AndreaBozzo/ceres-open-data-index huggingface dataset:
MSEEL Boggess 3H Well Data

Boggess 3H well data from the Marcellus Shale Energy and Environment Laboratory (MSEEL). The resources were downloaded, packaged and uploaded from the MSEEL website https://www.mseel.com/data/.

"The objective of the Marcellus Shale Energy and Environment Laboratory (MSEEL) is to provide a long-term field site to develop and validate new knowledge and technology to improve recovery efficiency and minimize environmental implications of unconventional resource development."

A read me file was created from the data describing the essential information and metadata for the resources included in this submission, and is available for download from this submission. The read me has a file list and directory information describing how the data files are organized and zipped within this submission. 

Tags: Boggess, MSEEL, Marcellus Shale Energy and Environment Laboratory, Oil and Gas Well Data, well data
MSEEL Boggess 1H Well Data

Boggess 1H well data from the  Marcellus Shale Energy and Environment Laboratory (MSEEL). The resources were downloaded, packaged and uploaded from the MSEEL website https://www.mseel.com/data/. 

"The objective of the Marcellus Shale Energy and Environment Laboratory (MSEEL) is to provide a long-term field site to develop and validate new knowledge and technology to improve recovery efficiency and minimize environmental implications of unconventional resource development."

A read me file was created from the data describing the essential information and metadata for the resources included in this submission, and is available for download from this submission. The read me has a file list and directory information describing how the data files were organized and zipped within this submission. 

Tags: DOE field laboratory, MSEEL, Marcellus Shale Energy and Environment Laboratory, Oil and Gas Well Data, Well data
MSEEL Reports, Presentations, and other documents

Text documents including environmental reports, presentations, and other reports, associated with the Marcellus Shale Energy and Environment Laboratory, including environmental reports, presentations, and project reports and documents. The resources were downloaded, packaged and uploaded from the MSEEL website https://www.mseel.com/data/. 
"The objective of the Marcellus Shale Energy and Environment Laboratory (MSEEL) is to provide a long-term field site to develop and validate new knowledge and technology to improve recovery efficiency and minimize environmental implications of unconventional resource development."

A read me was created from the data describing the essential information and metadata for the resources included in this submission, and is available for download from this submission. The read me has a file list and directory information describing how the data files were organized and zipped within this submission. 

Tags: DOE field laboratory, MSEEL, Marcellus Shale, Marcellus Shale Energy and Environment Laboratory, Presentations, Production data, documents, reports
MSEEL Boggess 17H Well Data

Boggess 17H well data from the Marcellus Shale Energy and Environment Laboratory (MSEEL). The resources were downloaded, packaged and uploaded from the MSEEL website https://www.mseel.com/data/.

"The objective of the Marcellus Shale Energy and Environment Laboratory (MSEEL) is to provide a long-term field site to develop and validate new knowledge and technology to improve recovery efficiency and minimize environmental implications of unconventional resource development."

A read me file was created from the data describing metadata for the resources included in this submission, and is available for download from this submission. The read me has a file list and directory information describing how the data files are organized and zipped within this submission.

Tags: Boggess, DOE field laboratory, MSEEL, Marcellus Shale, Marcellus Shale Energy and Environment Laboratory, Oil and Gas Well Data, well data
Electrical resistivity model of Newberry Volcano

Electrical resistivity model of Newberry Volcano in the central Oregon Cascades. Model created by inverting magnetotelluric (MT) data with the ModEM inversion software. All support files used in the inversion are present. Model is centered at 43.7261, -121.3156.

Tags: Electrical Resistivity, Geothermal, Newberry, magma, magnetotellurics, rhyolite
Kimberlina 1.2 Velocity Models and Seismic Data

Kimberlina 1.2 Velocity model and synthetic seismic data, produced in collaboration of teams at the National Energy Technology Laboratory, Los Alamos National Laboratory, and Lawrence Livermore National Laboratory through the National Risk Assessment Partnership. 

Data is associated with the following publication:
Zheng Zhou, Youzuo Lin, Zhongping Zhang, Yue Wu, Zan Wang, Robert Dilmore, and George Guthrie, "A Data-Driven CO2 Leakage Detection Using Seismic Data and Spatial-Temporal Densely Connected Convolutional Neural Networks," International Journal of Greenhouse Gas Control, Vol 90, 2019.

