion algorithm that inverts pre‐stack seismic data, sorted by angle gather, directly for: density; P‐wave; and S‐wave velocity models. The proposed iterative geostatistical inverse procedure is based on the use of stochastic sequential simulation and co‐simulation algorithms as the perturbation technique of the model parametre space; and the use of a genetic algorithm as a global optimiser to make the simulated elastic models converge from iteration to iteration. All the elastic models simulated during the iterative procedure honour the marginal prior distributions of P‐wave velocity, S‐wave velocity and density estimated from the available well‐log data, and the corresponding joint distributions between density versus P‐wave velocity and P‐wave versus S‐wave velocity. We successfully tested and implemented the proposed inversion procedure on a pre‐stack synthetic dataset, built from a real reservoir, and on a real pre‐stack seismic dataset acquired over a deep‐water gas reservoir. In both cases the results show a good convergence between real and synthetic seismic and reliable high‐resolution elastic sub‐surface Earth models.  相似文献   

2.
We explore the link between basin modelling and seismic inversion by applying different rock physics models. This study uses the E‐Dragon II data in the Gulf of Mexico. To investigate the impact of different rock physics models on the link between basin modelling and seismic inversion, we first model relationships between seismic velocities and both (1) porosity and (2) effective stress for well‐log data using published rock physics models. Then, we build 1D basin models to predict seismic velocities derived from basin modelling with different rock physics models, in a comparison with average sonic velocities measured in the wells. Finally, we examine how basin modelling outputs can be used to aid seismic inversion by providing constraints for the background low‐frequency model. For this, we run different scenarios of inverting near angle partial stack seismic data into elastic impedances to test the impact of the background model on the quality of the inversion results. The results of the study suggest that the link between basin modelling and seismic technology is a two‐way interaction in terms of potential applications, and the key to refine it is establishing a rock physics models that properly describes changes in seismic signatures reflecting changes in rock properties.  相似文献   

3.
An extension of a previously developed rock physics model is made that quantifies the relationship between the ductile fraction of a brittle/ductile binary mixture and the isotropic seismic reflection response. By making a weak scattering (Born) approximation and plane wave (eikonal) approximation, with a subsequent ordering according to the angles of incidence, singular value decomposition analyses are performed to understand the stack weightings, number of stacks, and the type of stacks that will optimally estimate two fundamental rock physics parameters – the ductile fraction and the compaction and/or diagenesis. It is concluded that the full PP stack, i.e., sum of all PP offset traces, and the “full” PS stack, i.e., linear weighted sum of PS offset traces, are the two optimal stacks needed to estimate the two rock physics parameters. They dominate over both the second‐order amplitude variation offset “gradient” stack, which is a quadratically weighted sum of PP offset traces that is effectively the far offset traces minus the near offset traces, and the higher order fourth order PP stack (even at large angles of incidence). Using this result and model‐based Bayesian inversion, the seismic detectability of the ductile fraction (shown by others to be the important rock property for the geomechanical response of unconventional reservoir fracking) is demonstrated on a model characteristic of the Marcellus shale play.  相似文献   

4.
A workflow for simultaneous joint PP‐PS prestack inversion of data from the Schiehallion field on the United Kingdom Continental Shelf is presented and discussed. The main challenge, describing reasonable PS to PP data registration before any prestack or joint PP‐PS inversion, was overcome thanks to a two‐stage process addressing the signal envelope, then working directly on the seismic data to estimate appropriate time‐variant time‐shift volumes. We evaluated the benefits of including PS along with PP prestack seismic data in a joint inversion process to improve the estimated elastic property quality and also to enable estimation of density compared with other prestack and post‐stack inversion approaches. While the estimated acoustic impedance exhibited a similar quality independent of the inversion used (PP post‐stack, PP prestack or joint PP‐PS prestack inversion) the shear impedance estimation was noticeably improved by the joint PP‐PS prestack inversion when compared to the PP prestack inversion. Finally, the density estimated from joint PP and PS prestack data demonstrated an overall good quality, even where not well‐controlled. The main outcome of this study was that despite several data‐related limitations, inverting jointly correctly processed PP and PS data sets brought extra value for reservoir delineation as opposed to PP‐only or post‐stack inversion.  相似文献   

