Subsalt Regions Research Articles

Identifying imaging challenges for 1D and 3D geometric complexity (LG space)

In some situations, it is difficult to image seismic data even when factors such as illumination, anisotropy, and attenuation are resolvable. An often-overlooked but dominant factor affecting imaging is the geometric complexity of subsurface reflectors. In some of these settings, we propose that geometric complexity plays a dominant role in the quality of seismic imaging. This has been documented in subsalt regions with poor image quality where 3D vertical seismic profiles (VSPs) are available. VSPs often demonstrate that there is good illumination below salt, but the complexity of the observed downgoing wave and diffractions cannot be simulated with smooth earth models. We use synthetic examples with high geometric complexity and no other complications to analyze the imaging process: a 2D sediment-salt model with rough salt-top topography, and a 1D model with complex reflectivity. In these models, it is difficult to estimate velocity, and it is challenging to image the data. These synthetic examples are useful to understand the limitations of imaging with smooth models, to create guidelines to identify geometric complexity in field data, and to develop possible mitigations to improve imaging. Further real data examples will be needed to test geometric complexity.

Physics‐reliable frugal local uncertainty analysis for full waveform inversion

AbstractFull waveform inversion stands at the forefront of seismic imaging technologies, pivotal in retrieving high‐resolution subsurface velocity models. Its application is especially profound when imaging complex geologies such as salt bodies, which are regions notoriously challenging, yet essential given their hydrocarbon potential. However, with the power of full waveform inversion comes the intrinsic challenge of estimating the associated uncertainties. Such uncertainties are crucial in understanding the reliability of subsurface models, particularly in terrains like subsalt regions. Addressing this, we advocate for a nuanced approach employing the Stein variational gradient descent algorithm. Through a judicious use of a limited number of velocity model particles and the integration of random field‐based perturbations, our methodology provides a local representation of the uncertainties inherent in full waveform inversion. Our evaluations, based on the Marmousi model, showcase the robustness of the proposed technique. Yet, it is our exploration into salt‐intensive terrains, leveraging data from the Sigsbee 2A synthetic model and the Gulf of Mexico, that emphasizes the method's versatility. Findings indicate pronounced uncertainties along salt boundaries and in the deeper subsalt sediments, contrasting the minimal uncertainties in non‐salt terrains. However, anomalies like salt canyons present unique challenges, potentially due to the interplay of multi‐scattering effects. Emphasizing the scalability and cost‐effectiveness of this approach, we highlight its potential for large‐scale industrial applications in full waveform inversion, while also underscoring the necessity for prudence when integrating these uncertainty insights into subsequent seismic‐driven geological and reservoir modelling.

An efficient local imaging strategy based on illumination analysis with deep learning

We propose a deep-learning-based illumination analysis and efficient local imaging method. Based on the wavefield forward modeling, seismic illumination can intuitively express the energy propagation of direct waves, reflected waves, and transmitted waves, while it requires high calculation costs. We use a series of convolution operations in deep learning to establish the nonlinear relationship between the model and the illuminations to realize single-shot illumination result of the model. Stacking the single shot illumination results obtained by the network prediction can further help determine the target area. For the target area, we use a deep learning method to obtain the low illumination area of the geological model. Each shot has contribution to the low illuminated area; single shot is selected based on the contribution of the shot being greater than the average illuminance, and the low illumination area is imaged by reverse time migration on the selected shot gather. The trained convolutional neural network can help us quickly obtain the single shot illumination result of the model, which is convenient to analyze the energy distribution of various areas of geological model, and do further imaging for target areas. Using part of the shot gathers to image a local area can recover the complex geological structure of the area and improve the efficiency of reverse time migration especially for 3D problems. This method has universal applicability and is suitable for local imaging of various complex models such as subsalt areas and deep regions.

