A parallel computing thin‐sheet inversion algorithm for airborne time‐domain data utilising a variable overburden

Accurate modelling of the conductivity structure of mineralisations can often be difficult. In order to remedy this, a parametric approach is often used. We have developed a parametric thin‐sheet code, with a variable overburden. The code is capable of performing inversions of time‐domain airborne electromagnetic data, and it has been tested successfully on both synthetic data and field data. The code implements an integral solution containing one or more conductive sheets, buried in a half‐space with a laterally varying conductive overburden. This implementation increases the area of applicability compared to, for example, codes operating in free space, but it comes with a significant increase in computational cost. To minimise the cost, the code is parallelised using OpenMP and heavily optimised, which means that inversions of field data can be performed in hours on multiprocessor desktop computers. The code models the full system transfer function of the electromagnetic system, including variable flight height. The code is demonstrated with a synthetic example imitating a mineralisation buried underneath a conductive meadow. As a field example, the Valen mineral deposit, which is a graphite mineral deposit located in a variable overburden, is successfully inverted. Our results match well with previous models of the deposit; however, our predicted sheet remains inconclusive. These examples collectively demonstrate the effectiveness of our thin‐sheet code.     

Application of the redundant-lifting scheme for ground-roll attenuation in near-surface characterization using full-waveform inversion on P-wave seismic data

Seismic modelling of the shallow subsurface (within the first few metres) is often challenging when the data are dominated by ground-roll and devoid of reflection. We showed that, even when transmission is the only available phase for analysis, fine-scale and interpretable P-wave velocity (V_P) and attenuation (Q_P⁻¹) models can still be prepared using full-waveform inversion, with data being preconditioned for ground-roll. To prove this idea, we suppressed the ground-roll in two different ways before full-waveform inversion modelling: first, through a bottom mute; second, through a novel wavelet transform-based method known as the redundant-lifting scheme. The applicability of full-waveform inversion is tested through imaging two buried targets. These include a pair of utility water pipes with known diameters of 0.8 m and burial depths of 1.5 m, respectively. The second target is the poorly documented backfill, which was the former location of the pipe(s). The data for full-waveform inversion are acquired along a 2D profile using a static array of 24, 40 Hz vertical component geophones and a buried point source. The results show that (a) the redundant-lifting scheme better suppresses the ground roll, which in turn provides better images of the targets in full-waveform inversion; and (b) the V_P and Q_P⁻¹ models from full-waveform inversion of redundant-lifting scheme data could detect the two targets adequately.     

Constructing a discrete fracture network constrained by seismic inversion data

Rock fractures are of great practical importance to petroleum reservoir engineering because they provide pathways for fluid flow, especially in reservoirs with low matrix permeability, where they constitute the primary flow conduits. Understanding the spatial distribution of natural fracture networks is thus key to optimising production. The impact of fracture systems on fluid flow patterns can be predicted using discrete fracture network models, which allow not only the 6 independent components of the second‐rank permeability tensor to be estimated, but also the 21 independent components of the fully anisotropic fourth‐rank elastic stiffness tensor, from which the elastic and seismic properties of the fractured rock medium can be predicted. As they are stochastically generated, discrete fracture network realisations are inherently non‐unique. It is thus important to constrain their construction, so as to reduce their range of variability and, hence, the uncertainty of fractured rock properties derived from them. This paper presents the underlying theory and implementation of a method for constructing a geologically realistic discrete fracture network, constrained by seismic amplitude variation with offset and azimuth data. Several different formulations are described, depending on the type of seismic data and prior geologic information available, and the relative strengths and weaknesses of each approach are compared. Potential applications of the method are numerous, including the prediction of fluid flow, elastic and seismic properties of fractured reservoirs, model‐based inversion of seismic amplitude variation with offset and azimuth data, and the optimal placement and orientation of infill wells to maximise production.     