5.
针对某复杂断块天然气目标储层,在岩石物理分析的指导下,综合利用地质、地震、测井等资料,提出了一套面向复杂天然气藏的叠前地震预测技术.首先基于地震岩石物理分析得到的初始横波信息,采用叠前贝叶斯非线性三参数反演得到了井旁控制点处精确纵横波速度和密度信息,然后通过叠前/叠后联合反演技术实现了面向目标的弹性阻抗体反演及含气储层敏感参数直接提取,最后结合小波变换时频谱分析的方法从叠前地震资料中估算地层吸收参数值,提高天然气藏识别精度.实际应用表明,综合各种叠前地震预测技术,可以大大提高对复杂天然气藏的识别精度,降低勘探风险.  相似文献   

6.
Seismic amplitudes contain important information that can be related to fluid saturation. The amplitude‐versus‐offset analysis of seismic data based on Gassmann's theory and the approximation of the Zoeppritz equations has played a central role in reservoir characterization. However, this standard technique faces a long‐standing problem: its inability to distinguish between partial gas and “fizz‐water” with little gas saturation. In this paper, we studied seismic dispersion and attenuation in partially saturated poroelastic media by using frequency‐dependent rock physics model, through which the frequency‐dependent amplitude‐versus‐offset response is calculated as a function of porosity and water saturation. We propose a cross‐plotting of two attributes derived from the frequency‐dependent amplitude‐versus‐offset response to differentiate partial gas saturation and “fizz‐water” saturation. One of the attributes is a measure of “low frequency”, or Gassmann, of reflectivity, whereas the other is a measure of the “frequency dependence” of reflectivity. This is in contrast to standard amplitude‐versus‐offset attributes, where there is typically no such separation. A pragmatic frequency‐dependent amplitude‐versus‐offset inversion for rock and fluid properties is also established based on Bayesian theorem. A synthetic study is performed to explore the potential of the method to estimate gas saturation and porosity variations. An advantage of our work is that the method is in principle predictive, opening the way to further testing and calibration with field data. We believe that such work should guide and augment more theoretical studies of frequency‐dependent amplitude‐versus‐offset analysis.  相似文献   

7.
Underground fractures play an important role in the storage and movement of hydrocarbon fluid. Fracture rock physics has been the useful bridge between fracture parameters and seismic response. In this paper, we aim to use seismic data to predict subsurface fractures based on rock physics. We begin with the construction of fracture rock physics model. Using the model, we may estimate P-wave velocity, S-wave velocity and fracture rock physics parameters. Then we derive a new approximate formula for the analysis of the relationship between fracture rock physics parameters and seismic response, and we also propose the method which uses seismic data to invert the elastic and rock physics parameters of fractured rock. We end with the method verification, which includes using well-logging data to confirm the reliability of fracture rock physics effective model and utilizing real seismic data to validate the applicability of the inversion method. Tests show that the fracture rock physics effective model may be used to estimate velocities and fracture rock physics parameters reliably, and the inversion method is resultful even when the seismic data is added with random noise. Real data test also indicates the inversion method can be applied into the estimation of the elastic and fracture weaknesses parameters in the target area.  相似文献   

8.
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 Vs/Vp ratio. Conventional methods use a constant or a time‐varying Vs/Vp model. Here, a time‐ and space‐varying model is used during the computation of the ‘reflectivities’. The Vs/Vp model is generated using well log data and picked horizons. For multicomponent data applications, the latter model can also be generated from processing Vs/Vp 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. Vp/Vs 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.  相似文献   

9.
Fluid depletion within a compacting reservoir can lead to significant stress and strain changes and potentially severe geomechanical issues, both inside and outside the reservoir. We extend previous research of time‐lapse seismic interpretation by incorporating synthetic near‐offset and full‐offset common‐midpoint reflection data using anisotropic ray tracing to investigate uncertainties in time‐lapse seismic observations. The time‐lapse seismic simulations use dynamic elasticity models built from hydro‐geomechanical simulation output and a stress‐dependent rock physics model. The reservoir model is a conceptual two‐fault graben reservoir, where we allow the fault fluid‐flow transmissibility to vary from high to low to simulate non‐compartmentalized and compartmentalized reservoirs, respectively. The results indicate time‐lapse seismic amplitude changes and travel‐time shifts can be used to qualitatively identify reservoir compartmentalization. Due to the high repeatability and good quality of the time‐lapse synthetic dataset, the estimated travel‐time shifts and amplitude changes for near‐offset data match the true model subsurface changes with minimal errors. A 1D velocity–strain relation was used to estimate the vertical velocity change for the reservoir bottom interface by applying zero‐offset time shifts from both the near‐offset and full‐offset measurements. For near‐offset data, the estimated P‐wave velocity changes were within 10% of the true value. However, for full‐offset data, time‐lapse attributes are quantitatively reliable using standard time‐lapse seismic methods when an updated velocity model is used rather than the baseline model.  相似文献   

