Workshop Review: Joint DGG-SEG Scientific Drilling Workshop a success

SEG and the German Geophysical Society (DGG) held their first joint workshop in early March at DGG's 2021 Annual Meeting. The workshop was part of a new cooperative aim between DGG and SEG to promote engagement between the societies, to foster growth in geophysics, and to expand the community of scientists and engineers tackling important geophysical problems. The 2021 workshop theme, “Scientific Drilling,” was chosen because scientific drilling provides access to rocks and fluids in the subsurface that are essential for ground truthing interpretations from geophysical data and geologic interpretation, for providing samples and in-situ data for detailed characterization, and for providing inputs to models. Consequently, the workshop aimed to attract interest across many subfields of geophysics.

Sedapp v2021: a nonlinear diffusion-based forward stratigraphic model for shallow marine environments

The formation of stratigraphy in shallow marine environments has long been an important topic within the geologic community. Although many advances have been made in the field of forward stratigraphic modeling (FSM), there are still some areas that can be improved in the existing models. In this work, the authors present our recent development and application of Sedapp, which is a new nonlinear open-source R code for FSM. This code uses an integrated depth–distance related function as the expression of the transport coefficient to underpin the FSM with more alongshore details. In addition to conventional parameters, a negative-feedback sediment supply rate and a differentiated deposition–erosion ratio were also introduced. All parameters were implemented in a nonlinear manner. Sedapp is a 2DH tool that is also capable of running 1DH scenarios. Two simplified case studies were conducted. The results showed that Sedapp not only assists in geologic interpretation but is also an efficient tool for internal architecture predictions.

Sedapp: a non-linear diffusion-based forward stratigraphic model for shallow marine environments

The formation of stratigraphy in shallow marine environments has long been an important topic within the geologic community. Although many advances have been made in the field of forward stratigraphic modelling (FSM), there are still some shortcomings to the existing models. In this work, the authors present our recent development and application of Sedapp: a new non-linear open-source R code for FSM. This code uses an integrated depth-distance related function as the expression of the transport coefficient to underpin the FSM with more along-shore details. In addition to conventional parameters, a negative-feedback sediment supply rate and a differentiated deposition-erosion ratio were also introduced. All parameters were implemented in a non-linear manner. Sedapp is a 3D (2DH) tool while also capable of 2D (1DH) scenarios. Two simplified case studies were conducted. The results show that Sedapp can not only assist in geologic interpretation, but is also an efficient tool for internal architecture predictions.

High-dimensional co-occurrence matrix: A new tool for 3D seismic target visualization and interpretation

The interpretation of seismic attributes has been developed for more than 40 years, but it still cannot be fully matched with the study of geologic sedimentology. There are two main bottlenecks. One is that almost no attributes can completely characterize amplitudes from a 3D perspective. Another is the influence of wavelets (frequency and phase). Accordingly, a new volumetric attribute extraction technique is presented for solving these two problems as much as possible. A high-dimensional co-occurrence matrix (HCM), as a statistical representation of the spatial structural relationship between data points, can be one of the solutions to extracting 3D attributes. By considering the global spatial distribution, the HCM fixes the directional distortion of the existing co-occurrence matrix methods and effectively suppresses vertical wavelet illusions. By realizing a rapid transformation of seismic data to 3D geologic target visualizations, this method does not rely heavily on structural information such as dip and azimuth and becomes a convenient bridge from seismic to geologic interpretation. We have applied the methodology to channel delineation in a 3D seismic survey acquired in Ordos, China. The results indicate that the attribute volume extracted from HCM expresses the geologic target convincingly and eliminates the illusions caused by the wavelets. The deposition history of the channels could be observed continuously through geologic time.

Least-squares extended reverse time migration with randomly sampled space shifts

Because the velocity errors are inevitable in field data applications, direct implementation of conventional least-squares reverse time migration (LSRTM) would generate defocused migration images. Extending the model domain has the potential to preserve the data information, and reducing the extended model could provide a final image with more continuous subsurface structures for geologic interpretation. However, the computational cost and the memory requirement would be increased significantly compared to conventional LSRTM. To obtain an inversion image with better quality than conventional LSRTM, while maintaining the same computational cost and memory requirement, we have introduced random space shifts in LSRTM. The key point is to perform implicit model extension and immediate model reduction within each iteration of the inversion procedure. To be robust against the random noise during the random sampling process, we formulate the inverse problem based on a correlation objective function. Numerical examples on a simple layered model, the Marmousi model, and the SEAM model demonstrate that even when the bulk velocity errors are up to 10%, we still obtain reasonable results for subsurface geologic interpretation.

