The northeastern North Carolina coastal system, from False Cape, Virginia, to Cape Lookout, North Carolina, has been studied by a cooperative research program that mapped the Quaternary geologic framework of the estuaries, barrier islands, and inner continental shelf. This information provides a basis to understand the linkage between geologic framework, physical processes, and coastal evolution at time scales from storm events to millennia. The study area attracts significant tourism to its parks and beaches, contains a number of coastal communities, and supports a local fishing industry, all of which are impacted by coastal change. Knowledge derived from this research program can be used to mitigate hazards and facilitate effective management of this dynamic coastal system. This regional mapping project produced spatial datasets of high-resolution geophysical (bathymetry, backscatter intensity, and seismic reflection) and sedimentary (core and grab-sample) data. The high-resolution geophysical data were collected during numerous surveys within the back-barrier estuarine system, along the barrier island complex, in the nearshore, and along the inner continental shelf. Sediment cores were taken on the mainland and along the barrier islands, and both cores and grab samples were taken on the inner shelf. Data collection was a collaborative effort between the U.S. Geological Survey (USGS) and several other institutions including East Carolina University (ECU), the North Carolina Geological Survey, and the Virginia Institute of Marine Science (VIMS). The high-resolution geophysical data of the inner continental shelf were collected during six separate surveys conducted between 1999 and 2004 (four USGS surveys north of Cape Hatteras: 1999-045-FA, 2001-005-FA, 2002-012-FA, 2002-013-FA, and two USGS surveys south of Cape Hatteras: 2003-003-FA and 2004-003-FA) and cover more than 2600 square kilometers of the inner shelf. Single-beam bathymetry data were collected north of Cape Hatteras in 1999 using a Furuno fathometer. Swath bathymetry data were collected on all other inner shelf surveys using a SEA, Ltd. SwathPLUS 234-kHz bathymetric sonar. Chirp seismic data as well as sidescan-sonar data were collected with a Teledyne Benthos (Datasonics) SIS-1000 north of Cape Hatteras along with boomer seismic reflection data (cruises 1999-045-FA, 2001-005-FA, 2002-012-FA and 2002-013-FA). An Edgetech 512i was used to collect chirp seismic data south of Cape Hatteras (cruises 2003-003-FA and 2004-003-FA) along with a Klein 3000 sidescan-sonar system. Sediment samples were collected with a Van Veen grab sampler during four of the USGS surveys (1999-045-FA, 2001-005-FA, 2002-013-FA, and 2004-003-FA). Additional sediment core data along the inner shelf are provided from previously published studies. A cooperative study, between the North Carolina Geological Survey and the Minerals Management Service (MMS cores), collected vibracores along the inner continental shelf offshore of Nags Head, Kill Devils Hills and Kitty Hawk, North Carolina in 1996. The U.S. Army Corps of Engineers collected vibracores along the inner shelf offshore of Dare County in August 1995 (NDC cores) and July-August 1995 (SNL cores). These cores are curated by the North Carolina Geological Survey and were used as part of the ground validation process in this study. Nearshore geophysical and core data were collected by the Virginia Institute of Marine Science. The nearshore is defined here as the region between the 10-m isobath and the shoreline. High-resolution bathymetry, backscatter intensity, and chirp seismic data were collected between June 2002 and May 2004. Vibracore samples were collected in May and July 2005. Shallow subsurface geophysical data were acquired along the Outer Banks barrier islands using a ground-penetrating radar (GPR) system. Data were collected by East Carolina University from 2002 to 2005. Rotasonic cores (OBX cores) from five drilling operations were collected from 2002 to 2006 by the North Carolina Geological Survey as part of the cooperative study with the USGS. These cores are distributed throughout the Outer Banks as well as the mainland. The USGS collected seismic data for the Quaternary section within the Albemarle-Pamlico estuarine system between 2001 and 2004 during six surveys (2001-013-FA, 2002-015-FA, 2003-005-FA, 2003-042-FA, 2004-005-FA, and 2004-006-FA). These surveys used Geopulse Boomer and Knudsen Engineering Limited (KEL) 320BR Chirp systems, except cruise 2003-042-FA, which used an Edgetech 424 Chirp and a boomer system. The study area includes Albemarle Sound and selected tributary estuaries such as the South, Pungo, Alligator, and Pasquotank Rivers; Pamlico Sound and trunk estuaries including the Neuse and Pamlico Rivers; and back-barrier sounds including Currituck, Croatan, Roanoke, Core, and Bogue.