10.
This paper discusses and addresses two questions in carbonate reservoir characterization: how to characterize pore‐type distribution quantitatively from well observations and seismic data based on geologic understanding of the reservoir and what geological implications stand behind the pore‐type distribution in carbonate reservoirs. To answer these questions, three geophysical pore types (reference pores, stiff pores and cracks) are defined to represent the average elastic effective properties of complex pore structures. The variability of elastic properties in carbonates can be quantified using a rock physics scheme associated with different volume fractions of geophysical pore types. We also explore the likely geological processes in carbonates based on the proposed rock physics template. The pore‐type inversion result from well log data fits well with the pore geometry revealed by a FMI log and core information. Furthermore, the S‐wave prediction based on the pore‐type inversion result also shows better agreement than the Greensberg‐Castagna relationship, suggesting the potential of this rock physics scheme to characterize the porosity heterogeneity in carbonate reservoirs. We also apply an inversion technique to quantitatively map the geophysical pore‐type distribution from a 2D seismic data set in a carbonate reservoir offshore Brazil. The spatial distributions of the geophysical pore type contain clues about the geological history that overprinted these rocks. Therefore, we analyse how the likely geological processes redistribute pore space of the reservoir rock from the initial depositional porosity and in turn how they impact the reservoir quality.  相似文献   

11.
State‐of‐the‐art 3D seismic acquisition geometries have poor sampling along at least one dimension. This results in coherent migration noise that always contaminates pre‐stack migrated data, including high‐fold surveys, if prior‐to‐migration interpolation was not applied. We present a method for effective noise suppression in migrated gathers, competing with data interpolation before pre‐stack migration. The proposed technique is based on a dip decomposition of common‐offset volumes and a semblance‐type measure computation via offset for all constant‐dip gathers. Thus the processing engages six dimensions: offset, inline, crossline, depth, inline dip, and crossline dip. To reduce computational costs, we apply a two‐pass (4D in each pass) noise suppression: inline processing and then crossline processing (or vice versa). Synthetic and real‐data examples verify that the technique preserves signal amplitudes, including amplitude‐versus‐offset dependence, and that faults are not smeared.  相似文献   

12.
In this paper we present a case history of seismic reservoir characterization where we estimate the probability of facies from seismic data and simulate a set of reservoir models honouring seismically‐derived probabilistic information. In appraisal and development phases, seismic data have a key role in reservoir characterization and static reservoir modelling, as in most of the cases seismic data are the only information available far away from the wells. However seismic data do not provide any direct measurements of reservoir properties, which have then to be estimated as a solution of a joint inverse problem. For this reason, we show the application of a complete workflow for static reservoir modelling where seismic data are integrated to derive probability volumes of facies and reservoir properties to condition reservoir geostatistical simulations. The studied case is a clastic reservoir in the Barents Sea, where a complete data set of well logs from five wells and a set of partial‐stacked seismic data are available. The multi‐property workflow is based on seismic inversion, petrophysics and rock physics modelling. In particular, log‐facies are defined on the basis of sedimentological information, petrophysical properties and also their elastic response. The link between petrophysical and elastic attributes is preserved by introducing a rock‐physics model in the inversion methodology. Finally, the uncertainty in the reservoir model is represented by multiple geostatistical realizations. The main result of this workflow is a set of facies realizations and associated rock properties that honour, within a fixed tolerance, seismic and well log data and assess the uncertainty associated with reservoir modelling.  相似文献   

