Elastic full-waveform inversion (EFWI) updates high-resolution model parameters by minimizing the misfit function between the observed and modeled data. EFWI possesses strong nonlinearity and is likely to converge to a local minimum when the inversion begins with inaccurate initial models. Elastic reflection waveform inversion (ERWI) recovers the low-wavenumber components of P- and S-wave velocities

Identifying thinly bedded reservoirs is important in exploration, appraisal, and development. The thin beds that we are referring to are of meter scale or less. Conventional seismic attributes are not able to resolve thin-bed effects. A new frequency-dependent amplitude variation with offset (FAVO) seismic attribute is developed for the prediction of thin beds. It is based on seismic wave scattering

Compared with isotropic media, at least two extra parameters are involved in common P-wave seismic data processing and interpretation for transversely isotropic media. Previous synthetic model testing has shown that it is challenging to estimate anisotropy parameters even using extremely low noise level seismic data from a simple geologic setting. Although theoretically independent, anisotropy parameters

Describing and understanding the basement relief of sedimentary basins is vital for oil and gas exploration. The traditional method to map an interface in each spatial direction is based on 3D modeling of gravity Bouguer anomalies with variable lateral and vertical density contrasts using a priori information derived from other types of geoscience data sets as constraints (e.g., well and/or seismic

In this article, the Editor of Geophysics provides an overview of all technical articles in this issue of the journal.

Evaluating structural uncertainties associated with seismic imaging and target horizons can be of critical importance for decision making related to oil and gas exploration and production. An important breakthrough for industrial applications has been made with the development of industrial approaches to velocity model building. We have developed an extension of these approaches, sampling an equiprobable

Elastic wavefield solutions computed by finite-difference (FD) methods in complex anisotropic media are essential elements of elastic reverse time migration and full-waveform inversion analyses. Cartesian formulations of such solution methods, though, face practical challenges when aiming to represent curved interfaces (including free-surface topography) with rectilinear elements. To forestall such

Seismic prediction of fluid and lithofacies distribution is of great interest to reservoir characterization, geologic model building, and flow unit delineation. Inferring fluids and lithofacies from seismic data under the framework of machine learning is commonly subject to issues of limited features, imbalanced data sets, and spatial constraints. As a consequence, an extreme gradient boosting-based

Characterizing the kinematics of seismic waves in elastic vertical transversely isotropic (VTI) media involves four independent parameters. To reduce the complexity, the acoustic approximation for P-waves reduces the number of required parameters to three by setting the vertical S-wave velocity to zero. However, because only the SV-wave phase velocities parallel or perpendicular to the symmetry axis

Surface-related multiple elimination (SRME) has proven to be a robust surface multiple and primary estimation tool for decades. However, surface-related multiple leakage is still commonly observed in SRME-processed results due to imperfect multiple predictions. Usually, adaptive subtraction cannot fully correct for these effects without primary damage. Local primary-and-multiple orthogonalization (LPMO)

We have described an algorithm to perform automatic dip picking on borehole images. One key element of our method is a statistical validation, based on the a contrario theory, which is used to decide whether each candidate dip is to be accepted or not. Our method also uses a randomized Hough transform, which greatly improves the processing speed, allowing for a real-time detection of dips during image

We have developed an overset-grid algorithm to simplify the difficulty of curvilinear grid (CG) generation and increase the computational efficiency for seismic wavefield modeling by using the finite-difference method in areas with complex surface topography. The overset grid comprises a Cartesian grid block and an approximately orthogonal CG block. The Cartesian grid covers most of the simulation

We have developed a Runge-Kutta discontinuous Galerkin (RKDG) method for solving wave equations in isotropic and anisotropic poroelastic media at low frequencies. First, the 2D Biot’s two-phase equations are transformed into a first-order system with dissipation. Then, the system is discretized by using the discontinuous Galerkin method with a third-order Runge-Kutta time discretization. The numerical

Time-domain seismic forward and inverse modeling for a dissipative medium is a vital research topic for investigating the attenuation structure of the earth. Constant Q, also called the frequency independence of the quality factor, is a common assumption for seismic Q inversion. We have developed first- and second-order nearly constant Q dissipative models of the generalized standard linear solid type

We have developed a true amplitude solution to the seismic imaging problem. We derive a diagonal scaling approach for the normal operator approximation in the curvelet domain. This is based on the theorem that states that curvelets remain approximately invariant under the action of the normal operator. We use curvelets as essential tools for approximation and inversion. We also exploit the theorem

Full-waveform inversion (FWI) suffers from the local minima problem and requires a sufficiently accurate starting model to converge to the correct solution. Wave-equation traveltime inversion (WETI) is an effective tool to retrieve the long-wavelength components of the velocity model. We have developed a joint diving/direct and reflected wave WETI (JDRWETI) method to build P- and S-wave velocity macromodels