This set of data contains raw and Initially-processed 2D and 3D seismic data from the Utah FORGE study area near Roosevelt Hot Springs. Reprocessed versions of these data can be accessed at the linked submission in the Resources section titled "Reprocessed Seismic Reflection Data." The zipped archives numbered from 1-100 to 1001-1122 contain 3D seismic uncorrelated shot gatherers SEG-Y files. The zipped archives numbered from 1-100C to 1001-1122C contain 3D seismic correlated shot gatherers SEG-Y files. Other data have intuitive names.

The increasing scale and diversity of seismic data, and the growing role of big data in seismology, has raised interest in methods to make data exploration more accessible. This paper presents the use of knowledge graphs (KGs) for representing seismic data and metadata to improve data exploration and analysis, focusing on usability, flexibility, and extensibility. Using constraints derived from domain knowledge in seismology, we define semantic models of seismic station and event information used to construct the KGs. Our approach utilizes the capability of KGs to integrate data across many sources and diverse schema formats. We use schema-diverse, real-world seismic data to construct KGs with millions of nodes, and illustrate potential applications with three big-data examples. Our findings demonstrate the potential of KGs to enhance the efficiency and efficacy of seismological workflows in research and beyond, indicating a promising interdisciplinary future for this technology. Methods The data here consists of, and was collected from:

Station metadata, in StationXML format, acquired from IRIS DMC using the fdsnws-station webservice (https://service.iris.edu/fdsnws/station/1/). Earthquake event data, in NDK format, acquired from the Global Centroid-Moment Tensor (GCMT) catalog webservice (https://www.globalcmt.org) [1,2]. Earthquake event data, in CSV format, acquired from the USGS earthquake catalog webservice (https://doi.org/10.5066/F7MS3QZH) [3].

The format of the data is described in the README. In addition, a complete description of the StationXML, NDK, and USGS file formats can be found at https://www.fdsn.org/xml/station/, https://www.ldeo.columbia.edu/~gcmt/projects/CMT/catalog/allorder.ndk_explained, and https://earthquake.usgs.gov/data/comcat/#event-terms, respectively. Also provided are conversions from NDK and StationXML file formats into JSON format. References: [1] Dziewonski, A. M., Chou, T. A., & Woodhouse, J. H. (1981). Determination of earthquake source parameters from waveform data for studies of global and regional seismicity. Journal of Geophysical Research: Solid Earth, 86(B4), 2825-2852. [2] Ekström, G., Nettles, M., & Dziewoński, A. M. (2012). The global CMT project 2004–2010: Centroid-moment tensors for 13,017 earthquakes. Physics of the Earth and Planetary Interiors, 200, 1-9. [3] U.S. Geological Survey, Earthquake Hazards Program, 2017, Advanced National Seismic System (ANSS) Comprehensive Catalog of Earthquake Events and Products: Various, https://doi.org/10.5066/F7MS3QZH.

Dataset Description

This dataset contains 3D seismic data and corresponding fault labels, stored in .npz format with two keys: - 'seis': Represents the seismic traces, a 3D volume of size 128x128x128. - 'fault': Represents the fault labels, also a 3D volume of size 128x128x128.

The seismic traces represent the subsurface geological structures, while the fault labels provide the ground truth for fault locations in the seismic volume. The dataset is suitable for training, validating, and testing deep learning models, especially 3D convolutional neural networks, for the task of automatic fault detection in seismic data.

Steps for Dataset Creation

The dataset was created following the approach outlined by Xinming Wu in his FaultSeg3D paper (Wu, 2019). The primary steps in creating the dataset are described below:

1. Seismic Data Simulation:

   • The seismic volumes were generated using a synthetic data simulation process, which allows for precise control over fault geometry and other subsurface structures. Synthetic seismic data were chosen because they allow easy labeling of faults and reduce ambiguity in training data.
   • Seismic wave propagation was modeled using methods such as convolution of reflectivity with wavelets. A variety of geological structures, including horizons and faults, were simulated to ensure diversity in fault patterns.

2. Fault Labeling:

   • Fault labels were generated by simulating faults in the synthetic data. The faults were defined based on displacements in the geological layers or through other structural variations. Each voxel in the seismic volume is assigned a binary label (0 or 1) depending on whether it belongs to a fault or not.
   • In the 'fault' label volume, 1 indicates the presence of a fault, and 0 indicates no fault.

3. 3D Convolutional Neural Network Preparation:

   • The dataset was preprocessed for use in 3D convolutional neural networks (CNNs), which require input data with uniform dimensions and structures. To facilitate this, the seismic data and corresponding fault labels were cropped or padded to the size 128x128x128 to maintain consistency across all examples.
   • Seismic traces were normalized to have values in a specific range, typically between -1 and 1, to ensure stable neural network training.

4. Saving the Dataset:

   • The processed seismic traces and fault labels were saved in an .npz file format with two keys, 'seis' for the seismic volume and 'fault' for the fault labels. This format is efficient for loading into Python-based deep learning frameworks like TensorFlow or PyTorch.
   • Both the seismic traces and fault labels have the same size (128x128x128) to ensure compatibility with the input/output structure of the 3D CNN models used for fault detection.