Interpolation artifacts as a result of spatial aliasing: A case study of the airborne magnetic data set of southeastern Minas Gerais, Brazil

Linear features at an acute angle with the flight direction are imaged as a series of aligned circular anomalies in the images of Area 15 aeromagnetic survey, which covered part of the Brazilian southeastern region. These features are interpolation artifacts, a recurring problem found in airborne magnetic images that cause problems for qualitative and quantitative geophysical-geologic interpretation. This imaging problem is attributed to spatial aliasing. By running simulations of magnetic data on a synthetic model, we have physically demonstrated that the interpolation artifacts from Area 15 are due to inappropriate survey design. Besides the most common expression of artifacts, we described a geologically noncoherent linear pattern as a new type of artifact. Supported by spectral analyses, we found that the Area 15 aliased spectrum is similar to geologic high-frequency magnetic features, which constitutes a motive for unearthing the correct geophysical signal. Thus, we made use of four techniques for removing the artifacts. The trend enforcement method partially improved the images, whereas the inverse interpolation method was ineffective, apparently because Area 15 data are severely aliased. The constrained coherence diffusion and multitrend gridding methods were able to significantly reduce the presence of artifacts. Despite the high-frequency attenuation, these tools adequately enhanced the magnetic trends and minimized the artifacts. Therefore, the improved images are better suited for reliable geologic interpretation.

Seismic image-guided 3D inversion of marine controlled-source electromagnetic and magnetotelluric data

Geologic interpretation of resistivity models from marine controlled-source electromagnetic (CSEM) and magnetotelluric (MT) data for hydrocarbon exploration and reservoir monitoring can be problematic due to structural complexity and low-resistivity contrasts in sedimentary units typically found in new frontier areas. It is desirable to reconstruct 3D resistivity structures that are consistent with seismic images and geologic expectations of the subsurface to reduce uncertainty in the evaluation of petroleum ventures. Structural similarity is achieved by promoting a cross-gradient constraint between external seismically derived gradient fields and the inversion resistivity model. The gradient fields come from coherency weighted structure tensors computed directly from the seismic volume. Consequently, structural similarity is obtained without the requirement for any horizon interpretation or picking, thus significantly reducing the complexity and effort. We have determined the effectiveness of this approach using CSEM, MT, and seismic data from a structurally complex fold-thrust belt in offshore northwest Borneo.

Estimation and geologic interpretation of regolith chargeability and superparamagnetic susceptibility in airborne electromagnetic data

All available inversion software for airborne electromagnetic (AEM) data can at a minimum fit a nondispersive conductivity model to the observed inductive secondary field responses, whether operating in the time or frequency domain. Quasistatic inductive responses are essentially controlled by the induction number, the product of frequency with conductivity and magnetic permeability. Recent research has permitted the conductivity model to be dispersive, commonly using a single Cole-Cole parameterization of the induced polarization (IP) effect; but this parameterization slows down and destabilizes any inversion, and it does not account for the need for dual or multiple Cole-Cole responses. Little has been published on inverting AEM data affected by frequency-dependent magnetic permeability, or superparamagnetism (SPM), usually characterized by a Chikazumi model. Because the IP and SPM effects are small and are usually only obvious at late delay times, the aim of our research is to determine if these IP and SPM effects can be fitted and stripped from the AEM data after being approximated with simple dispersive models. We are able to successfully automate a thin-sheet model to do this stripping. Stripped data then can be inverted using a nondispersive conductivity model. The IP and SPM parameters fitted independently to each independent measured decay to provide stripping are proven to be spatially coherent, and they are geologically sensible. The results are found to enhance interpretation of the regolith geology, particularly the nature and distribution of transported materials that are not afforded by mapping conductivity/conductance alone.

Estimation of Noise in the In Situ Hyperspectral Data Acquired by Chang’E-4 and Its Effects on Spectral Analysis of Regolith

The Chang’E-4 (CE-4) spacecraft landed successfully on the far side of the Moon on 3 January 2019, and the rover Yutu-2 has explored the lunar surface since then. The visible and near-infrared imaging spectrometer (VNIS) onboard the rover has acquired numerous spectra, providing unprecedented insight into the composition of the lunar surface. However, the noise in these spectral data and its effects on spectral interpretation are not yet assessed. Here we analyzed repeated measurements over the same area at the lunar surface to estimate the signal–noise ratio (SNR) of the VNIS spectra. Using the results, we assessed the effects of noise on the estimation of band centers, band depths, FeO content, optical maturity (OMAT), mineral abundances, and submicroscopic metallic iron (SMFe). The data observed at solar altitudes <20° exhibit low SNR (25 dB), whereas the data acquired at 20°–35° exhibit higher SNR (35–37 dB). We found differences in band centers due to noise to be ~6.2 and up to 28.6 nm for 1 and 2 μm absorption, respectively. We also found that mineral abundances derived using the Hapke model are affected by noise, with maximum standard deviations of 6.3%, 2.4%, and 7.0% for plagioclase, pyroxene, and olivine, respectively. Our results suggest that noise has significant impacts on the CE-4 spectra, which should be considered in the spectral analysis and geologic interpretation of lunar exploration data.