《地球物理勘探》出版了关于地球物理科学的最佳初级研究，因为它适用于地球资源的勘探、评估和开采。该杂志大量借鉴了石油和矿产勘探行业研究人员的贡献，具有非常实用的倾向。尽管该杂志为这些领域的工作人员之间的交流提供了一个有价值的论坛，但它也非常适合学术地球物理学的研究人员。

The journal 'Geophysical Prospecting' publishes high-quality research in the field of geophysical sciences, particularly relevant to the exploration, assessment, and extraction of earth resources. It draws extensively on contributions from researchers in the oil and mineral exploration industries, emphasizing practical applications. While it serves as a valuable forum for communication among professionals in these fields, it is also well-suited for researchers in academic geophysics.

《Geophysical Prospecting》杂志发表关于地球物理科学的高质量研究，特别适用于地球资源的勘探、评估和开采。该杂志广泛吸纳了石油和矿产勘探领域研究人员的贡献，具有很强的实用性。虽然它为这些领域的专业人士提供了一个宝贵的交流平台，但同样也适合学术地球物理学的研究者。

Geophysical Prospecting

ABSTRACT Electrical induced polarisation surveys are used to detect chargeable materials in the earth. For interpretation of time domain electrical‐induced polarisation data a common procedure is to first invert the direct current data (electric current on time) to recover conductivity and then invert the induced polarisation data (current off‐time) to recover chargeability. This direct current‐induced polarisation inversion procedure assumes that the off time data are free of secondary electromagnetic induction effects. To comply with this, early time data are often discarded or not recorded. For mid‐time data, an electromagnetic decoupling technique, which removes electromagnetic induction in the observations, needs to be implemented. Usually, responses from a half‐space or a layered earth are subtracted. Recent capability in three‐dimensional time domain electromagnetic forward modelling and inversion allows to revisit these procedures. In a Time domain electromagnetic‐induced polarisation survey, a high sampling rate allows early time channels of the electromagnetic data to be recorded. The recovery of chargeability then follows a three‐step workflow: (i) invert early time channel time domain electromagnetic data to recover the three‐dimensional conductivity; (ii) use that conductivity to compute the time domain electromagnetic response at later time channels and subtract this fundamental response from the observations to extract the induced polarisation responses, and (iii) invert the induced polarisation responses to recover a three‐dimensional chargeability. This workflow effectively removes electromagnetic induction effects in the observations and produces better chargeability and conductivity models compared with conventional approaches. In a synthetic example involving a gradient array, we show that the conductivity structure obtained from the early time channel data, which are usually discarded, is superior to that obtained from the steady state direct current voltages. This adds a further reason to collect these electromagnetic data.

Seogi Kang

Douglas W. Oldenburg

Time domain electromagnetic‐induced polarisation: extracting more induced polarisation information from grounded source time domain electromagnetic data

时域电磁感应极化：从接地源时域电磁数据中提取更多感应极化信息

ABSTRACT Magnetic surveys for geophysical interpretation will most usefully furnish estimates of the three components of the magnetic field vector. We review methods for obtaining this information based on scalar and tensor magnetic field measurements and point out the advantages of fluxgate vector measurements. Fluxgate vector magnetometers can be powerful instruments in magnetic mapping. The main problems in using fluxgate magnetometers arise from calibration errors and drift but these can be overcome using a quick and simple method of calibration. This method also has the advantage of compensating permanent and induced magnetic fields generated by the airplane. This is illustrated by a new aeromagnetic survey flown in the Vosges area (France). Measurement accuracy is shown to be similar to that obtained with scalar magnetometers. We take advantage of this accuracy to calculate in the Fourier domain other magnetic functions from the total‐field anomaly, in particular, the magnetic gradient tensor is obtained without using any superconducting quantum devices. A similar approach is used to introduce a new magnetic anomaly tensor that is the equivalent of the pseudo‐gravity tensor. Maps presented in the last sections serve as an example to illustrate the various functions, the goal of the paper being to obtain magnetic vector data from the observations without first postulating the detailed nature of the sources.

Marc Munschy

Simon Fleury

Scalar, vector, tensor magnetic anomalies: measurement or computation?