Citation

The dataset and its creation methodology are based on the approach introduced in the following paper:

Xinming Wu, "FaultSeg3D: Using Synthetic Seismic Data to Train an End-to-End Convolutional Neural Network for 3D Seismic Fault Detection," Geophysics, 2019.

Snapshot img

North America Seismic Survey Market Size 2024-2028

The north america seismic survey market size is forecast to increase by USD 2.34 billion at a CAGR of 4.46% between 2023 and 2028.

The market is experiencing significant growth due to the increase in deepwater and ultra-deepwater Exploration and Production (E and P) projects. This trend is driven by the vast potential of these waters for oil and gas reserves. Additionally, there is a growing shift towards advanced technologies such as Artificial Intelligence (AI) and machine learning for interpreting seismic data. These technologies enable more accurate and efficient analysis of large datasets. However, the market faces challenges from environmental scrutiny and regulatory hurdles associated with seismic surveys. Stringent regulations and increasing public awareness of the potential environmental impact of seismic surveys may hinder market growth.Despite these challenges, the market is expected to continue expanding due to the high demand for accurate geological data for E and P projects. The integration of advanced technologies is also expected to mitigate the environmental concerns and improve the overall efficiency of seismic surveys.

What will be the size of the North America Seismic Survey Market during the forecast period?

Request Free Sample

The North American seismic survey market is a dynamic and evolving industry, driven by the ongoing pursuit of hydrocarbon resources, particularly unconventional ones. Seismic surveys play a crucial role in exploration and production, providing valuable subsurface data for reservoir monitoring, optimization, and hydrocarbon recovery. Technological advancements continue to shape the market, with high-performance computing, broadband seismic sensors, and advanced imaging algorithms enhancing imaging resolution and interpretation capabilities. Despite these innovations, market competition remains fierce, with smaller companies vying for market share. Exploration budgets and project delays pose challenges, necessitating cost-effective and efficient seismic services. Environmental regulations, permitting requirements, indigenous land rights, and seismic protection concerns add complexity to the market.Seismic protection devices, earthquake-resistant structures, and sensors, streamers, and data processing software are essential components of the industry's response to these challenges. Ultimately, the market is characterized by its commitment to safety, innovation, and the responsible exploration and production of hydrocarbon resources.

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. TypeData acquisitionData processingData interpretationEnd-userOilgasOthersGeographyNorth AmericaCanadaMexicoUS

By Type Insights

The data acquisition segment is estimated to witness significant growth during the forecast period.

The market is driven by the data acquisition segment, which focuses on gathering subsurface data for geological analysis and interpretation. Technological innovations, including high-resolution 3D and 4D seismic imaging, have revolutionized seismic survey technology. Advanced imaging algorithms, broadband seismic sensors, and high-performance computing facilitate more accurate and detailed subsurface data. This data is essential for the oil and gas industry, which uses it extensively for exploration and production activities. As energy demand continues to rise, the need for precise data to locate and assess potential hydrocarbon reservoirs drives market growth. Additionally, the expansion of renewable energy projects, such as offshore wind farms and geothermal energy, requires subsurface site characterization and geotechnical assessments, further fueling market demand.Seismic survey services, including processing, interpretation, permitting requirements, and seismic protection devices, are integral components of the data acquisition process. Ensuring the protection of human life, property, and the environment during seismic events is a critical priority. Seismic survey equipment, including sensors, streamers, and data processing software, are continually evolving to meet the industry's demands for subsurface insights.

Get a glance at the market share of various segments Request Free Sample

The Data acquisition segment was valued at USD 4.02 billion in 2018 and showed a gradual increase during the forecast period.

Market Dynamics

Our researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

What are the key market drivers leading to the rise

In 2008, the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), in cooperation with the U.S. Army Corps of Engineers conducted a geophysical and sampling survey of the riverbed of the Upper St. Clair River between Port Huron, MI, and Sarnia, Ontario, Canada. The objectives were to define the Quaternary geologic framework of the St. Clair River to evaluate the relationship between morphologic change of the riverbed and underlying stratigraphy. This report presents the geophysical and sample data collected from the St. Clair River, May 29-June 6, 2008 as part of the International Upper Great Lakes Study, a 5-year project funded by the International Joint Commission of the United States and Canada to examine whether physical changes in the St. Clair River are affecting water levels within the upper Great Lakes, to assess regulation plans for outflows from Lake Superior, and to examine the potential effect of climate change on the Great Lakes water levels ( http://www.iugls.org). This document makes available the data that were used in a separate report, U.S. Geological Survey Open-File Report 2009-1137, which detailed the interpretations of the Quaternary geologic framework of the region. This report includes a description of the suite of high-resolution acoustic and sediment-sampling systems that were used to map the morphology, surficial sediment distribution, and underlying geology of the Upper St. Clair River during USGS field activity 2008-016-FA . Video and photographs of the riverbed were also collected and are included in this data release. Future analyses will be focused on substrate erosion and its effects on river-channel morphology and geometry. Ultimately, the International Upper Great Lakes Study will attempt to determine where physical changes in the St. Clair River affect water flow and, subsequently, water levels in the Upper Great Lakes.