The Kimberlina 1.2 Velocity models were produced by Zan Wang, Robert Dilmore, William Harbert, and Lianjie Huang at NETL. The following citations are directly related to the creation of the velocity models:

Wang, Z.  Harbert, W., Dilmore, R., Huang, L. Modeling of time-lapse seismic monitoring using CO2 leakage simulations for a model CO2 storage site with realistic geology: Application in assessment of early leak-detection capabilities.  International Journal of Greenhouse Gas Control. V. 76, September 2018, Pages 39-52. https://doi.org/10.1016/j.ijggc.2018.06.011
Wang, Z., Dilmore, R., Harbert, W. Inferring CO2 saturation from synthetic surface seismic and downhole monitoring data using machine learning for leakage detection at CO2 sequestration sites. International Journal of Greenhouse Gas Control, V. 100, September 2020. https://doi.org/10.1016/j.ijggc.2020.103115

The velocity models were built based on the Kimberlina 1.2 aquifer impact data which is associated with the following publications:

Buscheck, T.A., Mansoor, K., Yang, X., Wainwright, H., and Carroll, S. (2019). Downhole pressure and chemical monitoring for CO2 and brine leak detection in aquifers above a CO2 storage reservoir. International Journal of Greenhouse Gas Control. 91. 102812. 10.1016/j.ijggc.2019.102812. 
Xianjin Yang, Thomas A. Buscheck, Kayyum Mansoor, Zan Wang, Kai Gao, Lianjie Huang, Delphine Appriou, Susan A. Carroll, Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, Volume 90, 2019, 102803, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2019.102803

The synthetic seismic data was produced by Youzuo Lin and team at LANL, and are associated with the following citations:

Jordan, P. D., and J. L. Wagoner. Characterizing Construction of Existing Wells to a CO2 Storage Target: The Kimberlina Site, California.
Zheng Zhou, Youzuo Lin, Zhongping Zhang, Yue Wu, Zan Wang, Robert Dilmore, and George Guthrie, "A Data-Driven CO2 Leakage Detection Using Seismic Data and Spatial-Temporal Densely Connected Convolutional Neural Networks," International Journal of Greenhouse Gas Control, Vol 90, 2019.

Tags: CO2 Leakage, Kimberlina, Kimberlina 1.2, Reservoir Modeling, model, seismic, synthetic seismic, velocity model
Simple Chemistry Runs

Simple Chemistry Runs.  512 runs compressed into 20 folders of 25 runs each.  These simulation results were used to develop the geochemistry scaling function for the carbonate aquifer ROM used in the Aquifer Impact Model and the Phase I Integrated Assessment Model.

The data is associated with the following resources:

Bacon, D. H., Z. Dai and L. Zheng (2014). "Geochemical Impacts of Carbon Dioxide, Brine, Trace Metal and Organic Leakage into an Unconfined, Oxidizing Limestone Aquifer." Energy Procedia 63: 4684-4707.

Bacon, D. H.; Keating, E. H.; Dai, Z.; Harp, D. R.; Pawar, R. J. Reduced-Order Model for the Impacts of Carbon Dioxide and Brine Leakage into an Unconfined, Oxidizing Carbonate Aquifer, Third-Generation; NRAP-TRS-III-010-2017; NRAP Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2017; p 76. DOI: 10.18141/1433153.

Tags: Chemistry, Edwards Aquifer, Integrated Assessment, NRAP-Open-IAM, Runs, Simple
Simulation and Plant Data for Fault Detection Validation Study of an AI Learning System

The data asset contains two parts: 1) simulation data from GE Steam Power’s dynamic boiler simulator based on a reference boiler design; 2) plant data from Southern Company collected from a boiler feed water pump. The data are generated and/or gathered under the DOE program (DE-FE0031763) for the validation study of the DANCE4CFDD AI learning system developed during the program. All the data fields are normalized to preserve confidential or business sensitive information. For more information about the data and the validation study, please refer to the final report (forthcoming).  