Full-waveform inversion (FWI) of 3D wide-azimuth data for elastic orthorhombic media suffers from parameter trade-offs which cannot be overcome without constraining the model-updating procedure. We present an FWI methodology that incorporates geologic constraints to reduce the inversion nonlinearity and increase the resolution of parameter estimation for orthorhombic models. These constraints are obtained

We have developed a workflow for computing the seismic-wave moduli dispersion and attenuation due to squirt flow in a numerical model derived from a micro X-ray computed tomography image of cracked (through thermal treatment) Carrara marble sample. To generate the numerical model, the image is processed, segmented, and meshed. The finite-element method is adopted to solve the linearized, quasistatic

Half-moon events are a special type of microseismic source mechanism that is found at various hydraulic-fracturing sites, but hardly observed in natural seismicity. This event type can be explained either by a vertical slip on a nearly vertical fault plane or by a horizontal slip on a nearly horizontal fault plane. For this, special stress conditions are required, for instance, nearly equal horizontal

Two- and three-dimensional rock-penetrating-radar data were acquired on the wall of a pillar in an underground limestone mine. The objective was to test the ability of radar to image fractures and karst voids and to characterize their geometry, aperture, and fluid content, with the goal of mitigating mining hazards. Strong radar reflections in the field data correlate with fractures and a cave exposed

Borehole acoustic logging plays an important role in inverting the five Thomsen parameters of many formations characterized as a transversely isotropic medium with a vertical axis of symmetry (VTI). In general, these parameters are obtained under certain assumptions, and the formation type defined by the relation of Thomsen parameters is not taken into consideration. We have developed a method to determine

Different versions of the Radon transform (RT) are widely used in seismic data processing to focus the recorded seismic events. Multiple separation, data interpolation, and noise attenuation are some of the RT applications in seismic processing workflows. Unfortunately, conventional RT methods cannot focus events perfectly in the RT domain. This problem arises due to the blurring effects of the source

When modeling wave propagation, truncation of the computational domain to a manageable size requires nonreflecting boundaries. To construct such a boundary condition on one side of a rectangular domain for a finite-difference discretization of the acoustic wave equation in the frequency domain, the domain is extended on that one side to infinity. Constant extrapolation in the direction perpendicular

Seismic wave attenuation caused by subsurface viscoelasticity reduces the quality of migration and the reliability of interpretation. A variety of Q-compensated migration methods have been developed based on the second-order viscoacoustic quasidifferential equations. However, these second-order wave-equation-based methods are difficult to handle with density perturbation and surface topography. In

Full-waveform inversion, a high-resolution seismic imaging method, is known to require sufficiently accurate initial models to converge toward meaningful estimations of the subsurface mechanical properties. This limitation is due to the nonconvexity of the least-squares distance with respect to the kinematic mismatch. We propose a comparison of five misfit functions promoted recently to mitigate this

Full-waveform inversion (FWI) can be applied to time-lapse (4D) seismic data for subsurface reservoir monitoring. However, nonrepeatability (NR) issues can contaminate the data and cause artifacts in the estimation of 4D rock and fluid property changes. Therefore, evaluating and studying the NR effects on the 4D data and FWI results can help, for instance, discriminate inversion artifacts from true

We have adopted a method to understand uncertainty and interpretability of a Bayesian convolutional neural network for detecting 3D channel geobodies in seismic volumes. We measure heteroscedastic aleatoric uncertainty and epistemic uncertainty. Epistemic uncertainty captures the uncertainty of the network parameters, whereas heteroscedastic aleatoric uncertainty accounts for noise in the seismic volumes

The characteristics of P-wave reflection coefficients can be dependent on the properties of the interface separating the two dissimilar poroelastic media. To evaluate the influence of the interface condition, we have developed a general theoretical formulation of seismic reflection and transmission of waves at arbitrary incidence angles in fluid-saturated porous media. The formulation is derived based

Digital rock physics (DRP) is an emerging technique that has rapidly become an indispensable tool to estimate elastic properties. The success of DRP mainly depends on three factors: acquiring a 3D rock structure image, accurately identifying 3D minerals, and using a proper numerical simulation method. Shales present a substantial challenge for DRP owing to their heterogeneous structure, composition

PP-wave azimuthal elastic impedance (EI) data inverted from azimuthal prestack seismic reflection data can be theoretically and practically used for fluid- and fracture-property discrimination in naturally porous and fluid-saturated fractured reservoirs within the exploration seismic frequency band. From the perspective of the low-frequency Biot-Gassmann theory, Russell’s fluid indicator can be stably