Abstract

The increasing scale and diversity of seismic data, and the growing role of big data in seismology, has raised interest in methods to make data exploration more accessible. This paper presents the use of knowledge graphs (KGs) for representing seismic data and metadata to improve data exploration and analysis, focusing on usability, flexibility, and extensibility. Using constraints derived from domain knowledge in seismology, we define semantic models of seismic station and event information used to construct the KGs. Our approach utilizes the capability of KGs to integrate data across many sources and diverse schema formats. We use schema-diverse, real-world seismic data to construct KGs with millions of nodes, and illustrate potential applications with three big-data examples. Our findings demonstrate the potential of KGs to enhance the efficiency and efficacy of seismological workflows in research and beyond, indicating a promising interdisciplinary future for this technology.

Methods

The data here consists of, and was collected from:

Station metadata, in StationXML format, acquired from IRIS DMC using the fdsnws-station webservice (https://service.iris.edu/fdsnws/station/1/).

Earthquake event data, in NDK format, acquired from the Global Centroid-Moment Tensor (GCMT) catalog webservice (https://www.globalcmt.org) [1,2].

Earthquake event data, in CSV format, acquired from the Northern California Seismic Network (NCSN) catalog using the NCEDC's Northern California Earthquake Catalog Search webservice (doi.org/10.7932/NCEDC) [3].

Earthquake event data, in CSV format, acquired from the USGS earthquake catalog webservice (doi.org/10.5066/F7MS3QZH) [4].

A complete description of the StationXML file format can be found at https://www.fdsn.org/xml/station/.

A complete description of the NDK file format can be found at https://www.ldeo.columbia.edu/~gcmt/projects/CMT/catalog/allorder.ndk_explained.

A complete description of the NCEDC file format can be found at https://ncedc.org/pub/doc/cat1/catlist.txt.

A complete description of the USGS file format can be found at https://earthquake.usgs.gov/data/comcat/#event-terms.

Also provided are conversions from NDK and StationXML file formats into JSON format.

Usage Notes

No special programs or software is reqired to open the data files included here.

References

[1] Dziewonski, A. M., Chou, T. A., & Woodhouse, J. H. (1981). Determination of earthquake source parameters from waveform data for studies of global and regional seismicity. Journal of Geophysical Research: Solid Earth, 86(B4), 2825-2852.

[2] Ekström, G., Nettles, M., & Dziewoński, A. M. (2012). The global CMT project 2004–2010: Centroid-moment tensors for 13,017 earthquakes. Physics of the Earth and Planetary Interiors, 200, 1-9.

[3] NCEDC (2014), Northern California Earthquake Data Center. UC Berkeley Seismological Laboratory. Dataset. doi:10.7932/NCEDC.

[4] U.S. Geological Survey, Earthquake Hazards Program, 2017, Advanced National Seismic System (ANSS) Comprehensive Catalog of Earthquake Events and Products: Various, https://doi.org/10.5066/F7MS3QZH.