Elongated horizontal and vertical receivers in three-dimensional electromagnetic modelling and inversion

Electromagnetic geophysical methods often rely on measurements of naturally occurring or artificially impressed electric fields. It is technically impossible, however, to measure the electric field directly. Instead, the electric field is approximated by recording the voltage difference between two electrodes and dividing the obtained voltage by the distance between the electrodes. Typically, modelling and inversion algorithms assume that the electric fields are obtained over infinitely short point-dipoles and thus measured fields are assigned to a single point between the electrodes. Such procedures imply several assumptions: (1) The electric field between the two electrodes is regarded as constant or being a potential field and (2) the receiver dimensions are negligible compared to the dimensions of the underlying modelling grid. While these conditions are often fulfilled for horizontal electric fields, borehole sensors for recordings of the vertical electric field have dimensions in the order of ≈100 m and span several modelling grid cells. Observations from such elongated borehole sensors can therefore only be interpreted properly if true receiver dimensions and variations of electrical conductivity along the receiver are considered. Here, we introduce a numerical solution to include the true receiver geometry into electromagnetic modelling schemes, which does not rely on such simplifying assumptions. The algorithm is flexible, independent of the chosen numerical method to solve Maxwell's equations and can easily be implemented in other electromagnetic modelling and inversion codes. We present conceptual modelling results for land-based controlled source electromagnetic scenarios and discuss consideration of true receiver geometries for a series of examples of horizontal and vertical electric field measurements. Comparison with Ez data measured in an observation borehole in a producing oil field shows the importance of both considering the true length of the receiver and also its orientation. We show that misalignment from the vertical axis as small as 0.1° may seriously distort the measured signal, as horizontal electric field components are mapped into the desired vertical component. Adequate inclusion of elongated receivers in modelling and inversion can also help reducing effects of static shift when interpreting (natural source) magnetotelluric data.     

Full waveform inversion of SH‐ and Love‐wave data in near‐surface prospecting

We develop a two‐dimensional full waveform inversion approach for the simultaneous determination of S‐wave velocity and density models from SH ‐ and Love‐wave data. We illustrate the advantages of the SH/Love full waveform inversion with a simple synthetic example and demonstrate the method's applicability to a near‐surface dataset, recorded in the village ?achtice in Northwestern Slovakia. Goal of the survey was to map remains of historical building foundations in a highly heterogeneous subsurface. The seismic survey comprises two parallel SH‐profiles with maximum offsets of 24 m and covers a frequency range from 5 Hz to 80 Hz with high signal‐to‐noise ratio well suited for full waveform inversion. Using the Wiechert–Herglotz method, we determined a one‐dimensional gradient velocity model as a starting model for full waveform inversion. The two‐dimensional waveform inversion approach uses the global correlation norm as objective function in combination with a sequential inversion of low‐pass filtered field data. This mitigates the non‐linearity of the multi‐parameter inverse problem. Test computations show that the influence of visco‐elastic effects on the waveform inversion result is rather small. Further tests using a mono‐parameter shear modulus inversion reveal that the inversion of the density model has no significant impact on the final data fit. The final full waveform inversion S‐wave velocity and density models show a prominent low‐velocity weathering layer. Below this layer, the subsurface is highly heterogeneous. Minimum anomaly sizes correspond to approximately half of the dominant Love‐wavelength. The results demonstrate the ability of two‐dimensional SH waveform inversion to image shallow small‐scale soil structure. However, they do not show any evidence of foundation walls.     

Experimental quantification of the seismoelectric transfer function and its dependence on conductivity and saturation in loose sand

Under certain circumstances, seismic propagation within porous media may be associated to the conversion of mechanical energy to electromagnetic energy, which is known as a seismo‐electromagnetic phenomenon. The propagation of fast compressional P‐waves is more specifically associated to the manifestations of a seismoelectric field linked to the fluid flows within the pores. The analysis of seismoelectric phenomena, which requires the combination of the theory of electrokinetics and Biot's theory of poroelasticity, provides us with transfer function that links the coseismic seismoelectric field E to the seismic acceleration . To measure the transfer function, we have developed an experimental setup enabling seismoelectric laboratory observation in unconsolidated quartz sand within the kilohertz range. The investigation focused on the impact of fluid conductivity and water saturation over the coseismic seismoelectric field. During the experiment, special attention was given to the accuracy of electric field measurements. We concluded that, to obtain a reliable estimate of the electric field amplitude, the dipole from which the potential differences are measured should be of much smaller length than the wavelength of the propagating seismic field. Time‐lapse monitoring of the seismic velocities and seismoelectric transfer functions were performed during imbibition and drainage experiments. In all cases, the quantitative analysis of the seismoelectric transfer function was in good agreement with theoretical predictions. While investigating saturation variations from full to residual water saturation, we showed that the ratio undergoes a switch in polarity at a particular saturation , which also implies a sign change of the filtration, traducing a reversal of the relative fluid displacement with respect to the frame. This sign change at critical saturation stresses a particular behaviour of the poroelastic medium: the dropping of the coseismic electric field to zero traduces the absence of relative pore/fluid displacements representative of a Biot dynamically compatible medium. We concluded from our experimental study in loose sand that the measurements of the coseismic seismoelectric coupling may provide information on fluid distribution within the pores and that the reversal of the seismoelectric field may be used as an indicator of the dynamically compatible state of the medium.     

