Automated Author ProfileCARVALHO, BRUNO R.
CARVALHO, BRUNO R.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.1 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The marine Controlled-Source Electromagnetic (mCSEM) method provides complementary information to seismic imaging in the exploration of sedimentary basins. The mCSEM can be used to help in subsalt structural imaging, but mainly for reservoir scanning and appraisal as EM methods are especially sensible to the fluid content within the rocks.The mCSEM interpretation workflow is heavily based on inversion and forward--modeling for hypothesis testing. Until the recent past, the effectiveness of a given interpretation workflow was achieved after the drilling results, as there wasn't any geological complex model available to serve as a benchmark.The Society of Exploration Geophysics (SEG) recognized that gap and launched the SEAM (SEG Advanced Modeling)-Phase I project aiming to advance the geophysical science through the construction of a multi-physics subsurface model and generation of an associated dataset.SEAM Phase-I, a representation of the deepwater Gulf of Mexico salt domain, was designed to take as much realism and geological complexity as possible. Following the success of that first model, SEG launched SEAM Phase-II focused on the solution of land seismic challenges like near-surface complexities and fractured reservoirs.In the present publication, we will also describe the workflow to build Marlim--R3D, a realistic and complex geoelectric model. Marlim-R3D aims to be a reference model for mcSEM modeling and inversion studies of turbidite reservoirs of the Brazilian continental margin. Our model is based on previous seismic interpretation and constrained by the input of available well-log information.The workflow used is composed of seven sequential steps: seismic and well-log dataset loading, well-tie, Vp (P-wave velocity) cube construction, Vp-resistivity calibration, time-depth conversion, resistivity cube construction, Quality-control check.As a result, we obtained an interpreted dataset composed by main stratigraphic horizons, pseudo-well logs, and the resistivity cubes. These elements will be freely available for research or commercial use, under the Creative Common License.Files Description : Depth horizons: *xyz extension (Upper Oligocene, Upper Miocene, Sea Bottom, Top of Marlim Reservoir, Top and Base of the Salt)Pseudo Wells: *.LAS extension (extrated properties from modelling) ------- *.track extensions (well track)3D Cubes: *sgy Horizontal & Vertical Resistivity (Calculated resistivity from modelling - horizontal and vertical anisotropy) Log(RESH) & Log(RESV) files are the resistivity cubes but in common logarithmic scale
Authors
- CARVALHO, BRUNO R. ;
- MENEZES, PAULO T. L.