The northeastern North Carolina coastal system, from False Cape, Virginia, to Cape Lookout, North Carolina, has been studied by a cooperative research program that mapped the Quaternary geologic framework of the estuaries, barrier islands, and inner continental shelf. This information provides a basis to understand the linkage between geologic framework, physical processes, and coastal evolution at time scales from storm events to millennia. The study area attracts significant tourism to its parks and beaches, contains a number of coastal communities, and supports a local fishing industry, all of which are impacted by coastal change. Knowledge derived from this research program can be used to mitigate hazards and facilitate effective management of this dynamic coastal system. This regional mapping project produced spatial datasets of high-resolution geophysical (bathymetry, backscatter intensity, and seismic reflection) and sedimentary (core and grab-sample) data. The high-resolution geophysical data were collected during numerous surveys within the back-barrier estuarine system, along the barrier island complex, in the nearshore, and along the inner continental shelf. Sediment cores were taken on the mainland and along the barrier islands, and both cores and grab samples were taken on the inner shelf. Data collection was a collaborative effort between the U.S. Geological Survey (USGS) and several other institutions including East Carolina University (ECU), the North Carolina Geological Survey, and the Virginia Institute of Marine Science (VIMS). The high-resolution geophysical data of the inner continental shelf were collected during six separate surveys conducted between 1999 and 2004 (four USGS surveys north of Cape Hatteras: 1999-045-FA, 2001-005-FA, 2002-012-FA, 2002-013-FA, and two USGS surveys south of Cape Hatteras: 2003-003-FA and 2004-003-FA) and cover more than 2600 square kilometers of the inner shelf. Single-beam bathymetry data were collected north of Cape Hatteras in 1999 using a Furuno fathometer. Swath bathymetry data were collected on all other inner shelf surveys using a SEA, Ltd. SwathPLUS 234-kHz bathymetric sonar. Chirp seismic data as well as sidescan-sonar data were collected with a Teledyne Benthos (Datasonics) SIS-1000 north of Cape Hatteras along with boomer seismic reflection data (cruises 1999-045-FA, 2001-005-FA, 2002-012-FA and 2002-013-FA). An Edgetech 512i was used to collect chirp seismic data south of Cape Hatteras (cruises 2003-003-FA and 2004-003-FA) along with a Klein 3000 sidescan-sonar system. Sediment samples were collected with a Van Veen grab sampler during four of the USGS surveys (1999-045-FA, 2001-005-FA, 2002-013-FA, and 2004-003-FA). Additional sediment core data along the inner shelf are provided from previously published studies. A cooperative study, between the North Carolina Geological Survey and the Minerals Management Service (MMS cores), collected vibracores along the inner continental shelf offshore of Nags Head, Kill Devils Hills and Kitty Hawk, North Carolina in 1996. The U.S. Army Corps of Engineers collected vibracores along the inner shelf offshore of Dare County in August 1995 (NDC cores) and July-August 1995 (SNL cores). These cores are curated by the North Carolina Geological Survey and were used as part of the ground validation process in this study. Nearshore geophysical and core data were collected by the Virginia Institute of Marine Science. The nearshore is defined here as the region between the 10-m isobath and the shoreline. High-resolution bathymetry, backscatter intensity, and chirp seismic data were collected between June 2002 and May 2004. Vibracore samples were collected in May and July 2005. Shallow subsurface geophysical data were acquired along the Outer Banks barrier islands using a ground-penetrating radar (GPR) system. Data were collected by East Carolina University from 2002 to 2005. Rotasonic cores (OBX cores) from five drilling operations were collected from 2002 to 2006 by the North Carolina Geological Survey as part of the cooperative study with the USGS. These cores are distributed throughout the Outer Banks as well as the mainland. The USGS collected seismic data for the Quaternary section within the Albemarle-Pamlico estuarine system between 2001 and 2004 during six surveys (2001-013-FA, 2002-015-FA, 2003-005-FA, 2003-042-FA, 2004-005-FA, and 2004-006-FA). These surveys used Geopulse Boomer and Knudsen Engineering Limited (KEL) 320BR Chirp systems, except cruise 2003-042-FA, which used an Edgetech 424 Chirp and a boomer system. The study area includes Albemarle Sound and selected tributary estuaries such as the South, Pungo, Alligator, and Pasquotank Rivers; Pamlico Sound and trunk estuaries including the Neuse and Pamlico Rivers; and back-barrier sounds including Currituck, Croatan, Roanoke, Core, and Bogue.

The dataset contains active source seismic data recorded by 35 ocean bottom seismometers (OBS) in the equatorial Atlantic ocean. It is acquired during the ILAB-SPARC experiment conducted aboard the French R/V 'Pourquoi Pas?' in Fall 2018 as part of TransAtlanticILAB ERC project. The seismic data sample the oceanic lithosphere in a ridge perpendicular E-W profile.

This repository contains the example seismic data used in our manuscript, serving as supplementary materials for demonstrating our cross-domain transfer learning framework for seismic interpretation.The following publicly available datasets are referenced in the manuscript:Netherlands F3 BlockThe Netherlands F3 block dataset is a widely used benchmark dataset in seismic interpretation studies. It can be downloaded from Zenodo:https://zenodo.org/records/1471548(Referenced in: Alaudah et al., 2019; Silva et al., 2019)Teapot Dome Seismic DatasetThe Teapot Dome 3D seismic dataset is provided by the Society of Exploration Geophysicists (SEG), as described in Chiaramonte et al. (2008). Access information is available through SEG’s data portal.Parihaka 3D Seismic DatasetThe Parihaka 3D seismic dataset is publicly available and can be downloaded from the SEG Wiki:https://wiki.seg.org/wiki/Parihaka-3DIf you use the datasets linked above, please cite their original authors and data sources accordingly.