Three-dimensional inversion of airborne data with applications for detecting elongated subvertical bodies overlapped by an inhomogeneous conductive layer with topography

We propose the approach to 3D inversion of airborne electromagnetic data, which is intended for discovering subvertical bodies overlapped by essentially inhomogeneous conductive layers. The approach is based on the geometric inversion in which a geoelectrical medium is parameterized with the use of block structures. During the inversion, the coordinates of the borders between the blocks and the rows of the blocks as well as resistivities inside them are determined. In order to solve the forward problem of the airborne electromagnetic survey, we use the non-conforming optimized mesh with the hexahedral cells, which enables us to reduce the number of degrees of freedom and smoothly approximate the curved borders of a geological medium. For a more reliable discovery of subvertical objects, we propose to carry out 3D inversions at several rotations of block structures relative to the flight lines. The workability of this approach is demonstrated using the data which are synthesized for complex geoelectrical models with topography, inhomogeneous overlapping layers and target subvertical bodies oriented differently relative to the flight lines. The results of this investigation show that, in some way or other, the elongated subvertical object is discovered and its orientation (the direction of its long side) is defined at different rotations of block structures used in 3D inversions. However, the most accurate recovery of the subvertical object length is achieved when the direction of its long side almost coincides with the direction of one of the block structures axes. Thus, the block structures rotations allow not only more reliably discovering a target object in complex geoelectrical conditions, but also more exactly defining its orientation and length.     

Comparison of acoustic and elastic full-waveform inversion of 2D towed-streamer data in the presence of salt

Over the last years, full-waveform inversion has become an important tool in the list of processing and imaging technologies available to the industry. For marine towed-streamer data, full-waveform inversion is typically applied using an acoustic approximation because S-waves do not propagate in water and elastic effects in recorded data are generally assumed to be small. We compare acoustic and elastic modelling and full-waveform inversion for a field data set acquired offshore Angola over sediments containing a salt body with significant topology. Forward modelling tests reveal that such geological structures lead to significant mode conversions at interfaces and, consequently, to significant relative amplitude differences when elastically and acoustically modelled traces are compared. Using an acoustic approach for modelling in full-waveform inversion therefore leads to problems matching the synthetic data with the field data, even for recorded pressure data and with trace normalization applied. Full-waveform inversion is unable to find consistent model updates. Applying elastic full-waveform inversion leads to more consistent and reliable model updates with less artefacts, at the expense of additional computation cost. Although two-dimensional marine towed-streamer data are least favourable for the application of full-waveform inversion compared to three-dimensional data or ocean-bottom data, it is recommended to check on the existence of elastic effects before deciding on the final processing and imaging approach.     

叠前反演和地震吸收技术在复杂天然气藏地震预测中的应用

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.     

Effects of metallic system components on marine electromagnetic loop data

Electromagnetic loop systems rely on the use of non-conductive materials near the sensor to minimize bias effects superimposed on measured data. For marine sensors, rigidity, compactness and ease of platform handling are essential. Thus, commonly a compromise between rigid, cost-effective and non-conductive materials (e.g. stainless steel versus fibreglass composites) needs to be found. For systems dedicated to controlled-source electromagnetic measurements, a spatial separation between critical system components and sensors may be feasible, whereas compact multi-sensor platforms, remotely operated vehicles and autonomous unmanned vehicles require the use of electrically conductive components near the sensor. While data analysis and geological interpretations benefit vastly from each added instrument and multidisciplinary approaches, this introduces a systematic and platform-immanent bias in the measured electromagnetic data. In this scope, we present two comparable case studies targeting loop-source electromagnetic applications in both time and frequency domains: the time-domain system trades the compact design for a clear separation of 15 m between an upper fibreglass frame, holding most critical titanium system components, and a lower frame with its coil and receivers. In case of the frequency-domain profiler, the compact and rigid design is achieved by a circular fibreglass platform, carrying the transmitting and receiving coils, as well as several titanium housings and instruments. In this study, we analyse and quantify the quasi-static influence of conductive objects on time- and frequency-domain coil systems by applying an analytically and experimentally verified 3D finite element model. Moreover, we present calibration and optimization procedures to minimize bias inherent in the measured data. The numerical experiments do not only show the significance of the bias on the inversion results, but also the efficiency of a system calibration against the analytically calculated response of a known environment. The remaining bias after calibration is a time/frequency-dependent function of seafloor conductivity, which doubles the commonly estimated noise floor from 1% to 2%, decreasing the sensitivity and resolution of the devices. By optimizing size and position of critical conductive system components (e.g. titanium housings) and/or modifying the transmitter/receiver geometry, we significantly reduce the effect of this residual bias on the inversion results as demonstrated by 3D modelling. These procedures motivate the opportunity to design dedicated, compact, low-bias platforms and provide a solution for autonomous and remotely steered designs by minimizing their effect on the sensitivity of the controlled-source electromagnetic sensor.     

