Innovative application of full-waveform inversion applied to extended wide-azimuth marine streamer seismic in a complex salt environment

We demonstrated the application of full-waveform inversion (FWI) guided velocity model building to an extended wide-azimuth towed streamer (EWATS) seismic data set in the Gulf of Mexico. Field data were collected over a historically challenging imaging area, colloquially called the “grunge zone” due to the formation of a compressional allosuture emplaced between two colliding salt sheets. These data had a poor subsalt image below the suture with conventional narrow-azimuth data. Additional geologic complexities were observed including high-velocity carbonate carapace near the top of salt and multiple intrasalt sedimentary inclusions. As such, improved seismic imaging was required to plan and execute wells targeting subsalt strata. Significant improvements to the velocity model and subsalt image were evident with wide-azimuth towed streamer and later EWATS data using conventional top-down velocity model building approaches. Then, high-impact improvements were made using EWATS data with an FWI velocity model building workflow; this study represented an early successful application of FWI used to update salt body geometries from streamer seismic data, in which many past applications were limited to improving sedimentary velocities. Later petrophysical data verified the new FWI-derived model, which had significantly increased confidence in the structural and stratigraphic interpretation of subsalt reservoir systems below the grunge zone.

The Wolfspar experience with low-frequency seismic source field data: Motivation, processing, and implications

The promise of fully automatic full-waveform inversion (FWI) — a (seismic) data-driven velocity model building process — has proven elusive in complex geologic settings, with impactful examples using field data unavailable until recently. In 2015, success with FWI at the Atlantis Field in the U.S. Gulf of Mexico demonstrated that semiautomatic velocity model building is possible, but it also raised the question of what more might be possible if seismic data tailor-made for FWI were available (e.g., with increased source-receiver offsets and bespoke low-frequency seismic sources). Motivated by the initial value case for FWI in settings such as the Gulf of Mexico, beginning in 2007 and continuing into 2021 BP designed, built, and field tested Wolfspar, an ultralow-frequency seismic source designed to produce seismic data tailor-made for FWI. A 3D field trial of Wolfspar was conducted over the Mad Dog Field in the Gulf of Mexico in 2017–2018. Low-frequency source (LFS) data were shot on a sparse grid (280 m inline, 2 to 4 km crossline) and recorded into ocean-bottom nodes simultaneously with air gun sources shooting on a conventional dense grid (50 m inline, 50 m crossline). Using the LFS data with FWI to improve the velocity model for imaging produced only incremental uplift in the subsalt image of the reservoir, albeit with image improvements at depths greater than 25,000 ft (approximately 7620 m). To better understand this, reprocessing and further analyses were conducted. We found that (1) the LFS achieved its design signal-to-noise ratio (S/N) goals over its frequency range; (2) the wave-extrapolation and imaging operators built into FWI and migration are very effective at suppressing low-frequency noise, so that densely sampled air gun data with a low S/N can still produce useable model updates with low frequencies; and (3) data density becomes less important at wider offsets. These results may have significant implications for future acquisition designs with low-frequency seismic sources going forward.

Updating Subsurface Image of Khashim Al-Ahmer Gas Field Using the Interpretation for Anisotropic Velocity Model North-Eastern Iraq

This research deals with structural interpretation of Khashim Al-Ahmer Gas Field North-Eastern Iraq in Diyala Province, using the interpretation of inhomogeneous velocity data. The specific target in this field is the gaseous Jeribe reservoir representing the L. Miocene-Tertiary period. A very thick layer of evaporates Al-Fatha Formation is overlap the Jeribe Formation in the gas field and play as a sealed bed and transition zone for faults movement as a thrust fault. The thrust fault with gas content negatively affected the seismic energy, causing a high attenuation below the level of Al-Fatha Formation in the dome of the Khashm Al-Ahmer structure. Using the interval velocities derived from the sonic logs of five surrounding wells that represent the inhomogeneous behavior of the seismic wave velocity within the rock layers, a model of the velocity behavior in the field was built and the extent of the Jeribe gas reservoir was reconstructed according to the new velocities interpretation data.

Earthquake swarm activity in south Gujarat

South Gujarat, a part of western coast of Indian Peninsula started experiencing earth tremors of mild intensity since early February 1986. The shocks were widely felt with rumbling sound in these areas. More than 23000 micro earthquakes have since been recorded tilt December 1988, with a major event, ML=4.6 which occurred on.27 April.1986: In view of the location of multi-purpose projects like Ukai, Damanganga, .Jhuj, Kflia etc the monitoring this activity was Immediately started through a network of seven temporary- microearthquake recording stations. This was followed by various other studies such as geodetic, geomagnatic, radon gas monitoring and temperature measurements 9f hot springs. The Unai and Mola-Amba hot springs situated in this area have indicated the temperature of about 57oC and 37°C respectively against the normal atmospheric temperature of 33o C. The analysis by Hypo- 71 program on IBM computer of India Met. Dep., New Delhi, using a velocity model Koyna region has shown a well concentrated seismic activity over area of 7x 10 km2 and focal depth of 1-15 km. Clear migration of the activity has been observed. The activity which concentrated around Kella dam m early February-April 1986 migrated up to 18km to its south and back again to the religion around Kelia reservoir, by September 1987 with depth of foci progressively becoming shallower towards north .The 'b" value of 1.04 is higher than that of a few tectonic sequences of Peninsular India. The rate of decay of the activity was 0.52 which is rather slow compared to other sequences of the region. Hence, the reactivation of the existing fracturies/lineaments might be responsible or the recent activity. The geomagnetic studies in this area have corroborated tile existence of NW-SE to NNE-SSW trending conductive fractures. The earthquake activity during 1988 is quite low compared to earlier years.

