The Gulf of America Seismic Water Bottom Anomalies project, led by the Bureau of Ocean Energy Management (BOEM), has been mapping and identifying acoustic amplitude anomalies on the seafloor. These anomalies are areas where the acoustic response is significantly different from the surrounding background, indicating potential geological or biological features. The project aims to understand the distribution of natural hydrocarbon seeps, chemosynthetic communities, and coral communities. Over 230,000 square kilometers of seismic data have been interpreted, revealing thousands of anomalies, including high-positive, low-positive/negative, pockmarks, and water-column gas plumes. These findings are crucial for understanding the geological framework of the GOA and the fluid migration pathways beneath the seafloor. The data is collected using 3-D time-migrated seismic surveys, and verified through submersible, ROV, and AUV surveys.
Since 1998, geoscientists at the Bureau of Ocean Energy Management (BOEM) have identified and mapped water bottom (seafloor) acoustic amplitude anomalies in the deep-water Gulf of America (GOA) using 3-D time-migrated seismic surveys. The purpose of this mapping program is to understand the distribution of natural hydrocarbon seeps and related benthic fauna (chemosynthetic and coral communities) in the GOA, and to characterize other seafloor features related to the geological framework of the seafloor. These areas show anomalously high or low acoustic amplitude response relative to typical background, with most areas having overlapping seismic coverage by two or more surveys. These results cover over 230,000 square kilometers of seismic data interpretation.
The Bureau of Ocean Energy Management (BOEM) provides the data for use "as is." BOEM provides this information with the understanding that it is not guaranteed to be accurate, correct, or complete and conclusions drawn from such information are the responsibility of the user. While every effort has been made to ensure the accuracy, correctness and timeliness of materials presented within the limits of the current state of the art, BOEM assumes no responsibility for errors or omissions, nor because of the failure of the data to function on a particular system. This data was developed by the U.S. Government; no other proprietary rights may be attached to them, nor may they be sold to the U.S. Government as part of any procurement of products or services. Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the Bureau of Ocean Energy Management (BOEM) as the source of this information. Please mail GulfPublicInfo@boem.gov to report discrepancies.
Bureau of Ocean Energy Management (BOEM), Office of Resource Evaluation (ORE)
https://www.usa.gov/publicdomain/label/1.0/
| West | -96.783121 | East | -81.749864 |
| North | 29.360338 | South | 24.000286 |
| Maximum (zoomed in) | 1:5,000 |
| Minimum (zoomed out) | 1:20,000,000 |
Bureau of Ocean Energy Management (BOEM), Office of Resource Evaluation (ORE)
Data collected between 1998 and 2021.
https://www.usa.gov/publicdomain/label/1.0/
This data is in the public domain and has no access restrictions.
There are no restrictions; the data is releasable to the public.
The dataset does not include seismic anomalies outside the Gulf of America. Anomalies detected but not confirmed through direct investigation (e.g., submersible, ROV surveys) are excluded. Only anomalies identified using 3-D time-migrated seismic surveys are included. Seismic anomalies are generalized to a scale of 1:10,000. Detailed features such as individual gas chimneys and minor faults are not included. Historical anomalies that have been reclassified or removed are excluded from this dataset.
The dataset comprises seismic anomalies identified in the Gulf of America, using 3-D time-migrated seismic surveys. Anomalies include features such as hydrocarbon seeps, faults, and other subsurface structures exhibiting abnormal acoustic amplitude responses. Primary Sources: Seismic data collected through 3-D time-migrated seismic surveys. Secondary Sources: Geophysical logs, previous scientific literature, and direct investigations (e.g., submersible and ROV surveys) confirming the nature of anomalies. Seismic Data Collection: Uniform methodology for seismic data collection across all survey areas to ensure consistent quality. Data Processing: Standardized processing algorithms applied to the seismic data to maintain uniformity in identifying and characterizing anomalies. Anomaly Identification: Consistent criteria for identifying and categorizing seismic anomalies based on amplitude deviations and geological context. The conceptual model of the dataset is based on known geophysical principles and geological processes relevant to the Gulf of America region. The model consistently applies the same rules and assumptions across the dataset, ensuring that similar seismic responses are interpreted in a similar manner. Periodic validation of the dataset through cross-referencing with direct investigations and previous scientific literature.