Separation of PP- and PS-wave reflected seismic data using two-dimensional finite offset common-reflection-surface traveltime approximation

Recently, the interest in PS-converted waves has increased for several applications, such as sub-basalt layer imaging, impedance estimates and amplitude-versus-offset analysis. In this study, we consider the problem of separation of PP- and PS-waves from pre-stacked multicomponent seismic data in two-dimensional isotropic medium. We aim to demonstrate that the finite-offset common-reflection-surface traveltime approximation is a good alternative for separating PP- and PS-converted waves in common-offset and common shot configurations by considering a two-dimensional isotropic medium. The five parameters of the finite-offset common-reflection-surface are firstly estimated through the inversion methodology called very fast simulated annealing, which estimates all parameters simultaneously. Next, the emergence angle, one of the inverted parameters, is used to build an analytical separation function of PP and PS reflection separation based on the wave polarization equations. Once the PP- and PS-converted waves were separated, the sections are stacked to increase the signal-to-noise ratio using the special curves derived from finite-offset common-reflection-surface approximation. We applied this methodology to a synthetic dataset from simple-layered to complex-structured media. The numerical results showed that the inverted parameters of the finite offset common-reflection-surface and the separation function yield good results for separating PP- and PS-converted waves in noisy common-offset and common shot gathers.     

二维叠后地震数据的平稳随机介质参数估计

随机介质参数估计是随机介质理论应用于地震勘探的关键.本文提出了一种从二维叠后地震数据中估计平稳随机介质参数的方法.文中阐述了二维叠后地震数据与随机介质波阻抗模型的关系,以及随机介质自相关函数参数的估计原理和方法,并结合实例详细介绍了应用功率谱法进行随机介质参数估计的具体步骤;通过多个二维理论模型的估计试验,验证了方法的可行性和正确性;还对实际地震数据进行了随机介质参数的估计试验,结果表明,随机介质参数可以为三角洲沉积相的进一步划分提供参考,反映了该方法有较好的应用前景.相比前人的研究,本文所提出的随机介质参数估计方法是一种真正的二维算法,特别是能给出自相关角度θ的估计,这种基于功率谱的估计方法具有直观且高效率的优点,但也存在着误差较大的问题,需要进一步的改进和完善.     

Integration of rock physics and seismic inversion for rock typing and flow unit analysis: A case study

Rock typing and flow unit detection are more challenging in clastic reservoirs with a uniform pore system. An integrated workflow based on well logs, inverted seismic data and rock physics models is proposed and developed to address such challenges. The proposed workflow supplies a plausible reservoir model for further investigation and adds extra information. Then, this workflow has been implemented in order to define different rock types and flow units in an oilfield in the Persian Gulf, where some of these difficulties have been observed. Here, rock physics models have the leading role in our proposed workflow by providing a diagnostic framework in which we successfully differentiate three rock types with variant characteristics on the given wells. Furthermore, permeability and porosity are calculated using the available rock physics models to define several flow units. Then, we extend our investigation to the entire reservoir by means of simultaneous inversion and rock physics models. The outcomes of the study suggest that in sediments with homogeneous pore size distribution, other reservoir properties such as shale content and cementation (which have distinct effects on the elastic domain) can be used to identify rock types and flow units. These reservoir properties have more physical insights for modelling purposes and can be distinguished on seismic cube using proper rock physics models. The results illustrate that the studied reservoir mainly consists of rock type B, which is unconsolidated sands and has the characteristics of a reservoir for subsequent fluid flow unit analysis. In this regard, rock type B has been divided into six fluid units in which the first detected flow unit is considered as the cleanest unit and has the highest reservoir process speed about 4800 to 5000 mD. Here, reservoir quality decreases from flow unit 1 to flow unit 6.     

