Direct measurements of shell growth of an unclassified mussel from active hydrothermal vents along the Galápagos Rift reveal growth rates of approxmately 1 centimeter per year for mature specimens. The largest mussel collected (with shell length of 18.4 centimeters) was estimated to be 19 +/- 7 years old at the time of sampling. Recorded growth rates are among the highest documented for deep-sea species.
Objectives/Scope Sediment profile imaging (SPI) technology characterizes in situ physical, geochemical, and biological seafloor features. SPI was required by Mexico’s Agency for Safety, Energy, and Environment in 2017 for environmental baseline surveys (EBS) of oil lease blocks in the southern Gulf of Mexico. Because of its ability to provide information on benthic community health and the distribution of very thin (down to the centimeter scale) layers of deposited materials, SPI technology is highly effective for mapping drill cuttings or drilling muds released around wellheads during exploration or production and documenting their ecological impacts. SPI technology has not been widely used in the oil and gas industry for EBS or other monitoring activities. A primary objective of this work is to improve the transparency and consistency of the SPI data generation and data management process. Methods, Procedures, Process The SPI camera works like an inverted periscope and obtains an undisturbed 21x15-cm cross-sectional image of the upper sediment column. The camera is internally powered and can be deployed rapidly from a standard winch in depths to 4,000 m. Many stations can be sampled in a single day by "pogo-sticking" across a survey area. Sediment grain size, penetration depth, surface boundary roughness, natural and anthropogenic depositional layers, depth of the oxidized surface sediment layer, maximum biogenic mixing depth, and infaunal successional stage can be directly measured at sea or immediately following the cruise. Final SPI data sets can be provided within a few weeks of the survey. Results, Observations, Conclusions Details on the features measured in SPI images and the underlying interpretive paradigms are presented. To standardize the SPI data generation process, Integral Consulting Inc. has developed 1) a semiautomated image analysis platform, and 2) a SPI data-specific database architecture that allows both numerical and non-numerical metrics to be incorporated into a standard database structure. An integrated, software-based SPI analysis platform has been developed that imports image files and metadata and provides a graphical user interface. The software automatically stores the data, which can then be reviewed for quality assurance, plotted, statistically analyzed, and mapped or exported to other platforms (e.g., Esri ArcGIS©) for further evaluation. Image processing algorithms have been developed using a combination of open-source and commercially available software packages (e.g., MATLAB® and OpenCV) to automatically quantify key parameters. Novel/Additive Information SPI technology’s underutilization in the oil and gas industry may be in part due to a lack of standardization in the measurement of basic features in SPI images. A primary objective of this work is to develop a streamlined, standardized, and transparent process for generating and managing SPI data.
A laboratory study has shown that UV fluorescence photography combined with computer image analysis allows the detection and semi quantification of petroleum associated with bulk wet sediments. The threshold detection appears to be ca. 100 ppm. Biogenic mixing of oil-coated particles into the bottom by benthic organisms has been measured with this system. The results of this laboratory research are to be used to modify existing sediment-profile cameras so that this technique can be applied to in situ field reconnaispance mapping of gradients in sediment-assocfated hydrocarbons in the upper 20 cm of the seafloor.
Offshore wind developers obtain extensive geophysical, geotechnical, and habitat data during Site Characterization activities. Integration and delivery of this information to a diverse group of stakeholders and Government agencies is required. We present an integrated benthic habitat mapping approach tailored to regional geology and ground conditions and discuss how various data was utilized to deliver multiple components of the permitting process. Multiple data sets were integrated and presented via a web-based GIS platform to aid delivery, visualization, and communication. Our unified approach to benthic habitat mapping and delivery of products to stakeholders was instrumental in successfully coalescing multiple performers to develop their individual deliverables in a cohesive and rapid manner. This approach reduced risk to schedule and budget, without sacrificing data density or quality. Four annual (2019–2022) benthic surveys were acquired to support Site Characterization and subsequent permitting processes. High-Resolution Geophysical data were collected concomitantly with the 2020 benthic survey data and used to refine subsequent 2021 and 2022 benthic survey designs. Benthic survey data consisted of grab sample tests (grain size), macrofaunal taxonomy, sediment profile and plan view imagery (SPI-PV), video imagery from each grab station, and towed video transects. Acoustic data products were processed and interpreted to create polygons of seafloor sediment coverage over the ASOW study area and ground-truthed with physical sampling, video, and digital still imagery to refine and validate acoustic data into a mappable model of essential fish and benthic habitats. Seafloor morphology and seabed sediment interpretations were coalesced into a benthic habitat model that displayed substrates consisting mostly of mobile sand sheets, with interspersed areas of gravelly sand and discrete patches of gravel. Overlying the substrate model was a range of benthic features and morphologies, including sand ridges, sand waves, megaripples, ripples, areas of depressional marks, hummocky seafloor, interbedded surficial sediments, irregular seafloor, and localized relief features. From these data, classified maps of Coastal Marine Ecological Standard (CMECS) substrates and fish habitats were made. Additional CMECS classification of benthic biotic components were mapped, showing the taxonomic communities that are present in each substrate. Seabed sediment modeling and morphological trends were dynamically studied and compiled into an interpreted and GIS-friendly dataset that enabled rapid online transfer to subject matter experts tasked with quantifying the benthic ecosystem across the development area. The methods and modeling that were produced by expert refinement of geophysical data to reflect the physically observed habitat structures allowed for dynamic minimum mapping unit variability while also isolating and identifying key areas of interest for benthic researchers and regulators. This mapping process led to an efficient and unified approach for all teams, saving project time and expense.
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