We have introduced a passive surface-wave method using seismic ambient noise obtained from dozens of receivers forming spatially unaliased 2D arrays. The method delineates 2D or 3D S-wave velocity (VS) models to depths of several hundreds of meters, without using any sources. Typical data acquisition uses 50–100 vertical-component 2 Hz geophones on the surface with 5–30 m receiver spacing. Cableless

Steel-cased wells used as long electrodes (LEs) in a surface-electric or electromagnetic survey can enhance anomalous signals from deep hydraulic fracturing zones filled by injected fluid. Although recent research has been published on the algorithms designed for the simulation of the effect of casings, feasibility studies on resolving the small-scale fracturing fluid flow from surface data are lacking

The hydrology and geology of the Xinzhou geothermal field in South China and its surrounding area have been well studied. Previous studies have indicated that mantle heat, granite radioactive heat, and partial melting are the likely key thermal sources. However, neither the geometry of the geothermal reservoir nor the groundwater circulation pattern has been fully characterized. Toward that aim, a

Marchenko multiple elimination schemes are able to attenuate all internal multiple reflections in acoustic reflection data. These can be implemented with and without compensation for two-way transmission effects in the resulting primary reflection data set. The methods are fully automated and run without human intervention, but they require the data to be properly sampled and preprocessed. Even when

Mapping and monitoring saltwater intrusion are critical for the sustainable management of groundwater in coastal aquifers around the world. Increasingly, geophysical methods, such as electrical resistivity tomography (ERT), have been used to address these needs. We identify methods for the inversion of ERT data that would most accurately map the location and geometry of an intrusion wedge. This is

Elastic-wave imaging using multicomponent data can provide more useful subsurface information than acoustic-wave imaging, but it is usually algorithmically challenging. We have developed a vector elastic deconvolution migration method for high-resolution imaging of subsurface structures in isotropic and anisotropic elastic media. Our new method uses a vector deconvolution imaging condition based on

We have formulated an inversion approach for near-offset seismic reflection data based on full-waveform inversion (FWI) workflows, in which an element of standard seismic processing takes the place of each of the fundamental components of FWI. A motivation for using reflections in FWI is trying to update the model in deep zones in which the diving waves could not penetrate due to the large-offset limitation

Seismic acoustic impedance inversion plays an important role in subsurface quantitative interpretation. Due to the band-limited property of the seismic record and the discretization of the continuous elastic parameters with a limited sampling interval, the inverse problem suffers from serious ill-posedness. Various regularization methods are introduced into the seismic inversion to make the inversion

Full-waveform inversion (FWI) is popularly used to obtain a high-resolution subsurface velocity model. However, it requires either a good initial velocity model or low-frequency data to mitigate the cycle-skipping issue. Reflection-waveform inversion (RWI) uses a migration/demigration process to retrieve a background model that can be used as a good initial velocity in FWI. The drawback of conventional

Seismic inversion plays a very useful role in the detailed stratigraphic interpretation of migrated seismic volumes by enabling the estimation of reservoir properties over the complete volume. Traditional and machine learning-based seismic inversion workflows are limited to inverting each seismic trace independently of other traces to estimate impedance profiles, leading to lateral discontinuities

Triaxial induction logging tools have been widely applied to formation characterization due to their sensitivity to electric anisotropy. To model triaxial induction logs in multilayered general anisotropic formations, where the anisotropy can be arbitrary, an analytical method is applied to compute the tool responses. For the analytical method, Maxwell’s equations in the spectral domain are written

In electrical exploration techniques, an effective suppression method for Gaussian and impulsive random noise in spread-spectrum induced-polarization (SSIP) data continues to be challenging for conventional denoising methods. Remnant noise influences the complex resistivity spectrum and damages the subsequent interpretation of geophysical surveys. We have developed a hybrid method based on a correlation

Understanding the role of geometric spreading and estimating its effects on seismic wave propagation play an important role in several techniques used in seismic exploration. The spreading can be estimated through dynamic ray tracing or determined from reflection traveltime derivatives. In the latter case, derivatives of nonhyperbolic moveout approximations are often used. We offer an alternative approach

We have developed a stochastic inversion procedure for common-offset ground-penetrating radar (GPR) reflection measurements. Stochastic realizations of subsurface properties that offer an acceptable fit to GPR data are generated via simulated annealing optimization. The realizations are conditioned to borehole porosity measurements available along the GPR profile or equivalent measurements of another

Deep-learning (DL) technology has emerged as a new approach for seismic data interpolation. DL-based methods can automatically learn the mapping between regularly subsampled and complete data from a large training data set. Subsequently, the trained network can be used to directly interpolate new data. Therefore, compared with traditional methods, DL-based methods reduce the manual workload and render

Accurate identification and picking of P- and S-wave arrivals is important in earthquake and exploration seismology. Often, existing algorithms are lacking in automation, multiphase classification and picking, as well as performance accuracy. We have developed a new fully automated four-step workflow for efficient classification and picking of P- and S-wave arrival times on microseismic data sets.

