John Etgen’s research while affiliated with BP and other places

To better understand deepwater imaging challenges in the Gulf of Mexico, we constructed a large 3D model based on the complex salt geology of the Garden Banks protraction area. We simulated a regional wide-azimuth (WAZ) streamer survey with offsets of ±8 km inline and ±4 km crossline over this model. Using the true velocity model, reverse time migration of this data set produced a usable subsalt image nearly everywhere. The same synthetic seismic data set was passed to interpreters and geophysicists to process and image as if it were real field data. They did not get to see the true velocity model. Instead they performed conventional "migrate, pick, and flood" top-down velocity-model building, followed by final imaging through their interpreted velocity model. Where the salt was relatively simple, we found that the interpreted velocity model was reasonably accurate. Reverse time migration of the seismic data through these parts of the velocity model produced an image that was imperfect, but still usable for exploration-scale, structural interpretation. Where the salt structure was complex, however, it was sometimes grossly misinterpreted. The ensuing large-scale errors in the interpreted velocity model resulted in an unusable, shattered subsalt image. We next simulated a low-frequency, ocean-bottom-node (OBN) acquisition, with offsets up to 30 km in all azimuths. We started with the imperfect model produced by the interpreters and investigated what it would take for full-waveform inversion (FWI) to successfully find and fix the gross interpretation errors. Initial results suggest this "interpretation followed by FWI" methodology could produce a velocity model capable of generating an adequate subsalt image, but it may require ultrawide offsets (30 km), ultralow frequencies (below 2 Hz), and improved FWI algorithms to do so.

Beginning in 2007 and continuing into 2015 BP designed, built, and field tested Wolfspar®, a full-scale ultra-low-frequency seismic source optimized for full-waveform inversion. Like airguns or marine vibrators, at low frequencies the Wolfspar source declines in amplitude at about 18 dB / octave. However, Wolfspar differs from airguns in that it can tailor its output precisely to the needs of our preferred algorithm for velocity model building, full-waveform inversion (i.e., it is “FWI friendly”). The source also precisely records its radiated wavefield and this information can be used in the modeling step of the inversion algorithm. Although producing much less power than a large airgun array, this new source is more efficient with the energy it produces. Field-testing the source under tow at 4 knots, recording into ocean-bottom sensors, we achieved an excellent signal-to-noise ratio in the deep water Gulf of Mexico at offsets of over 30 km and at frequencies as low as 1.6 Hz despite the significant ambient noise at these frequencies. We expect that lower frequencies will be possible while under tow, but this has not yet been tested. Presentation Date: Monday, October 17, 2016 Start Time: 1:50:00 PM Location: 163/165 Presentation Type: ORAL

The problem of signal and noise separation has been worked on for the last few decades and it still continues to remain very relevant. One way to distinguish signal from noise is on the basis of curvature. Radon transforms enable us to do that by mapping the input data as a function of moveout. In order for the process of signal and noise separation to be effective we require high resolution in the Radon domain. Although we have access to methods that can increase the resolution by imposing sparsity constraints; these methods seldom preserve the amplitude nuances present in real data. In this abstract we propose an algorithm that can deliver sparse high resolution Radon domain representation without compromising the amplitude information. We also share a field data example to demonstrate the effectiveness of the process. Presentation Date: Tuesday, October 18, 2016 Start Time: 9:15:00 AM Location: 142 Presentation Type: ORAL

In an effort to better understand imaging challenges in the deep water Gulf of Mexico, in 2011 we constructed a large 3D model loosely based on the complex salt geology of the Garden Banks protraction area of the deep water GoM. We then simulated a regional WAZ (wide azimuth towed streamer) seismic survey over this model, producing data that on casual inspection could be mistaken for real. We then performed velocity-model building and imaging on this dataset as if it were real. In particular, the team performing the analysis never saw the correct model. For much of the model, especially where the salt was relatively simple, we found that the resulting velocity model was quite accurate, even if lacking in fine detail. Reverse-time migration of the seismic data through these parts of the velocity model produced an imperfect but usable image. In other places the salt structures were misinterpreted, causing large-scale errors in the migration velocity model, which resulted in an unusable, shattered image below the salt. We conclude that traditional velocity-model-building techniques can miss features that occur at too large a scale. Reliably imaging under complex salt in the Gulf of Mexico may require new velocity-model-building methodologies to be developed that are specifically designed to deal with the problem of large velocity heterogeneities.

We use finite-difference (FD) modeling to study the effect of spatial sampling on coherent noise suppression in 3D land seismic surveys. We compute realistic signal and noise wavefields separately and then combine them in various ways to form 3D surveys with variable S/N. We use two types of noise wavefields: source generated and ambient. We measure the S/N level for source-generated noise (SGN) inside the direct-arrival noise cone so that it represents the relative level of signal to scattered noise, and we use S/N levels of 0 dB and -35 dB so that we have both easy and difficult noise problems. We set the level of ambient noise so that the amplitude of the near-offset, direct-arrival, ground-roll is roughly equal to that for the 3D seismic survey sources. We use grid geometries, and we compare a source grid with 25 meter spacing paired with receiver grids having 25, 50, 100, and 200 meter spacings to the reciprocal cases for their relative performance in coherent noise suppression. In the process, we achieve fold levels of 400, 1600, 6400, and 25,600. When the S/N for SGN is high (i.e. the coherent noise is mostly direct-arrival and the scattered noise is no stronger than the signal), either dense sources and sparse receivers or sparse sources and dense receivers yield high quality images. However, as the S/N due to SGN decreases, dense receiver grids become favored. When ambient noise is included, the balance is further shifted in favor of dense receivers. Furthermore, adequate coherent noise suppression for very low S/N requires an increase in the density of the sparser of the two grids.