Multipathing in three‐parameter common‐image gathers from reverse‐time migration

ABSTRACTReverse‐time migration gives high‐quality, complete images by using full‐wave extrapolations. It is thus not subject to important limitations of other migrations that are based on high‐frequency or one‐way approximations. The cross‐correlation imaging condition in two‐dimensional pre‐stack reverse‐time migration of common‐source data explicitly sums the product of the (forward‐propagating) source and (backward‐propagating) receiver wavefields over all image times. The primary contribution at any image point travels a minimum‐time path that has only one (specular) reflection, and it usually corresponds to a local maximum amplitude. All other contributions at the same image point are various types of multipaths, including prismatic multi‐arrivals, free‐surface and internal multiples, converted waves, and all crosstalk noise, which are imaged at later times, and potentially create migration artefacts. A solution that facilitates inclusion of correctly imaged, non‐primary arrivals and removal of the related artefacts, is to save the depth versus incident angle slice at each image time (rather than automatically summing them). This results in a three‐parameter (incident angle, depth, and image time) common‐image volume that integrates, into a single unified representation, attributes that were previously computed by separate processes. The volume can be post‐processed by selecting any desired combination of primary and/or multipath data before stacking over image time. Separate images (with or without artifacts) and various projections can then be produced without having to remigrate the data, providing an efficient tool for optimization of migration images. A numerical example for a simple model shows how primary and prismatic multipath contributions merge into a single incident angle versus image time trajectory. A second example, using synthetic data from the Sigsbee2 model, shows that the contributions to subsalt images of primary and multipath (in this case, turning wave) reflections are different. The primary reflections contain most of the information in regions away from the salt, but both primary and multipath data contribute in the subsalt region.

Acquisition aperture correction in the angle domain toward true-reflection reverse time migration

Due to incomplete aperture coverage and complex overburden structures, the migration process cannot provide a true-amplitude image even though a true-amplitude propagator is used. Amplitude compensation based on source-side illumination ignores the aperture effects on the receiver side, and it may fail to recover the true-reflection/scattering strength of a geologic structure from the image. The structural dip largely controls if the wave incident on the structure can be reflected back and received by the acquisition aperture, so it should be taken into account in removing the acquisition effects from the migration image. We derived a dip-angle domain amplitude correctionfrom the resolution theory. The stacked migration image created by reverse time migration was decomposed into common dip images, which were compensated individually by the corresponding amplitude correction factor. Then, we summed up the corrected images to form a final image. To construct the amplitude correction factor, we generated a monofrequency Green’s function at the shot/geophone location and further decomposed it into incident/scattered plane waves. They were combined based on Snell’s law to construct correction factors for different dips. The final amplitude correction factor was formed by visiting all the shot-geophone pairs in the observation system. We devised efficient algorithms to make the amplitude correction more practical. We evaluated two numerical experiments, a five-layer model and the SEG/EAGE salt model, in which the amplitude correction led to a scalar/pressure image with an amplitude better matching the true impedance contrasts of subsurface structures, especially in areas with steep dips and in subsalt regions.

Critical reflection illumination analysis

Poor imaging is frequently observed in many subsalt regions, making the subsalt stratigraphy interpretation and prospect evaluation challenging. We propose a critical reflection illumination analysis to evaluate subsalt illumination in areas where high-velocity contrasts create illumination and imaging shadows. Critical reflection often occurs at the base or flank of salt bodies. If critical reflection occurred, continued iterations of processing and imaging would generate little, if any, improvement in imaging results. Similarly, increasing the offset/azimuth of the acquisition would offer limited or no advantage. We introduce the critical reflection illumination map and illumination rose diagram to efficiently and effectively evaluate the probability of critical reflection for the target. This analysis can help avoid expensive processing, imaging, and acquisition efforts for areas that are in the critical/postcritical reflection regime. Critical reflection illumination analysis can also be applied to other high-velocity contrast scenarios.

3D seismic reverse time migration on GPGPU

Reverse time migration (RTM) is a powerful seismic imaging method for the interpretation of steep-dips and subsalt regions; however, implementation of the RTM method is computationally expensive. In this paper, we present a fast and computationally inexpensive implementation of RTM using a NVIDIA general purpose graphic processing unit (GPGPU) powered with Compute Unified Device Architecture (CUDA). To accomplish this, we introduced a random velocity boundary in the source propagation kernel. By creating a random velocity layer at the left, right, and bottom boundaries, the wave fields that encounter the boundary regions are pseudo-randomized. Reflections off the random layers have minimal coherent correlation in the reverse direction. This process eliminates the need to write the wave fields to a disk, which is important when using a GPU because of the limited bandwidth of the PCI-E that is connected to the CPU and GPU. There are four GPU kernels in the code: shot, receiver, modeling, and imaging. The shot and receiver insertion kernels are simple and are computed using a GPU because the wave fields reside in GPU's memory. The modeling kernel is computed using Micikevicius's tiling method, which uses shared memory to improve bandwidth usage in 2D and 3D finite difference problems. In the imaging kernel, we also use this tiling method. A Tesla C2050 GPU with 4GB memory and 480 stream processing units was used to test the code. The shot and receiver modeling kernel occupancy achieved 85%, and the imaging kernel occupancy was 100%. This means that the code achieved a good level of optimization. A salt model test verified the correct and effective implementation of the GPU RTM code.