13.
Seismic reflection pre‐stack angle gathers can be simultaneously inverted within a joint facies and elastic inversion framework using a hierarchical Bayesian model of elastic properties and categorical classes of rock and fluid properties. The Bayesian prior implicitly supplies low frequency information via a set of multivariate compaction trends for each rock and fluid type, combined with a Markov random field model of lithotypes, which carries abundance and continuity preferences. For the likelihood, we use a simultaneous, multi‐angle, convolutional model, which quantifies the data misfit probability using wavelets and noise levels inferred from well ties. Under Gaussian likelihood and facies‐conditional prior models, the posterior has simple analytic form, and the maximum a‐posteriori inversion problem boils down to a joint categorical/continuous non‐convex optimisation problem. To solve this, a set of alternative, increasingly comprehensive optimisation strategies is described: (i) an expectation–maximisation algorithm using belief propagation, (ii) a globalisation of method (i) using homotopy, and (iii) a discrete space approach using simulated annealing. We find that good‐quality inversion results depend on both sensible, elastically separable facies definitions, modest resolution ambitions, reasonably firm abundance and continuity parameters in the Markov random field, and suitable choice of algorithm. We suggest usually two to three, perhaps four, unknown facies per sample, and usage of the more expensive methods (homotopy or annealing) when the rock types are not strongly distinguished in acoustic impedance. Demonstrations of the technique on pre‐stack depth‐migrated field data from the Exmouth basin show promising agreements with lithological well data, including prediction accuracy improvements of 24% in and twofold in density, in comparison to a standard simultaneous inversion. Much clearer and extensive recovery of the thin Pyxis gas field was evident using stronger coupling in the Markov random field model and use of the homotopy or annealing algorithms.  相似文献   

14.
Wide-azimuth seismic data can be used to derive anisotropic parameters on the subsurface by observing variation in subsurface seismic response along different azimuths. Layer-based high-resolution estimates of components of the subsurface anisotropic elastic tensor can be reconstructed by using wide-azimuth P-wave data by combining the kinematic information derived from anisotropic velocity analysis with dynamic information obtained from amplitude versus angle and azimuth analysis of wide-azimuth seismic data. Interval P-impedance, S-impedance and anisotropic parameters associated with anisotropic fracture media are being reconstructed using linearized analysis assuming horizontal transverse anisotropy symmetry. In this paper it is shown how additional assumptions, such as the rock model, can be used to reduce the degrees of freedom in the estimation problem and recover all five anisotropic parameters. Because the use of a rock model is needed, the derived elastic parameters are consistent with the rock model and are used to infer fractured rock properties using stochastic rock physics inversion. The inversion is based on stochastic rock physics modelling and maximum a posteriori estimate of both porosity and crack density parameters associated with the observed elastic parameters derived from both velocity and amplitude versus angle and azimuth analysis. While the focus of this study is on the use of P-wave reflection data, we also show how additional information such as shear wave splitting and/or anisotropic well log data can reduce the assumptions needed to derive elastic parameter and rock properties.  相似文献   

15.
Geostatistical seismic inversion methods are routinely used in reservoir characterisation studies because of their potential to infer the spatial distribution of the petro‐elastic properties of interest (e.g., density, elastic, and acoustic impedance) along with the associated spatial uncertainty. Within the geostatistical seismic inversion framework, the retrieved inverse elastic models are conditioned by a global probability distribution function and a global spatial continuity model as estimated from the available well‐log data for the entire inversion grid. However, the spatial distribution of the real subsurface elastic properties is complex, heterogeneous, and, in many cases, non‐stationary since they directly depend on the subsurface geology, i.e., the spatial distribution of the facies of interest. In these complex geological settings, the application of a single distribution function and a spatial continuity model is not enough to properly model the natural variability of the elastic properties of interest. In this study, we propose a three‐dimensional geostatistical inversion technique that is able to incorporate the reservoir's heterogeneities. This method uses a traditional geostatistical seismic inversion conditioned by local multi‐distribution functions and spatial continuity models under non‐stationary conditions. The procedure of the proposed methodology is based on a zonation criterion along the vertical direction of the reservoir grid. Each zone can be defined by conventional seismic interpretation, with the identification of the main seismic units and significant variations of seismic amplitudes. The proposed method was applied to a highly non‐stationary synthetic seismic dataset with different levels of noise. The results of this work clearly show the advantages of the proposed method against conventional geostatistical seismic inversion procedures. It is important to highlight the impact of this technique in terms of higher convergence between real and inverted reflection seismic data and the more realistic approximation towards the real subsurface geology comparing with traditional techniques.  相似文献   