Look-ahead vertical seismic profiling inversion approach for density and compressional wave velocity in Bayesian framework

To reduce drilling uncertainties, zero-offset vertical seismic profiles can be inverted to quantify acoustic properties ahead of the bit. In this work, we propose an approach to invert vertical seismic profile corridor stacks in Bayesian framework for look-ahead prediction. The implemented approach helps to successfully predict density and compressional wave velocity using prior knowledge from drilled interval. Hence, this information can be used to monitor reservoir depth as well as quantifying high-pressure zones, which enables taking the correct decision during drilling. The inversion algorithm uses Gauss–Newton as an optimization tool, which requires the calculation of the sensitivity matrix of trace samples with respect to model parameters. Gauss–Newton has quadratic rate of convergence, which can speed up the inversion process. Moreover, geo-statistical analysis has been used to efficiently utilize prior information supplied to the inversion process. The algorithm has been tested on synthetic and field cases. For the field case, a zero-offset vertical seismic profile data taken from an offshore well were used as input to the inversion algorithm. Well logs acquired after drilling the prediction section was used to validate the inversion results. The results from the synthetic case applications were encouraging to accurately predict compressional wave velocity and density from just a constant prior model. The field case application shows the strength of our proposed approach in inverting vertical seismic profile data to obtain density and compressional wave velocity ahead of a bit with reasonable accuracy. Unlike the commonly used vertical seismic profile inversion approach for acoustic impedance using simple error to represent the prior covariance matrix, this work shows the importance of inverting for both density and compressional wave velocity using geo-statistical knowledge of density and compressional wave velocity from the drilled section to quantify the prior covariance matrix required during Bayesian inversion.     

Combining discrete cosine transform and convolutional neural networks to speed up the Hamiltonian Monte Carlo inversion of pre-stack seismic data

Markov chain Monte Carlo algorithms are commonly employed for accurate uncertainty appraisals in non-linear inverse problems. The downside of these algorithms is the considerable number of samples needed to achieve reliable posterior estimations, especially in high-dimensional model spaces. To overcome this issue, the Hamiltonian Monte Carlo algorithm has recently been introduced to solve geophysical inversions. Different from classical Markov chain Monte Carlo algorithms, this approach exploits the derivative information of the target posterior probability density to guide the sampling of the model space. However, its main downside is the computational cost for the derivative computation (i.e. the computation of the Jacobian matrix around each sampled model). Possible strategies to mitigate this issue are the reduction of the dimensionality of the model space and/or the use of efficient methods to compute the gradient of the target density. Here we focus the attention to the estimation of elastic properties (P-, S-wave velocities and density) from pre-stack data through a non-linear amplitude versus angle inversion in which the Hamiltonian Monte Carlo algorithm is used to sample the posterior probability. To decrease the computational cost of the inversion procedure, we employ the discrete cosine transform to reparametrize the model space, and we train a convolutional neural network to predict the Jacobian matrix around each sampled model. The training data set for the network is also parametrized in the discrete cosine transform space, thus allowing for a reduction of the number of parameters to be optimized during the learning phase. Once trained the network can be used to compute the Jacobian matrix associated with each sampled model in real time. The outcomes of the proposed approach are compared and validated with the predictions of Hamiltonian Monte Carlo inversions in which a quite computationally expensive, but accurate finite-difference scheme is used to compute the Jacobian matrix and with those obtained by replacing the Jacobian with a matrix operator derived from a linear approximation of the Zoeppritz equations. Synthetic and field inversion experiments demonstrate that the proposed approach dramatically reduces the cost of the Hamiltonian Monte Carlo inversion while preserving an accurate and efficient sampling of the posterior probability.     

地震与大地电磁测深数据的自适应正则化同步联合反演

在传统的联合反演研究中,地球物理学者往往更多地关注数据拟合,很少涉及正则化理论.本文在电阻率和速度随机分布的大地电磁测深(MT)与地震联合反演研究的基础之上,将正则化思想引入到同步联合反演中,加入先验信息进行模型约束,选取最小模型为稳定泛函,并首次采用自适应正则化算法来确定联合反演的正则化因子.根据以往研究成果,采用非线性模拟退火方法来实现MT视电阻率或相位与地震走时的同步联合反演.此外,为了验证该算法的有效性,在模型对比试验中设计了4种不同方案.通过模型试验的对比分析,我们认为加入有效模型约束的自适应正则化联合反演,可以有效地提高解的稳定性和计算效率,并能在一定程度上解决不同地球物理数据加权系数人为选取问题,模型试验结果也表明了自适应正则化联合反演优于MT单独反演.     