Acknowledgment:  "This material is based upon work supported by the Department of Energy, National Energy Technology Laboratory under Award Number DE-FE0031763."
 
Disclaimer:  "This report was prepared as an account of work sponsored by an agency of the United States Government.  Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights.  Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof.  The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof."

Tags: Anomaly Detection, Boiler Dynamic Simulation Model, Coal-Fired Power Plants, Plant Time Series Data
Simulation and Plant Data for Fault Detection Validation Study of DANCE4CFDD AI Learning System

The data asset contains two parts: 1) simulation data from GE Steam Power’s dynamic boiler simulator based on a reference boiler design; 2) plant data from Southern Company collected from a boiler feed water pump. The data are generated and/or gathered under the DOE program (DE-FE0031763) for the validation study of the DANCE4CFDD AI learning system developed during the program. All the data fields are normalized to preserve confidential or business sensitive information. For more information about the data and the validation study, please refer to the final report (forthcoming).  

Acknowledgment:  "This material is based upon work supported by the Department of Energy, National Energy Technology Laboratory under Award Number DE-FE0031763."
 
Disclaimer:  "This report was prepared as an account of work sponsored by an agency of the United States Government.  Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights.  Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof.  The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof."


Tags: Anomaly Detection, Boiler Dynamic Simulation Model, Coal-Fired Power Plants, Plant Time Series Data
Application of NRAP-IAM-CS at Shenhua CO2 Storage Site, China

Key Findings:
Monte Carlo approach looking a uncertainty in system parameters (e.g., geology and well leakage parameters) and impact to groundwater. 
For all but the highest leakage scenarios, leakage was well below the threshold set by the IPCC and proxy indicators of pH and TDS were low. 

NRAP Tools: NRAP-IAM-CS

Location: Ordos Basin, China


![Graphic 1](https://ars.els-cdn.com/content/image/1-s2.0-S175058362100195X-gr17.jpg)
![Graphic 2](https://ars.els-cdn.com/content/image/1-s2.0-S175058362100195X-gr2.jpg)

Tags: CCS, CO2 Brine leakage, CO2 Storage, China, NRAP, Reservoir, Shenhua, modeling
Bedwell 33-52-1-1H Well

Computed tomography data described in the technical report series "Core Characterization of Bakken Shale from the Bedwell 33-52-1-1H Well, Sheridan County, Montana" by 
Cimadomo, D.; Moore, J.; Paronish, T.; Schmitt, R.; Sanguinito, S.; Crandall, D.; Dotson, B. 

Tags: Computed Tomography, Core Logging, Logging
Southeast-PA-Diabase

Computed tomography and high-resolution core log data associated with the technical report "Computed Tomography Scanning and Geophysical Measurements of the Southeastern Pennsylvania Triassic Diabase Core"

Schmitt, R.; Paronish, T.; Crandall, D.; Moore, J.; Neubaum, J.; Andrews, G. "Computed Tomography Scanning and Geophysical Measurements of the Southeastern Pennsylvania Triassic Diabase Core; DOE.NETL-2021.2843; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2021; p 104

Tags: Computed Tomography, Core Characterization, diabase
Computed Tomography Scans of Naturally Mineralized Fractures in Upper Wolfcamp Shale

Computed tomography scans of fractures in small samples of Wolfcamp Shale from the Permian Basin and a depth of approximately 10,400 feet that have been cemented through natural processes. These samples were CT scanned at NETL. The data sets compliment the manuscript by Hajirezaie et al entitled "Mineral characterization of a sealed fracture: A multiscale multimodal imaging study of a syntaxial vein"

Tags: Computed Tomography, Fracture, Mineralization and Cements, Wolfcamp, shale
Micro-CT Imaging and Fluid Flow Simulations of Fractures in MSEEL Shale

micro-CT scans of a naturally fractured MSEEL shale sample as a shear fracture is generated and displaced in the center, intact region of the sample. Steady State laminar fluid flow simulations were then performed on each individual fracture during each experimental segment as effective stress and shear displacement changed. 

Released under LA-UR-21-24335.