Subsalt imaging by target-oriented inversion-based imaging:A 3D field-data example

Reflectivity images obtained by prestack depth migration are often distorted by uneven subsurface illumination, especially in areas with complex geology, such as subsalt regions. We address the problem of uneven illumination in subsalt imaging by posing the reflectivity-imaging problem as a linear inverse problem and solving it in the image domain in a target-oriented fashion. The most computationally intensive part of the image-domain inversion is the explicit computation of the so-called Hessian operator. The Hessian is defined to be the normal operator of the associated modeling/imaging operator, which is a direct measure of the illumination deficiency of the imaging system. We can overcome the cost issue by using the phase-encoding technique in the 3D conical-wave domain for marine streamer acquisitions. We apply the inversion-based imaging methodology to a 3D field data set acquired from the Gulf of Mexico, and we precondition the inversion with nonstationary dip filters, which naturally incorporate interpreted geologic information. Numerical examples demonstrate that imaging by regularized inversion successfully recovers the reflectivities from the effects of uneven illumination, yielding images with more balanced amplitudes and higher spatial resolution.

One-way/one-return boundary-element method and salt internal multiples

Surface-related multiples or internal multiples can produce artifacts in migrated images using one-way wave-equation methods. Salt-body-related internal-multiple removal remains a challenging problem for this approach. To investigate the effects of salt-body-related internal multiples on subsalt imaging, the boundary-element method is implemented in a one-way/one-return scheme to separate the primary transmission/reflection arrivals at the salt boundaries from the internal multiples. Numerical results demonstrate that the proposed method is effective for modeling primary transmission/reflection arrivals through/from irregular interfaces between strong-velocity-contrast media. Internal multiples are obtained through straight subtraction of primary reflection arrivals from full reflected-wave data. The image from prestack depth migration of these pure internal multiples using one-way propagators is compatible with some strong artifacts in the subsalt region from migration of full-wave data using the same one-way propagators. Results suggest that a significant part of artifacts in the subsalt region in the prestack image for the 2D SEG-EAGE salt model using one-way propagators might be caused by salt internal multiples.

Improving sub-salt imaging using 3D basin model derived velocities

The quality of depth imaging is directly related to the accuracy of the underlying velocity model. In most sub-salt settings, lack of angular illumination severely degrades the resolution and accuracy of velocity information derived from the seismic data itself. A standard approach for building a starting velocity model uses more reliable velocity information outboard of salt which is subsequently extrapolated to populate the sub-salt regions. The shortcoming of this method lies in the assumption that the effective stress observed outboard of salt can be extrapolated beneath salt solely as a function of depth below mudline. Velocities derived from basin model effective stress data show excellent large-scale agreement to seismic velocities. 3D basin modeling represents the most rigorous approach for determining sub-salt effective stresses because it accounts for depositional history, sand distribution and connectivity, variable shale properties, timing of salt emplacement – all of which influence the magnitude and distribution of abnormal pore pressure. In the presented study a calibrated present day effective stress cube from a 3D basin model was used to calculate sub-salt velocities for an exploration well in the Central Gulf of Mexico. The comparison between basin modeling derived velocities and the original velocity field showed remarkable differences, particularly in that the former indicated a far more complex sub-salt velocity distribution than the latter. Utilizing basin model sediment velocities to re-migrate the seismic data set resulted in a more detailed image as well as changed source rock geometries. Where the original image showed a deep de-focus at the source rock level, the new geometry would focus hydrocarbons into the identified trap. Based on the results of the subsequently drilled exploration well, it has to be assumed that the re-migrated data, aided by basin modeling derived velocities, provide a more accurate image of the sub-salt geology.