A regional oil study that utilizes the detailed geochemical analysis of a representative suite of samples is an excellent way of identifying, evaluating and comparing the various petroleum systems that have contributed to the reserves of a large area. All oil samples are analyzed using a sophisticated suite of analyses including determination of physical properties (API and weight percent sulfur), gas chromatography, stable carbon isotopes, and gas chromatography/mass spectrometry. In order to maximize the benefits of this approach, the geochemical results are then integrated within a meaningful geologic framework.
All GSI studies are presented in both analytical and interpretive formats to insure that all findings are accessible to explorationists and research personnel. All geochemical data are provided in electronic format. A synthesis and interpretation of all information is presented in comprehensive final reports. Below are examples of deliverables that are included within a non-exclusive report.
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Greater Campos Oil Wells Location
- Our final report is delivered with separate Access databases for each sample set
– Crude Oils
– Source Rocks
– Piston Cores
- Raw Data Files
- Report Files
- Meta Files
- Mapping Capabilities
- Proprietary Data Browser
The Well Profile provides key information such as:
- Rock Eval
- Source Evaluation
- Maturity Assessment
- Depth/Age Relationship
Crude Oil Summary
The Oil Summary sheets relay important information such as;
- Gas Chromatography
- Compositional Data
- Biomarker Ratios
- Mass Chromatograms
- Interactive – access to raw data files via Peakview
All of this information is linked directly into ArcGis. This program, combined with our information, allows you to overlay such information over a map of the basin that includes the blocks and our sample data coverage.
Cluster Analysis Chart
GSI uses multivariate statistical analysis to group the oils into families based on their geochemical composition. These families help give insight on the origin of the oil. Strict parameters are set before going through this process. We then determine whether the samples should be included or excluded from the sample set.
The crossplots generated based on the data received adds value to the raw data and reinforces the findings from the cluster analysis dendogram. A multitude of components are charted against each other, where important patterns begin to reveal themselves. For example, the scores and loads plots compare principal components to determine where they fit on the lacustrine and marine scale.