标量、矢量、张量磁异常：测量还是计算？

ABSTRACT In this paper, we present a case study on the use of the normalized source strength (NSS) for interpretation of magnetic and gravity gradient tensors data. This application arises in exploration of nickel, copper and platinum group element (Ni‐Cu‐PGE) deposits in the McFaulds Lake area, Northern Ontario, Canada. In this study, we have used the normalized source strength function derived from recent high resolution aeromagnetic and gravity gradiometry data for locating geological bodies. In our algorithm, we use maxima of the normalized source strength for estimating the horizontal location of the causative body. Then we estimate depth to the source and structural index at that point using the ratio between the normalized source strength and its vertical derivative calculated at two levels; the measurement level and a height h above the measurement level. To discriminate more reliable solutions from spurious ones, we reject solutions with unreasonable estimated structural indices. This method uses an upward continuation filter which reduces the effect of high frequency noise. In the magnetic case, the advantage is that, in general, the normalized magnetic source strength is relatively insensitive to magnetization direction, thus it provides more reliable information than standard techniques when geologic bodies carry remanent magnetization. For dipping gravity sources, the calculated normalized source strength yields a reliable estimate of the source location by peaking right above the top surface. Application of the method on aeromagnetic and gravity gradient tensor data sets from McFaulds Lake area indicates that most of the gravity and magnetic sources are located just beneath a 20 m thick (on average) overburden and delineated magnetic and gravity sources which can be probably approximated by geological contacts and thin dikes, come up to the overburden.

Majid Beiki

Pierre Keating

David A. Clark

Interpretation of magnetic and gravity gradient tensor data using normalized source strength – A case study from McFaulds Lake, Northern Ontario, Canada

利用归一化源强度解释磁场和重力梯度张量数据——以加拿大安大略省北部McFaulds湖为例的研究

Abstract Full‐tensor magnetic gradiometry data have been collected commercially for the last few years. However, to date, there is still no clarity on how to compare these data to scalar total field surveys. Some users display the vertical gradient of the vertical component ( B zz ) and compare that to a first vertical derivative of total field with the caveat that ‘they are similar’. Others compute the length of the measured vector and call that total field. We establish the basic formulas to calculate total field from the tensor components and demonstrate this with a real data example from Thompson, Manitoba, Canada. Another key question is whether full‐tensor interpolation is required to obtain total field from tensor data. We compare the results from using a commercial full‐tensor interpolation algorithm with standard minimum curvature of the tensor components individually and with another open‐source code that uses a radial basis function interpolator on the individual tensor components. All three applications produced a total field grid of superior quality to that calculated from a scalar total field survey available for the area of study.

Hernan Ugalde

Bill Morris

Akshay Kamath

Brian Parsons

Full‐tensor magnetic gradiometry: Comparison with scalar total magnetic intensity, processing and visualization guidelines

全张量磁梯度测量：与标量总磁强度的比较、处理与可视化指南

ABSTRACT Various models have been proposed to link partial gas saturation to seismic attenuation and dispersion, suggesting that the reflection coefficient should be frequency‐dependent in many cases of practical importance. Previous approaches to studying this phenomenon typically have been limited to single‐interface models. Here, we propose a modelling technique that allows us to incorporate frequency‐dependent reflectivity into convolutional modelling. With this modelling framework, seismic data can be synthesised from well logs of velocity, density, porosity, and water saturation. This forward modelling could act as a basis for inversion schemes aimed at recovering gas saturation variations with depth. We present a Bayesian inversion scheme for a simple thin‐layer case and a particular rock physics model and show that, although the method is very sensitive to prior information and constraints, both gas saturation and layer thickness theoretically can be estimated in the case of interfering reflections.

Zhaoyu Jin

Mark Chapman

Xiaoyang Wu

Giorgos Papageorgiou

Estimating gas saturation in a thin layer by using frequency‐dependent amplitude versus offset modelling