The Seismic Interpretation for (X) Oil Field Depending on 3D Seismic Data of Nearby Oil Field, Southern Iraq

This research focused on using seismic data to review the structure of the (X) Oil Field, located 40 km SW of Basrah, Southern Iraq. The study utilises a 3D seismic survey conducted during 2011-2012, covering the (Y) Oil Field 2 km to the west, and with partial coverage across (X), to map the Top Zubair reflector. Seismic rock properties analysis was conducted on key (X) Oil Field wells and used to tie the Top Zubair reflector on (X) Oil Field. The reflector was mapped within the time domain using DecisionSpace Software, and then converted to depth using a velocity model. The depth structure map was then compared to the original oil water contact (OOWC) across the fields to understand the potential structural closure of the Top Zubair reservoir in both fields.

The perception threshold of the vestibular Coriolis illusion

BACKGROUND: The vestibular Coriolis illusion is a disorienting sensation that results from a transient head rotation about one axis during sustained body rotation about another axis. Although often used in spatial disorientation training for pilots and laboratory studies on motion sickness, little is known about the minimum required rotation rate to produce the illusion. OBJECTIVE: This study determined the perception threshold associated with the Coriolis illusion. METHODS: Nineteen participants performed a standardized pitching head movement during continuous whole-body yaw rotation at rates varying between 5 to 50 deg/s. The participants reported their motion sensation in relation to three hypothesized perception thresholds: 1) any sense of motion, 2) a sense of rotation, and 3) a sense of rotation and its direction (i.e., the factual Coriolis illusion). The corresponding thresholds were estimated from curves fitted by a generalized linear model. RESULTS: On average threshold 1 was significantly lower (8 deg/s) than thresholds 2 and 3. The latter thresholds did not differ from each other and their pooled value was 10 deg/s. CONCLUSIONS: The Coriolis illusion is perceived at yaw rates exceeding 10 deg/s using a pitching head movement with 40 deg amplitude and 55 deg/s peak velocity. Model analysis shows that this corresponds to an internal rotation vector of 6 deg/s. With this vector the Coriolis perception threshold can be predicted for any other head movement.

Building FWI starting model from wells with dynamic time warping and convolutional neural networks

Full waveform inversion (FWI) needs a feasible starting model, because otherwise it might converge to a local minimum and the inversion result might suffer from detrimental artifacts. We built a feasible starting model from wells by applying dynamic time warping (DTW) localized rewarp and convolutional neural network (CNN) methods alternatively. We used the DTW localized rewarp method to extrapolate the velocities at well locations to the non-well locations in the model space. Rewarping is conducted based on the local structural coherence which is extracted from a migration image of an initial infeasible model. The extraction uses the DTW method. The purpose of velocity extrapolation is to provide sufficient training samples to train a CNN, which maps local spatial features on the migration image into the velocity quantities of each layer. We further designed an interactive workflow to reject inaccurate network predictions and to improve CNN prediction accuracy by incorporating the Monte Carlo dropout method. We demonstrated that the proposed method is robust against the kinematic incorrectness in the migration velocity model, and is capable to produce a feasible FWI starting model.

Migration velocity analysis based on focusing diffractions generated using the CRS wavefront attributes: Application to real land data

In land seismic data processing, the prestack time migration (PSTM) image remains the standard imaging output, but a reliable migrated image of the subsurface depends on the accuracy of the migration velocity model. We have adopted two new algorithms for time-domain migration velocity analysis based on wavefield attributes of the common-reflection-surface (CRS) stack method. These attributes, extracted from multicoverage data, were successfully applied to build the velocity model in the depth domain through tomographic inversion of the normal-incidence-point (NIP) wave. However, there is no practical and reliable method for determining an accurate and geologically consistent time-migration velocity model from these CRS attributes. We introduce an interactive method to determine the migration velocity model in the time domain based on the application of NIP wave attributes and the CRS stacking operator for diffractions, to generate synthetic diffractions on the reflection events of the zero-offset (ZO) CRS stacked section. In the ZO data with diffractions, the poststack time migration (post-STM) is applied with a set of constant velocities, and the migration velocities are then selected through a focusing analysis of the simulated diffractions. We also introduce an algorithm to automatically calculate the migration velocity model from the CRS attributes picked for the main reflection events in the ZO data. We determine the precision of our diffraction focusing velocity analysis and the automatic velocity calculation algorithms using two synthetic models. We also applied them to real 2D land data with low quality and low fold to estimate the time-domain migration velocity model. The velocity models obtained through our methods were validated by applying them in the Kirchhoff PSTM of real data, in which the velocity model from the diffraction focusing analysis provided significant improvements in the quality of the migrated image compared to the legacy image and to the migrated image obtained using the automatically calculated velocity model.