It is possible to gain knowledge of the reservoir through the massive and multivariate analysis of the information masked in well logs, maps and dynamic data.
Well logs
- Generation of missing logs.
- Calculation of missing logs in wells due to data loss or non-measurement.
- Special logs calculations from commonly measured logs.
- Vertical analysis of the reservoir:
- Finding similarities
- Identification of different reservoir qualities
- Classification of lithologies
- Sweet Spot Detection
- Opportunity Identification
- Prioritize workovers
- Combining with seismic data
- Porosity and permeability calculation by combining logs and core measurements.
- Calculation of fluid content from cores and tests.
Maps
- Areal analysis of the reservoir based on porosity maps, poral volume, initial saturations, reservoir thicknesses, etc.
- Areal analysis of the reservoir from maps calculated from well logs.
In House Developed Methodology
- Search for similarities / characterization of the reservoir.
- It uses multivariate analysis methodologies.
- It combines clustering techniques and unsupervised learning neural networks.
- The results are validated by more than one algorithm with a % of confidence.
- It can be applied to logs data, maps and production KPIs or completion characteristics.
- It is possible to identify formations tops.
- Allows differentiating reservoir zones from non-reservoir zones within a formation.
- Allows the identification of reservoir qualities within a formation.
Availability
- Web
- Desktop
- Integrated with Sahara software.