利用频率依赖的振幅随偏移距变化模型估算薄层气体饱和度

Abstract Compressive sensing introduces novel perspectives on non‐uniform sampling, leading to substantial reductions in acquisition cost and cycle time compared to current seismic exploration practices. Non‐uniform spatial sampling, achieved through source and/or receiver areal distributions, and non‐uniform temporal sampling, facilitated by simultaneous‐source acquisition schemes, enable compression and/or reduction of seismic data acquisition time and cost. However, acquiring seismic data using compressive sensing may encounter challenges such as an extremely low signal‐to‐noise ratio and the generation of interference noise from adjacent sources. A significant challenge to this innovative approach is to demonstrate the translation of theoretical gains in sampling efficiency into operational efficiency in the field. In this study, we propose a spatial compression scheme based on compressive sensing theory, aiming to obtain an undersampled survey geometry by minimizing the mutual coherence of a spatial sampling operator. Building upon an optimised spatial compression geometry, we subsequently consider temporal compression through a simultaneous‐source acquisition scheme. To address challenges arising from the recorded compressed seismic data in the non‐uniform temporal and spatial domains, such as missing traces and crosstalk noise, we present a joint deblending and reconstruction algorithm. Our proposed algorithm employs the iterative shrinkage‐thresholding method to solve an ℓ 2 – ℓ 1 optimization problem in the frequency–wavenumber–wavenumber ( ω – k x – k y ) domain. Numerical experiments demonstrate that the proposed algorithm produces excellent deblending and reconstruction results, preserving data quality and reliability. These results are compared with non‐blended and uniformly acquired data from the same location illustrating the robustness of the application. This study exemplifies how the theoretical improvements based on compressive sensing principles can significantly impact seismic data acquisition in terms of spatial and temporal sampling efficiency.

Woodon Jeong

Constantinos Tsingas

Mohammed S. Almubarak

Yue Ma

Compressive sensing principles applied in time and space for three‐dimensional land seismic data acquisition and processing

用于三维陆地地震数据采集和处理的时空压缩感知原理

Abstract Spectral decomposition, aiding for direct hydrocarbon detection, generally employs time–frequency analysis methods to characterize the time‐varying frequency contents of the subsurface layers. However, ongoing efforts to improve time–frequency analysis resolution still face limitations, leading to inaccurate spectral decomposition. In this study, a quantum mechanics–based highlight volumes extraction method, which includes the quantum peak amplitude above average volume and the quantum peak frequency volume, is proposed as a novel spectral decomposition method for hydrocarbon detection. Seismic data are transformed into the time–frequency domain using continuous wavelet transform, and then each sample's amplitude spectrum of each trace is projected on a specific basis constructed by the wave functions using the Schröedinger equation. This yields the corresponding projection coefficient for each sample's amplitude spectrum. For each projection coefficient, the quantum peak amplitude above average volume is calculated by subtracting the average amplitude from the maximum amplitude. The quantum peak frequency volume consists of the local frequency points where the quantum peak amplitude is the maximum. Our approach stands out for its ability to indicate strong amplitude anomalies typically associated with the hydrocarbons and precise gas reservoir locations and has also been validated to handle seismic data with low signal‐to‐noise ratio well. Model tests and field data applications show the effectiveness and the advantages of the proposed quantum mechanics–based highlight volumes extraction method. The comparison with the conventional methods illustrates that the proposed quantum mechanics–based highlight volumes extraction method has higher temporal and spatial resolution and is more accurate in detecting the hydrocarbons in the gas reservoir. However, it may require longer computational times compared with the conventional methods. This work aims to complement the current spectral decomposition techniques with a new quantum mechanics–based highlight volumes extraction method.

Ya‐juan Xue

Hong Zhang

Jin‐Qiang Zhang

Xing‐jian Wang

Jun‐xing Cao

Zhe‐ge Liu

Wu Wen

Jia Yang

Dong‐Fang Li

Hydrocarbon detection via quantum mechanics–based highlight volumes extraction

基于量子力学的高亮体积提取烃类检测

Abstract The accuracy of a model obtained by multi‐parameter full‐waveform inversion can be estimated by analysing the sensitivity of the data to perturbations of the model parameters in selected subsurface points. Each perturbation requires the computation of the seismic response in the form of Born scattering data for a typically very large number of shots, making the method time consuming. The computational cost can be significantly reduced by placing sources of different types at the Born scatterer, the point where the subsurface parameters are perturbed. Instead of modelling each shot separately, reciprocity relations provide the wavefields from the shot positions to the scatter point in terms of wavefields from the scatterer to the shot positions. In this way, the Born scattering data from a single point in the isotropic elastic case for a marine acquisition with pressure sources and receivers can be expressed in terms of the wavefields for force and moment tensor sources located at the scatterer and only a small number of forward runs are required. A two‐dimensional example illustrates how the result can be used to determine the Hessian and local relative covariance matrix for the model parameters at the scatterer at the cost of five forward simulations. In three dimensions, that would be nine.