According to Cognitive Market Research, the global seismic services market size was USD XX million in 2024. It will expand at a compound annual growth rate (CAGR) of 6.80% from 2024 to 2031. North America held the major market share for more than 40% of the global revenue with a market size of USD 3340.60 million in 2024 and will grow at a compound annual growth rate (CAGR) of 5.0% from 2024 to 2031. Europe accounted for a market share of over 30% of the global revenue with a market size of USD 2505.45 million. Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 1920.85 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.8% from 2024 to 2031. Latin America had a market share of more than 5% of the global revenue with a market size of USD 417.58 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.2% from 2024 to 2031. Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 167.03 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.5% from 2024 to 2031. The offshore held the highest seismic services market revenue share in 2024. Market Dynamics of Seismic Services Market Key Drivers for Seismic Services Market Growing Exploration Activities in Previously Under-Explored Regions to Increase the Demand Globally Growing exploration activities in previously under-explored regions, such as the Arctic and deep-sea areas, significantly boost the seismic services market. As companies seek new resources in these challenging environments, advanced seismic surveys are crucial for mapping subsurface structures and assessing geological conditions. These regions often present complex geological formations and environmental conditions, increasing the demand for sophisticated seismic technology to ensure accurate data and minimize exploration risks. This expansion drives the need for specialized seismic services to support safe and efficient resource extraction and infrastructure development. Technological Advancements in Seismic Data Acquisition and Analysis to Propel Market Growth Technological advancements in seismic data acquisition and analysis have significantly enhanced the seismic services market. Innovations include advanced sensors, high-resolution imaging, and real-time data processing, which improve accuracy and efficiency in subsurface mapping. Enhanced data integration and big data analytics allow for more precise assessments and faster decision-making. These advancements drive demand across industries like oil and gas, infrastructure, and environmental studies, as they enable more effective exploration, risk assessment, and regulatory compliance. As technology evolves, the market for seismic services continues to expand. Restraint Factor for the Seismic Services Market High Initial Investment to Limit the Sales High initial investment is a significant restraint in the seismic services market. The costs involved in acquiring advanced seismic equipment, deploying specialized personnel, and conducting extensive surveys are substantial. This financial burden can deter smaller companies and limit market entry, particularly in emerging regions. Additionally, high upfront costs can lead to extended payback periods, affecting profitability and investment attractiveness. As a result, only well-capitalized firms can afford to undertake comprehensive seismic projects, potentially stifling market growth and innovation. Impact of Covid-19 on the Seismic Services Market The COVID-19 pandemic temporarily disrupted the seismic services market due to restrictions on fieldwork, supply chain interruptions, and reduced exploration activities. Lockdowns and travel bans delayed seismic surveys and data processing, while economic uncertainties led to decreased investment in new projects. As a result, companies faced project delays and revenue losses. However, as the pandemic subsided, recovery efforts and a renewed focus on energy security and infrastructure development helped drive the market's rebound. Introduction of the Seismic Services Market Seismic services involve the collection, processing, and analysis of seismic data to map subsurface structures, assess geological conditions, and support exploration, construction, and environmental assessments. The continuous development of geothermal and other renewable energy sources is boosting the seismic services market ...

In September 2021, the U.S. Geological Survey acquired high-resolution P- and S-wave data near seismic station CE.57213 in Fremont, California, approximately 100 m east of the mapped trace of the Hayward Fault. We acquired the seismic data to evaluate the time-averaged shear-wave velocity in the upper 30 m (VS30) and to better understand ground-shaking near the station CE.57213. The seismic data were acquired using a linear array of SmartSolo 3-component nodal seismometers (nodes), which continuously recorded at 2000 samples per second (0.5-ms sampling rate). We deployed 60 nodes, spaced at 2-m increments, along a 180-m-long, northeast-southwest-trending linear array. We generated P-wave seismic sources (shots) adjacent to each node at a 1-m offset using a 3.5-kg sledgehammer to vertically strike a steel plate on the ground surface. S-wave sources (shots) were generated adjacent to each node by horizontally striking an aluminum block with a 3.5-kg sledgehammer. For each shot poin ...

This dataset contains ground motion velocity and acceleration seismic waveforms recorded by the Southern California Seismic Network (SCSN) and archived at the Southern California Earthquake Data Center (SCEDC). A Distributed Acousting Sensing (DAS) dataset is included.

This is 2D and 3D seismic reflection data from Utah FORGE reprocessed during Phase 2c. The readme file containing an explanation of the data including data formats, software that can be used, processing, and projection and datum used. The Reprocessing document gives the rationale for reprocessing and shows examples of the improvements that were obtained. For all 3D and 2D data the following datasets were created and output in SEG-Y format: - Unmigrated Time - Prestack Time Migration (PSTM), Unenhanced (UnEnh) and Enhanced (Enh) - Prestack Depth Migration (PSDM), Unenhanced (UnEnh) and Enhanced (Enh) - Velocity Model used for Migration

Repurposing the fiber-optic cables from the existing telecommunication infrastructure makes it possible to record dense continuous seismic data in urban areas at low cost. From 2016 to 2019, we connected a disctributed acoustic sensing (DAS) interrogator unit to the fiber-optic cables in telecommunication conduits under Stanford University campus, recording years of continuous seismic data.