16.
We extend the frequency‐ and angle‐dependent poroelastic reflectivity to systematically analyse the characteristic of seismic waveforms for highly attenuating reservoir rocks. It is found that the mesoscopic fluid pressure diffusion can significantly affect the root‐mean‐square amplitude, frequency content, and phase signatures of seismic waveforms. We loosely group the seismic amplitude‐versus‐angle and ‐frequency characteristics into three classes under different geological circumstances: (i) for Class‐I amplitude‐versus‐angle and ‐frequency, which corresponds to well‐compacted reservoirs having Class‐I amplitude‐versus‐offset characteristic, the root‐mean‐square amplitude at near offset is boosted at high frequency, whereas seismic energy at far offset is concentrated at low frequency; (ii) for Class‐II amplitude‐versus‐angle and ‐frequency, which corresponds to moderately compacted reservoirs having Class‐II amplitude‐versus‐offset characteristic, the weak seismic amplitude might exhibit a phase‐reversal trend, hence distorting both the seismic waveform and energy distribution; (iii) for Class‐III amplitude‐versus‐angle and ‐frequency, which corresponds to unconsolidated reservoir having Class‐III amplitude‐versus‐offset characteristic, the mesoscopic fluid flow does not exercise an appreciable effect on the seismic waveforms, but there exists a non‐negligible amplitude decay compared with the elastic seismic responses based on the Zoeppritz equation.  相似文献   

17.
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 (VS/VP) 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 VS/VP 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.  相似文献   

18.
The generalized Radon transform (GRT) inversion contains an explicit relationship between seismic amplitude variations, the reflection angle and the physical parameters which can be used to describe the earth efficiently for inversion purposes. Using this relationship, we have derived parametrizations for acoustic and P–P scattering so that the variations in seismic amplitude with reflection angle for each parameter are sufficiently independent. These parametrizations show that small offset and large offset amplitudes are related to different physical parameters. In the case of acoustic scattering, the small-offset amplitudes are related to impedance variations while large-offset amplitudes are related to velocity variations. A similar result has been established for P–P scattering. The Born approximation (which is used to derive the GRT inversion) does not correctly predict the amplitude due to velocity variations at large offsets, and thus the inversion of velocity is not as satisfactory as the inversion of impedance.  相似文献   

19.
Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.  相似文献   

20.
We have previously applied three‐dimensional acoustic, anisotropic, full‐waveform inversion to a shallow‐water, wide‐angle, ocean‐bottom‐cable dataset to obtain a high‐resolution velocity model. This velocity model produced an improved match between synthetic and field data, better flattening of common‐image gathers, a closer fit to well logs, and an improvement in the pre‐stack depth‐migrated image. Nevertheless, close examination reveals that there is a systematic mismatch between the observed and predicted data from this full‐waveform inversion model, with the predicted data being consistently delayed in time. We demonstrate that this mismatch cannot be produced by systematic errors in the starting model, by errors in the assumed source wavelet, by incomplete convergence, or by the use of an insufficiently fine finite‐difference mesh. Throughout these tests, the mismatch is remarkably robust with the significant exception that we do not see an analogous mismatch when inverting synthetic acoustic data. We suspect therefore that the mismatch arises because of inadequacies in the physics that are used during inversion. For ocean‐bottom‐cable data in shallow water at low frequency, apparent observed arrival times, in wide‐angle turning‐ray data, result from the characteristics of the detailed interference pattern between primary refractions, surface ghosts, and a large suite of wide‐angle multiple reflected and/or multiple refracted arrivals. In these circumstances, the dynamics of individual arrivals can strongly influence the apparent arrival times of the resultant compound waveforms. In acoustic full‐waveform inversion, we do not normally know the density of the seabed, and we do not properly account for finite shear velocity, finite attenuation, and fine‐scale anisotropy variation, all of which can influence the relative amplitudes of different interfering arrivals, which in their turn influence the apparent kinematics. Here, we demonstrate that the introduction of a non‐physical offset‐variable water density during acoustic full‐waveform inversion of this ocean‐bottom‐cable field dataset can compensate efficiently and heuristically for these inaccuracies. This approach improves the travel‐time match and consequently increases both the accuracy and resolution of the final velocity model that is obtained using purely acoustic full‐waveform inversion at minimal additional cost.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号