Tags: Fractures, Fracturing Initiation, Marcellus Shale
Mid-Atlantic U.S. Offshore Carbon Storage Resource Assessment Project, Carbon Storage Resource Assessment Topical Report

Systematic carbon storage resource assessment of the offshore Mid-Atlantic coastal region from the Georges Bank Basin (GBB) through the Long Island Platform to the southern Baltimore Canyon Trough (BCT). Regional-scale prospective CO2 storage resources have been estimated for three potential deep saline storage zones to establish preliminary, screening-level constraints on the geologic storage resources available in the Mid-Atlantic offshore study region. Results of the regional analysis were used to delineate a selected area for refinement of storage resource estimates via dynamic injection and storage simulation.

Tags: Baltimore Canyon Trough, CO2 storage, Georges Bank Basin, Long Island Platform, Mid-Atlantic, offshore, resource estimate, saline
Mid-Atlantic U.S. Offshore Carbon Storage Resource Assessment Project, Task 6 Risk Factor Analysis Report

This report presents the risk factor analysis for the Mid-Atlantic U.S. Offshore Carbon Storage Resource Assessment Project. The analysis included an initial assessment of technical risk factors in mid-Atlantic offshore areas that may affect CO2 storage resource estimates for the following categories: 1. geologic storage processes, 2. long-term potential for CO2 migration, and 3. environmental setting factors that could influence the development of a carbon storage facility.

Tags: Baltimore Canyon Trough, CO2 leakage, CO2 storage capacity, Georges Bank Basin, Long Island Platform, Mid-Atlantic, offshore, risk
CIAM Climatological Isolation and Attraction Model–Climatological Lagrangian Coherent Structures

Matlab code to compute climatological Lagrangian Coherent Structures. Climatological Lagrangian Coherent Structures have been shown to be effective in identifying regions that persistently attract or isolate trajectories at the sea surface, while also identifying recurrent transport patterns and transport barriers. It is therefore known as the Climatological Isolation and Attraction Model within NETL DoE. 

This repository also includes the information necessary  to replicate the cCLS published in the paper which is freely available at:
https://www.nature.com/articles/s41598-018-23121-y


The method is developed in:
Duran, R., F. J. Beron-Vera, M. J. Olascoaga (2018). Extracting quasi-steady Lagrangian transport patterns from the ocean circulation: An application to the Gulf of Mexico. Scientific Reports, 8(1), 5218. https://www.nature.com/articles/s41598-018-23121-y

The method is successfully evaluated with a large dataset of satellite-tracked drifters, and with a different ocean model in:
Gough M.K., F. J. Beron-Vera, M. J. Olascoaga, J. Sheinbaum, J. Jouenno, R. Duran (2019). Persistent Lagrangian transport patterns in the northwestern Gulf of Mexico. J. Phys. Oceanogr., 49, 353–367, https://doi.org/10.1175/JPO-D-17-0207.1

and with floats and yet a different model in:
Maslo, A., Azevedo Correia de Souza, J. M., Andrade-Canto, F., & Rodríguez Outerelo, J. (2020). Connectivity of deep waters in the Gulf of Mexico. Journal of Marine Systems, 203, 103267. https://doi.org/10.1016/j.jmarsys.2019.103267

Tags: CIAM, LCS, Lagrangian transport, cLCS, dynamical systems, ocean, ocean transport, oil spill, oil transport, planning and response, recurrent trajectories, sea surface
SIMPA

SIMPA (Spatially Integrated Multivariate Probabilistic Assessment) is a Python-based fuzzy logic tool designed to help assess the likelihood of fluid and/or gas migration pathways throughout the subsurface. The SIMPA tool helps users develop and apply fuzzy logic to various datasets to construct knowledge-based inferential rules that reduce uncertainty and results in a visual representation depicting the likelihood of potential fluid and/or gas migration pathways. SIMPA results can offers an understanding of the magnitude and extent of natural and anthropogenic subsurface pathways, offering insight to subsurface hazards to improve storage assessments and critical information for improving industry decisions related to the use of various CCS methods and technologies. In addition, SIMPA can offer new insights for areas with little to no data to help inform site selection and production, evaluate potential risks and hazards, and support various decision making and risk management needs.   