This repository contains processed TensorFlow Record data files containing examples of earthquake and background noise signals recorded by the Stanford fiber-optic DAS array. These data were used for training, evaluation, and testing of a convolutional neural network for earthquake detection.

A two-week field operation was conducted in the John Day Reservoir on the Columbia River to image the floor of the pool, to measure the distribution and thickness of post-impoundment sediment, and to verify these geophysical data with video photography and bottom sediment samples. The field program was a cooperative effort between the USGS Coastal and Marine Geology Team of the Geologic Division and the USGS Columbia River Research Laboratory of the Biological Resources Division. The data collection was completed aboard the R/V ESTERO during September 13-27, 2000. The interest in sediment accumulation in the reservoir was two-fold. First, it was unknown how effective this reservoir was as a sediment trap to material that otherwise would have been transported down-river to the estuary and eventually to the ocean. The recent erosion of beaches along the Washington coast has been attributed to a decreased contribution of sediment from the Columbia River to the coastal system due to t ...

This dataset contains various types of digital data relating to earthquakes in central and northern California. Time series data come from broadband, short period, and strong motion seismic sensors, GPS, and other geophysical sensors.

Dataset of acceleration signals acquired from a low-cost Wireless Sensor Network (WSN) during seismic events occurred in Central Italy. The WSN consists of 5 low-cost sensor nodes, each embedding an ADXL355 tri-axial MEMS accelerometer with a fixed sampling frequency of 250 Hz. Continuous data was acquired from February 2023 to the end of June 2023. The continuous data was then trimmed around the origin time of seismic events that occurred near the installation site, close to the city of Pollenza (MC), Italy, during the acquisition period. A total of 67 events were selected from the Italian Istituto Nazionale di Geofisica e Vulcanologia (INGV) Seismology data center. The waveform data was then further analyzed and annotated by analysts from INGV. Annotations include a pick time for the S and P wave, and an uncertainty level for the annotations.

The data consists of two datasets, one containing earthquake traces, the other containing noise-only traces. There are two folders: the dataset_earthquakes folder contains seismic traces; the dataset_noise folder contains noise-only traces.

The earthquake dataset consists of 328 3x25001 arrays, each related to a seismic event and with its own metadata. The dataset follows the Seisbench format, in which each trace follows the convention 'bucket0$trace_number;:n_dimensions;:n_samples', where 'bucket0' indicates the block to which the trace belongs; 'trace_number' indicates the trace' index within the block; 'n_dimensions' denotes the number of measurement axes; and 'n_samples' represents the number of samples in the trace. The waveforms are included in the the waveforms.hdf5 file of the earthquake_dataset folder, while the metadata is in the metadata.csv file in the folder. For each trace in the waveforms.hdf5 file there is an associated row in the metadata.csv file at the same index (indicated by 'trace_number' in the trace name).

The original miniSEED files that were analyzed by the INGV analysts are made available. They are contained in the miniseed_files folder. Each file name follows the format '_eventID_originTime_WS.POZA.Sx.DNy.MSEED' where eventID is the ID of the event that is recorded in the trace, originTime is the origin of the event in UTC time (expressed with the YYYY-MM-DDThh:mm:ss.ssssss format), x is a number that is used to identify the sensor that recorded the trace, y indicates the measurement direction of that trace, named '1', '2', 'Z'. For each trace in the waveforms.hdf5 file, the name of the miniSEED files that comprise the trace are in the metadata row for that trace, under the ‘trace_name_original_1’, ‘trace_name_original_2’, and ‘trace_name_original_Z’ fields in the metadata.csv file.

The dataset_noise folder follows the same convention. It contains a waveforms.hdf5 file with waveforms without seismic activity. The metadata_csv file has the metadata associated to each noise trace. The miniSEED_files_noise folder contains the original miniSEED files of the noise traces.

