Ultrahigh-Resolution 3-Dimensional Seismic Imaging of Seeps from the Continental Slope of the Northern Gulf of Mexico: Subsurface, Seafloor and Into the Water Column
By
Brian N. Brookshire Jr., Brandon A. Mattox, Abby E. Parish and Allen G. Burks, Applied Science Group, NCS SubSea


Abstract
Utilizing recently advanced ultrahigh-resolution 3-dimensional (UHR3D) seismic tools we have imaged the seafloor geomorphology and associated subsurface aspects of seep related expulsion features along the continental slope of the northern Gulf of Mexico with unprecedented clarity and continuity.  Over an area of approximately 400 km2, over 50 discrete features were identified and three general seafloor geomorphologies indicative of seep activity including mounds, depressions and bathymetrically complex features were quantitatively characterized.  Moreover, areas of high seafloor reflectivity indicative of mineralization and areas of coherent seismic amplitude anomalies in the near-seafloor water column indicative of active gas expulsion were identified.  In association with these features, shallow source gas accumulations and migration pathways based on salt related stratigraphic uplift and faulting were imaged.  Shallow, bottom simulating reflectors (BSRs) interpreted to be free gas trapped under near seafloor gas hydrate accumulations were very clearly imaged.   
 

Figure 1 - Bathymetry map derived from the UHR3D data with seep feature footprints overlaid

Purpose
The purpose of the ongoing study presented here is to use UHR3D seismic data to characterize the seafloor and subsurface expressions of seep features in the Gulf of Mexico over a large area (hundreds of km2) at very high resolution (on the order of meters).    The scope and resolution of these data have allowed us to quantitatively and qualitatively assess a significantly large number of seep features. 
 
Methods

Seismic Data Acquisition
 
The seismic data were acquired as true 3D using a P-Cable UHR3D receiver spread.  The system is comprised of 18 x 100 m long streamers with a receiver group spacing of 6.25 m and a cross-line streamer spacing of 12.5 m.  Data were collected at the natural bin size of 3.125 x 6.25 m with a shot point spacing of 12.5 m which yields 4 fold of coverage.  Sail lines were spaced at 100 m providing 2 cmp lines of overlap between adjacent swaths.  A 210 in3 GI gun source fired in harmonic mode (~6 bar-m peak to peak) was employed.  The nominal near offset was held at about 80 m (Brookshire Jr, Landers, and Stein 2015). 
 
Seismic Data Processing
 
The seismic data were processed using flow presented below.
 
  • 20 Hz low cut filter
  • Temporal resample to 0.5 ms
  • Statics corrections
  • 2D SRME on common channel/shots
  • Zero phase operator
  • Noise attenuation
  • Regularization
  • Pre-Stack time migration
  • 3D stack
  • Amplitude balancing
 
Seismic Data Interpretation
 
Seismic data were viewed and interpreted using the IHS Kingdom suite of tools.  Data examples and interpretive products presented here include profiles from the 3D seismic cube, interpreted (picked) time horizons, amplitude extractions, and volume calculations.  The interpreted seafloor time horizon was exported and then further analyzed using Global Mapper, ArcGIS and AutoCAD to produce seep feature morphometric statistics and maps.
 
Seep features were identified based on the apparent seafloor morphologic expression as demonstrated in the interpreted, 3.125 x 6.25 m horizontally gridded, seafloor horizon derived from the UHR3D dataset.  The Z component of interpreted seafloor horizon, originally expressed as two-way travel time, was globally converted to depth using a 1500 m per second conversion factor.  The 3-dimensional (3D) surface was slope shaded and features were identified collaboratively by the authors as either mounds, depressions or complex features with the following criteria: the feature must be closed or semi-closed if on an ambient slope; the feature must demonstrate a slope of 5° or greater.  Following this, each feature was examined in more detail and defined based on the 5° degree slope perimeter.  In instances where the 5° slope perimeter was not perfectly continuous (dropping below 5°), a reasonable interpretation of the perimeter was made.  All further measurements of width, footprint area, volume and height were made within this perimeter.  Width was measured at the widest point for each feature.  Height (negative numbers for depth) was calculated as the difference between the highest and lowest point for each feature.  The footprint area of each feature was calculated using Global Mapper.  The cut (positive space) and fill (negative space) volumes for each feature were calculated using Global Mapper.  For Mounds, the cut volume is utilized, and for depressions the fill volume is utilized.  Complex features were not assigned a height or volume due to the relative ambiguity of these measurements resultant from the bathymetric irregularity of these features.  


Results
 
Within the 416.290 km2 interpretation area, we identified 52 discrete seep features with clear morphologic expression at the sea floor.  An overview map of the identified features is presented in Figure 1.  Summary statistics for these features are presented in Table 1.  Plots illustrating the range of morphometrics for the identified features are presented in Figures 2 – 5.  Representative examples of mound and depression feature horizontal and vertical scale are presented in Figures 6 - 7.  Figure 8 is a three level representation of the BSR, seafloor and water column amplitudes associated with a group of seep features.  The associated seismic profile is included and scaled to the horizontal dimensions of the plan view amplitude extractions.  Figure 9 is a blow up of one of the clearest examples of a BSR imaged in the dataset. This BSR simulates the seafloor reasonably well, in spite of the complex bathymetry of the mound, and displays increased dips, most notable on the flanks, relative to the seafloor.  Figure 10 illustrates the exceptionally imaged gas migration pathways associated with one of the mounds identified in the dataset. 

The subsurface expression of each seep feature was reviewed on an individual basis.   Seep features exhibiting subsurface BSR-like anomalies were noted.  BSR’s were identified based on coherency, relative amplitude, polarity reversal from the seafloor and bottom simulation (more apparent in some cases than others). 
 
Table 1 - Summary statistics for the 52 identified features