Tags: carbon storage, fluid migration, fuzzy logic, model, simpa, subsurface
Core Analysis E-Reports Produced for the Southwest Regional Partnership on Carbon Sequestration for Wells 13-10A, 13-14, and 32-8 of the Farnsworth Unit, Texas

The submission is three electronic reports (e-reports) produced by Terra Tek, a former Schlumberger company, for and under the oversight of the Southwest Regional Partnership on Carbon Sequestration (SWP). The SWP designed and implemented a coring and core analysis program in conjunction with the previous field operator Chaparral Energy, L.L.C. The main SWP contacts who oversaw the coring and core analysis program, including geologic core descriptions and sample selection for testing by the Terra Tek, are listed below in the Authors section. The three reports are for Wells 13-10A, 13-14, and 32-8 of the Farnsworth Unit, TX, a site of the SWP's CO2 storage and enhanced oil recovery project. The e-reports include many data types that are not listed in full detail here, but may include: geomechanical, geochemical, and petrophysical measurements; white light and UV core photos; spectral gamma logs on the core; and Heterogeneous Rock Analysis logs. Fracture core review reports are included for Wells 13-14 and 32-8.

The three e-reports each have many subfolders with the various types of data in spreadsheets, pdfs, image files, or other formats. The main e-reports for each well are listed by the well name. The sub-folder “E-Report” for each well has a Report.html file, which, when opened, will have hyperlinks to the various data sets and information. The files in the zipped folder will need to be extracted for the Report.html files to work properly.

These authors thank Joseph Hall, a geologist formerly of Chaparral Energy, L.L.C., for assistance in designing the coring program, his geologic expertise of the Farnsworth Unit, and his assistance with characterizing the core. Christopher Gillespie, of Terra Tek at the time, managed the myriad geomechanical, geochemical, and petrophysical measurements provided by Terra Tek for this project. The core from which the samples were collected for this project are housed at the Subsurface Data and Core Libraries of the New Mexico Bureau of Geology and Mineral Resources, Socorro, New Mexico, USA.

Funding for this project is provided by the U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) through the Southwest Regional Partnership on Carbon Sequestration (SWP) under Award No. DE-FC26-05NT42591. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. These e-reports describe objective technical results and analysis. Any subjective views or opinions that might be expressed in the reports do not necessarily represent the views of the US Department of Energy or the United States Government. 



Tags: Caprock, Core Analysis, Oil Reservoirs, Permeability, Porosity, Southwest Regional Partnership on Carbon Sequestration
Basal Cambrian - GIS raster layers

Basal Cambrian project GIS files were created based on outputs from the project’s geologic model. These files represent generalized characteristics of the Cambro-Ordovician Saline System (COSS) and are influenced by the model’s grid cell size, and, as a result, these data layers should not be used as an absolute value at any particular location. 

Within the basal Cambrian geodatabase are eight raster layers representing various geologic properties for the COSS derived from geologic modeling efforts. These include isopach, structure top, measured depth, permeability, porosity, pressure, TDS, and temperature. Values are generally in imperial units.

Tags: Basal Cambrian, GIS, PCOR, Phase III, rasters
Comprehensive GOM Federal Waters Platform, Incident, Metocean, and Geohazard Dataset

The dataset contains integrated data from an array of disparate data sources, all spatially and temporally linked to platforms in the federal waters of the Gulf of Mexico (platform data from BSEE, 2020). Integrated data includes past reported incidents dating back to 1956 (BSEE, BOEM, MMS), metocean data (see Nelson et al. in review for source information), and geohazard data (see Nelson et al. in review for source information). Proprietary well production information was redacted from this dataset, but was used in resulting analytics.

Tags: Full System, Geohazard, Geospatial Infrastructure, Incidents, Metocean, Offshore, Platform
Supplementary data for Technical Report: Towards A Geo-Data Science Method for Assessing Rare-Earth Element Occurrences in Coal and Other Sedimentary Systems

Supplementary data includes two appendices:

-Appendix A: Bibliography of references that helped inform development of the REE-SED assessment method. 

-Appendix B: Sample data template. 

Tags: Coal, Geo-data, REE, Rare Earth Elements, TRS