The northeastern North Carolina coastal system, from False Cape, Virginia, to Cape Lookout, North Carolina, has been studied by a cooperative research program that mapped the Quaternary geologic framework of the estuaries, barrier islands, and inner continental shelf. This information provides a basis to understand the linkage between geologic framework, physical processes, and coastal evolution at time scales from storm events to millennia. The study area attracts significant tourism to its parks and beaches, contains a number of coastal communities, and supports a local fishing industry, all of which are impacted by coastal change. Knowledge derived from this research program can be used to mitigate hazards and facilitate effective management of this dynamic coastal system. This regional mapping project produced spatial datasets of high-resolution geophysical (bathymetry, backscatter intensity, and seismic reflection) and sedimentary (core and grab-sample) data. The high-resolution geophysical data were collected during numerous surveys within the back-barrier estuarine system, along the barrier island complex, in the nearshore, and along the inner continental shelf. Sediment cores were taken on the mainland and along the barrier islands, and both cores and grab samples were taken on the inner shelf. Data collection was a collaborative effort between the U.S. Geological Survey (USGS) and several other institutions including East Carolina University (ECU), the North Carolina Geological Survey, and the Virginia Institute of Marine Science (VIMS). The high-resolution geophysical data of the inner continental shelf were collected during six separate surveys conducted between 1999 and 2004 (four USGS surveys north of Cape Hatteras: 1999-045-FA, 2001-005-FA, 2002-012-FA, 2002-013-FA, and two USGS surveys south of Cape Hatteras: 2003-003-FA and 2004-003-FA) and cover more than 2600 square kilometers of the inner shelf. Single-beam bathymetry data were collected north of Cape Hatteras in 1999 using a Furuno fathometer. Swath bathymetry data were collected on all other inner shelf surveys using a SEA, Ltd. SwathPLUS 234-kHz bathymetric sonar. Chirp seismic data as well as sidescan-sonar data were collected with a Teledyne Benthos (Datasonics) SIS-1000 north of Cape Hatteras along with boomer seismic reflection data (cruises 1999-045-FA, 2001-005-FA, 2002-012-FA and 2002-013-FA). An Edgetech 512i was used to collect chirp seismic data south of Cape Hatteras (cruises 2003-003-FA and 2004-003-FA) along with a Klein 3000 sidescan-sonar system. Sediment samples were collected with a Van Veen grab sampler during four of the USGS surveys (1999-045-FA, 2001-005-FA, 2002-013-FA, and 2004-003-FA). Additional sediment core data along the inner shelf are provided from previously published studies. A cooperative study, between the North Carolina Geological Survey and the Minerals Management Service (MMS cores), collected vibracores along the inner continental shelf offshore of Nags Head, Kill Devils Hills and Kitty Hawk, North Carolina in 1996. The U.S. Army Corps of Engineers collected vibracores along the inner shelf offshore of Dare County in August 1995 (NDC cores) and July-August 1995 (SNL cores). These cores are curated by the North Carolina Geological Survey and were used as part of the ground validation process in this study. Nearshore geophysical and core data were collected by the Virginia Institute of Marine Science. The nearshore is defined here as the region between the 10-m isobath and the shoreline. High-resolution bathymetry, backscatter intensity, and chirp seismic data were collected between June 2002 and May 2004. Vibracore samples were collected in May and July 2005. Shallow subsurface geophysical data were acquired along the Outer Banks barrier islands using a ground-penetrating radar (GPR) system. Data were collected by East Carolina University from 2002 to 2005. Rotasonic cores (OBX cores) from five drilling operations were collected from 2002 to 2006 by the North Carolina Geological Survey as part of the cooperative study with the USGS. These cores are distributed throughout the Outer Banks as well as the mainland. The USGS collected seismic data for the Quaternary section within the Albemarle-Pamlico estuarine system between 2001 and 2004 during six surveys (2001-013-FA, 2002-015-FA, 2003-005-FA, 2003-042-FA, 2004-005-FA, and 2004-006-FA). These surveys used Geopulse Boomer and Knudsen Engineering Limited (KEL) 320BR Chirp systems, except cruise 2003-042-FA, which used an Edgetech 424 Chirp and a boomer system. The study area includes Albemarle Sound and selected tributary estuaries such as the South, Pungo, Alligator, and Pasquotank Rivers; Pamlico Sound and trunk estuaries including the Neuse and Pamlico Rivers; and back-barrier sounds including Currituck, Croatan, Roanoke, Core, and Bogue.

Geoscience Australia conducted a seismic reflection survey in various localities throughout Tasmania between January and April 1995. This seismic survey formed part of AGSO project `TASGO' (b103201), a National Geoscience MappingAccord (NGMA) project carried out in conjunction with the Tasmanian Geological Survey (within Tasmania Development and Resources). The seismic survey obtained 134 km of 10 to 20 fold common mid-point (CMP) deep reflection seismic data along six traverses over an 8 week acquisition period. In addition, gravityobservations were made by the Tasmanian Geological Survey at 120 m intervals along five of the lines. Statewide aeromagnetic data has been interpolated to provide profiles along eachseismic line, and shot hole cuttings and water samples were taken for later analysis. The reflection crew provided support for AGSO's refraction and tomography data acquisition which is reported separately.