Risk assessment of CO2 storage requires the use of geophysical monitoring techniques to quantify changes in selected reservoir properties such as CO2 saturation, pore pressure, and porosity. Conformance monitoring and the associated decision making rest upon the quantified properties derived from geophysical data, with uncertainty assessment. We have developed a general framework combining seismic

With geophysical surveys evolving from traditional 2D to 3D models, the large volume of data adds challenges to inversion, especially when aiming to resolve complex 3D structures. An iterative forward solver for the controlled-source electromagnetic (CSEM) method requires less memory than that for a direct solver; however, it is not easy to iteratively solve an ill-conditioned linear system of equations

First-arrival traveltime tomography (FATT) is used to delineate shallow velocity structures to identify static effects in oil exploration as well as to characterize the near surface for geotechnical purposes. Because FATT is generally used for land seismic data processing, it becomes necessary to consider irregular topography especially when performing wave-based tomography. However, the standard Cartesian

Detection of the property changes in the reservoir during injection and production is important. However, the detection process is very challenging using surface seismic surveys because these property changes often induce subtle changes in the seismic signals. The quantitative evaluation of the subsurface property obtained by full-waveform inversion allows for better monitoring of these time-lapse

Seismic estimation of the fluid factor and shear modulus plays an important role in reservoir fluid identification and characterization. Various amplitude variation with offset inversion methods have been used to estimate these two parameters, which are generally based on approximate formulations of the Zoeppritz equations. However, the accuracy of these methods is limited because the forward modeling

Coupling factors of sources and receivers vary dramatically due to the strong heterogeneity of the near surface, and they are as important as the model parameters for the inversion success. We have adopted a full-waveform inversion (FWI) scheme that corrects for variable coupling factors while updating the model parameters. A linear inversion is embedded into the scheme to estimate the source and receiver

Amplitude variation with incidence angle (AVA) analysis is an essential tool for discriminating lithology in hydrocarbon reservoirs. Compared to traditional AVA inversion using only compressional wave (P-wave) information, joint AVA inversion using PP and PS seismic data provides better estimation of rock properties (e.g., density, P- and shear wave [S-wave] velocities). Currently, the most used AVA

Elastic full-waveform inversion (FWI) is a powerful tool for high-resolution subsurface multiparameter characterization. However, 3D FWI applied to land data for near-surface applications is particularly challenging because the seismograms are dominated by highly energetic, dispersive, and complex-scattered surface waves (SWs). In these conditions, a successful deterministic FWI scheme requires an

Research on the non-double-couple (NDC) components in an earthquake is important for characterizing true source processes. The moment-tensor (MT) source model is commonly used to study NDC earthquakes. However, MT inversions are still challenging when earthquakes have small magnitudes, especially microearthquakes. The general-dislocation (GD) model specifies the focal mechanism as a shear-tensile slip

Describing hydraulic properties in the subsurface in at least two dimensions is one of the main objectives in hydrogeophysics. However, due to the limited resolution and ambiguity of the individual methods, those images are often blurry. We have developed a methodology to combine two measuring methods, magnetic resonance tomography (MRT) and electrical resistivity tomography (ERT). To this end, we

Quantitative estimation of subsurface water and ice content values is critical for the understanding and modeling of permafrost evolution in alpine regions. Geophysical methods permit the assessment of subsurface conditions in a noninvasive and quasicontinuous manner; in particular, the combination of seismic refraction tomography (SRT) and electrical resistivity tomography (ERT) through a petrophysical

Nondestructive and noninvasive visualization and quantification of dynamic subsurface hydrologic processes are needed. Using a ground-penetrating-radar (GPR) antenna array, time-lapse common-offset gather and common midpoint (CMP) data can be collected by fixing the antenna at a given location when scanning the subsurface. We have determined wetting front depths continuously during a field infiltration

The belowground architecture of the critical zone (CZ) consists of soil and rock in various stages of weathering and wetness that acts as a medium for biological growth, mediates chemical reactions, and controls partitioning of hydrologic fluxes. Hydrogeophysical imaging provides unique insights into the geometries and properties of earth materials that are present in the CZ and beyond the reach of

The seismoelectric method is based on the capacity of seismic waves to generate measurable modifications of the electrical field in porous media. Even though it combines the advantages of seismic and geoelectrical methods, it remains largely underused in hydrogeophysics. Its signal results from an electrokinetic coupling that can be modeled using either the coupling coefficient or the effective excess