WesternGeco

Submarine landslides (slides) are some of the most voluminous sediment gravity-flows on Earth and they dominate the stratigraphic record of many subaqueous basins. The general kinematics and internal structure of slides are relatively well-understood, although the way in which they increase in volume and internally deformed as they evolve, and how these processes relate to the development of their basal (shear) surface, remains largely unknown. We here use three high-resolution 3D seismic surveys (two broadband time-migrated seismic reflection datasets and a depth-migrated volume) from the Angoche Basin, offshore Mozambique to undertake detailed mapping and intra-slide strain analysis of a shallowly buried, large, and thus well-imaged submarine landslide (c. 530 km3). We also provide detailed documentation of the along-strike variations in the structural style and evolution of the toe region, and how these relate to the overall emplacement of the slide. Seismic attribute analysis image several key kinematic indicators, including broadly NW-trending (i.e., flow-parallel) lateral margins, longitudinal shears, and sub-orthogonal shears in the main body of the deposit, and broadly NE-trending (i.e., flow-normal) symmetric pop-up blocks in the toe region. The slide exhibits varying degrees of frontal emergence along strike, displaying a single frontal (toe) wall in the SW to a more complex, stair-step geometry in the NE. Basal grooves are noticeably absent, with a key observation being that contractional structures are locally observed c. 7 km downdip of the present toe wall. Based on the distribution of and cross-cutting relationship between intra-slide structures, we propose an emplacement model involving two distinct phases of deformation; (i) bulk shortening, parallel to the overall SE-directed emplacement direction, accommodated by the formation of NE-trending symmetric pop-up blocks bound by fore-thrusts and back-thrusts; and (ii) the development of NW-trending sinistral shear zones that offsets the earlier formed shortening structures, and which possibly formed due a spatial variations the evolving rock strength as the flow arrested, resulting in intra-slide flow cells. We infer the basal shear surface or zone incrementally propagated downdip ahead of the developing slide mass, with distal contractional structures being the expression of rather cryptic, updip sliding of the entire sediment mass. Our study demonstrates the value of using 3D seismic reflection data to study the structure and emplacement kinematics of slides, and the complex strains that can arise due to temporal and spatial variations in sediment rheology.

We show an integrated reservoir characterization study of a deepwater oil field in the Gulf of Mexico (GOM). Seismic data were acquired in our study area with both NATS and WATS (narrow- and wide-azimuth towed streamer) configurations. Data are of good quality apart from a large void in the WATS dataset, as these data were shot when a platform was in place over the crest of the field. NATS data were shot previously with no obstruction, however the two surveys have different azimuthal and angular coverage. To understand the impact and illumination of each dataset, we undertook a modeling study which supported merging the two datasets. Additionally, a poor data zone exists to the north of the field due to a salt overhang. We performed an extensive post-migration gather conditioning workflow to further improve image fidelity for better fault interpretation and reservoir definition. Additionally, we carried out a seismic rock property modeling study using wells in our study area to determine the expected seismic response of the reservoir. This demonstrated that there is an optimal projection for both lithology and fluid separation, but this separation is difficult to detect seismically. To help identify compartmenting faults across the field, we utilized a machine learning-based approach to quickly help predict the location of the faults. We also trained a probabilistic neural network to predict areas of high net-to-gross reservoir which we correlate to wells within our study area. This study demonstrates integrated applications in imaging, rock properties modeling and seismic interpretation using machine learning methods, where the approaches leveraged here could be used to further aid in reservoir interpretation and characterization elsewhere in the GOM.

Improvements in time-lapse (4D) seismic processing methods provide opportunities to extract additional information from older time-lapse seismic data sets. This new information can help to optimize reservoir production. Four marine streamer time-lapse seismic data sets on the Njord field, offshore mid-Norway, were previously processed in 2007. Reprocessing in 2020 concentrated on better noise and multiple attenuation, improved imaging, and a focused step-by-step workflow to estimate and correct timing variations within and between surveys. The results dramatically improved on the 2007 processing. Gas injection could be tracked in greater detail and previously unidentified 4D signal was interpreted. The new data sets are expected to enhance reservoir understanding and improve future field performance.

In this study, we reveal what can be achieved from modern reprocessing of legacy regional 2D data using modern broadband and depth imaging techniques. We achieve a higher signal-to-noise ratio, improved event continuity and more reliable deeper Cretaceous and Jurassic images. Use of a single 3D velocity model-building method incorporating several 2D seismic lines simultaneously ensures line ties even for 2D regional data. The largest problems encountered were related to the 100 m to 4800 m range of water depths which required a variety of demultiple methods needed to ensure regionally consistent results in the presence of strong 3D effects. We illustrate regional quality control tools used and the removal of some spurious events associated with the original processing flow. We draw attention to some nuances involved in the interpretation of standard difference displays, show the improvements arising from the use of water column function velocities and quantify the additional value of Full Waveform Inversion (FWI) to improved imaging for the project. Improved imaging results will expand understanding of the basins’ geometry and sediment fill and should provide an excellent tool for future industry and academic research in the Irish offshore.

We develop a workflow to invert for primaries from 2D freesurface shallow-water (⇠100m) data with missing near offsets. The workflow is based on closed-loop surface-related multiple elimination. We apply a nearest-neighbor search followed by differential normal moveout to interpolate missing traces in the input data. Interpolation errors result in artifacts in inverted primaries. We use local primary and multiple orthogonalization as a shaping regularization operator to reduce the artifacts associated with missing near offsets. We apply the workflow to a synthetic demonstrating its robustness. When applied to a field data example the workflow yields results similar to adaptive subtraction of a free-surface multiple model generated by a hybrid wave-field extrapolation and surface-related multiple elimination method. Continuity of deeper reflectors is improved. Crosscorrelation with a free-surface multiple model also supports the validity of the workflow.