Quasi-2D hybrid joint inversion of seismic and geoelectric data

Many joint inversion schemes use 1D forward modelling in the integrated interpretation of various geophysical data. In extending the joint inversion approach to the investigation of 2D structures, the discretization of the model parameters and the appropriate choice of the forward‐modelling procedure play a very important role. In this paper, a hybrid seismic–geoelectric joint inversion method is proposed for the investigation of 2D near‐surface geological structures. The electric and seismic models are coupled together through the use of common boundaries between the adjacent layers. Assuming a 2D model composed of homogeneous layers with curved boundaries, a fast ray‐tracing algorithm is used for the calculation of refraction seismic traveltime data. In the geoelectric forward modelling, a locally 1D approximation is used. The boundary surfaces are written in the form of series expansion; the inversion algorithms are formulated for the expansion coefficients and the petrophysical parameters as unknowns. Two versions of the inversion method are proposed: in versions A and B, interval‐wise constant functions and Chebyshev polynomials are, respectively, used as basis functions of the series expansion. The versions are tested by means of synthetic and in situ measured data. The tests show that both methods are stable and accurate.     

Quantitative estimation of water storage and residence time in the epikarst with time‐lapse refraction seismic

The hydrodynamic characterization of the epikarst, the shallow part of the unsaturated zone in karstic systems, has always been challenging for geophysical methods. This work investigates the feasibility of coupling time‐lapse refraction seismic data with petrophysical and hydrologic models for the quantitative determination of water storage and residence time at shallow depth in carbonate rocks. The Biot–Gassmann fluid substitution model describing the seismic velocity variations with water saturation at low frequencies needs to be modified for this lithology. I propose to include a saturation‐dependent rock‐frame weakening to take into account water–rock interactions. A Bayesian inversion workflow is presented to estimate the water content from seismic velocities measured at variable saturations. The procedure is tested first with already published laboratory measurements on core samples, and the results show that it is possible to estimate the water content and its uncertainty. The validated procedure is then applied to a time‐lapse seismic study to locate and quantify seasonal water storage at shallow depth along a seismic profile. The residence time of the water in the shallow layers is estimated by coupling the time‐lapse seismic measurements with rainfall chronicles, simple flow equations, and the petrophysical model. The daily water input computed from the chronicles is used to constraint the inversion of seismic velocities for the daily saturation state and the hydrodynamic parameters of the flow model. The workflow is applied to a real monitoring case, and the results show that the average residence time of the water in the epikarst is generally around three months, but it is only 18 days near an infiltration pathway. During the winter season, the residence times are three times shorter in response to the increase in the effective rainfall.     

Three‐dimensional receiver deghosting of seismic streamer data using L1 inversion and redundant extended radon dictionary

In this paper, we propose a novel three‐dimensional receiver deghosting algorithm that is capable of deghosting both horizontal and slanted streamer data in a theoretically consistent manner. Our algorithm honours wave propagation phenomena in a true three‐dimensional sense and frames the three‐dimensional receiver deghosting problem as a Lasso problem. The ultimate goal is to minimise the mismatch between the actual measurements and the simulated wavefield with an L1 constraint applied in the extended Radon space to handle the underdetermined nature of this problem. We successfully demonstrate our algorithm on a modified three‐dimensional EAGE/SEG Overthrust model and a Red Sea marine dataset.     

重震联合中速度-密度耦合研究综述

基于物性参数耦合的多地球物理数据联合反演方法是21世纪初发展起来的新技术,速度-密度耦合约束下的重震联合反演是其重要分支之一.相比于传统的重震资料综合解释,基于速度-密度耦合的重震联合反演能够减少主观因素的干扰,发挥地震和重力数据的互补作用,产生精度和一致性更高的速度-密度模型.结合国内外现状,本文较为全面地介绍了现有的速度-密度耦合方式,并讨论了速度-密度耦合约束下重震联合反演策略和目标函数的构建及求解等相关问题.不同反演策略和耦合方式的适用性不同,没有绝对的优劣之分.根据研究区的实际情况,在合适的速度-密度耦合约束下开展重震联合反演研究和应用是下一步工作的重点.