W. A. Mulder

B. N. Kuvshinov

Accelerating target‐oriented multi‐parameter elastic full‐waveform uncertainty estimation by reciprocity

通过互易性加速面向目标的多参数弹性全波形不确定性估计

Abstract Source time‐reversal imaging based on wave equation theory can achieve high‐precision source location in complex geological models. For the time‐reversal imaging method, the imaging condition is critical to the location accuracy and imaging resolution. The most commonly used imaging condition in time‐reversal imaging is the scalar cross correlation imaging condition. However, scalar cross‐correlation imaging condition removes the directional information of the wavefield through modulus operations to avoid the direct dot product of mutually orthogonal P‐ and S‐waves, preventing the imaging condition from leveraging the wavefield propagation direction to suppress imaging artefacts. We previously tackled this issue by substituting the imaging wavefield with the energy current density vectors of the decoupled wavefield, albeit at the cost of increased computational and storage demands. To balance artifact suppression with reduced computational and memory overhead, this work introduces the Poynting and polarization vectors mixed imaging condition. Poynting and polarization vectors mixed imaging condition utilizes the polarization and propagation direction information of the wavefield by directly dot multiplying the undecoupled velocity polarization vector with the Poynting vector, eliminating the need for P‐ and S‐wave decoupling or additional memory. Compared with scalar cross‐correlation imaging condition, this imaging condition can accurately image data with lower signal‐to‐noise ratios. Its performance is generally consistent with previous work but offers higher computational efficiency and lower memory usage. Synthetic data tests on the half‐space model and the three‐dimensional Marmousi model demonstrate the effectiveness of this method in suppressing imaging artefacts, as well as its efficiency and ease of implementation.

Nan Hu

Hao Li

Yunsheng Zhao

Yongming Lu

Tao Lei

Mei He

Xingda Jiang

Wei Zhang

Poynting and polarization vectors mixed imaging condition of source time‐reversal imaging

源时间反演成像的坡印廷矢量与极化矢量混合成像条件

Abstract Seismic inversion, a crucial process in reservoir characterization, gains prominence in overcoming challenges associated with traditional methods, particularly in exploring deeper reservoirs. In this present study, we propose an inversion approach based on modern techniques like sparse layer reflectivity and particle swarm optimization to obtain inverted impedance. The proposed sparse layer reflectivity and particle swarm optimization techniques effectively minimize the error between recorded seismic reflection data and synthetic seismic data. This reduction in error facilitates accurate prediction of subsurface parameters, enabling comprehensive reservoir characterization. The inverted impedance obtained from both methods serves as a foundation for predicting porosity, utilizing a radial basis function neural network across the entire seismic volume. The study identifies a significant porosity zone (&gt;20%) with a lower acoustic impedance of 6000–8500 m/s g cm 3 , interpreted as a sand channel or reservoir zone. This anomaly, between 1045 and 1065 ms two‐way travel time, provides high‐resolution insights into the subsurface. The particle swarm optimization algorithm shows higher correlation results, with 0.98 for impedance and 0.73 for porosity, compared to sparse layer reflectivity's 0.81 for impedance and 0.65 for porosity at well locations. Additionally, particle swarm optimization provides high‐resolution subsurface insights near well location and across a broader spatial range. This suggests particle swarm optimization's superior potential for delivering higher resolution outcomes compared to sparse layer reflectivity.

Ravi Kant

Brijesh Kumar

Ajay P. Singh

G. Hema

S. P. Maurya

Raghav Singh

K. H. Singh

Piyush Sarkar

Enhancing porosity prediction: Integrating seismic inversion utilizing sparse layer reflectivity, and particle swarm optimization with radial basis function neural networks

增强孔隙度预测：综合利用稀疏层反射率的地震反演与粒子群优化径向基函数神经网络

Abbreviation	Geophys. Prospect.
Journal Impact	1.85
Quartiles(Global)	GEOCHEMISTRY & GEOPHYSICS(Q3)

ISSN	0016-8025, 1365-2478
h-index	96

Publication Information	Publisher: John Wiley and Sons Inc，Publishing cycle: Bimonthly，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 1953，Proportion of original research papers: 99.16%，Self Citation Rate:11.10%， Gold OA Rate: 21.37%
Average review cycle	网友分享经验：较慢,6-12周
Average recruitment ratio	网友分享经验：容易

Geophysical Prospecting

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