The water bottom horizon was mapped over these surveys using hand-interpreted seed-lines and geophysical interpretation software automatic picking function to fill the gaps between. Next, the water bottom’s acoustic amplitude was extracted and displayed in plan view. Boundary polygons were drawn around areas with anomalously high-positive and low-positive amplitudes, as well as negative amplitudes (complete phase-reversal of the water bottom horizon). The amplitude maps were cross-checked with vertical seismic profiles to verify correctness in the auto-picked interpretation. In vertical 3-D seismic profiles beneath most of the amplitude anomalies, blanking and/or visible fluid-migration pathways (e.g., vertical gas “chimneys” and faults) are often visible in the subsurface up to the water bottom. As through December 2016, BOEM, NOAA, industry contractors, and others have confirmed hundreds of the anomalies as hydrocarbon seeps and carbonate hard grounds through utilization of submersible, ROV, AUV, camera sled surveys, piston cores, trawls, and multibeam sonar identifying water column gas plumes.
1. Gather seismic data using techniques like 3D seismic surveys, multicomponent seismic data, and controlled source electromagnetic (CSEM) data. 2. Process the collected seismic data to enhance signal quality and reduce noise. This may involve filtering, deconvolution, and migration techniques. 3. Identify potential seismic anomalies by analyzing the processed data. Look for unusual patterns or features that differ from the surrounding geological formations. 4. Integrate seismic data with other geological and geophysical data, such as well logs and geological maps, to gain a comprehensive understanding of the anomaly. 5. Interpret the integrated data to determine the nature of the anomaly. This may involve distinguishing between different types of anomalies, such as hydrocarbon accumulations, gas hydrates, or geological faults. 6. Validate the interpretation by comparing it with existing well data or conducting additional surveys if necessary.
Unusual features or patterns detected on the Gulf of America seafloor using seismic data. Seismic anomalies are identified by their acoustic amplitude responses, which differ from the typical background response of the water bottom and can be used to indicate various geological and biological features.
Bureau of Ocean Energy Management (BOEM)
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Feature geometry.
Esri
Coordinates defining the features.
The dataset or data layer of water bottom anomalies from which specific geospatial features are extracted.
Bureau of Ocean Energy Management (BOEM)
The water bottom anomaly data layer or dataset from which specific geospatial features are derived.
The designated name or label for a specific water bottom anomaly dataset.
Bureau of Ocean Energy Management (BOEM)
The designated name or label for a specific water bottom anomaly dataset.
A categorical grouping or classification of Water Bottom Anomaly (WBA) type based on specific criteria such as their acoustic amplitude response, origin, or geological characteristics. BOEM uses two classifications for WBAs: 1) Seep-Related and 2) Non-Seep Related.
Bureau of Ocean Energy Management (BOEM)
A categorical grouping or classification of Water Bottom Anomaly (WBA) type based on specific criteria such as their acoustic amplitude response, origin, or geological characteristics. BOEM uses two classifications for WBAs: 1) Seep-Related and 2) Non-Seep Related.
Classification types used to help geoscientists understand the distribution of natural hydrocarbon seeps and other seafloor anomaly features in the Gulf of America.
Bureau of Ocean Energy Management (BOEM)
Classification types used to help geoscientists understand the distribution of natural hydrocarbon seeps and other seafloor anomaly features in the Gulf of America.
A detailed narrative or explanatory notes associated with Water Bottom Anomalies (WBAs). A WBA description provides specific information about the characteristics, origins, and implications of these anomalies, including details about their acoustic properties, spatial distribution, and potential causes. This description helps geoscientists and researchers understand and analyze the nature and significance of the anomalies, ensuring accurate interpretations and effective resource management.
Bureau of Ocean Energy Management (BOEM)
A detailed narrative or explanatory notes associated with Water Bottom Anomalies (WBAs). A WBA description provides specific information about the characteristics, origins, and implications of these anomalies, including details about their acoustic properties, spatial distribution, and potential causes. This description helps geoscientists and researchers understand and analyze the nature and significance of the anomalies, ensuring accurate interpretations and effective resource management.
Internal field
Esri
Internal field
Esri
https://www.usa.gov/publicdomain/label/1.0/
This data is in the public domain and has no access restrictions.
There are no restrictions; the data is releasable to the public.