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- Formation evaluation to define shale volume, mineralogy, effective porosity, saturation and permeability using deterministic or probabilistic models
- conventional clastic and carbonate reservoirs
- unconventional and organic rich reservoirs
- fractured reservoirs
- helium gas reservoirs
- carbon dioxide sequestration (CCS) wells
- underground source of drinking water (USDW) well evaluation
- injection / disposal wells
- geothermal wells
- lithium extraction from formation water
- oil sand reservoirs
- Log normalization
- double point and single point normalization procedures to remedy spurious log data
- normalization parameters are mapped to determine if log variation is due to geology or log calibration / environmental factors
- Log editing
- correct off depth logs
- remove NULL values over short intervals
- baseline shifting
- multiple linear regression to remedy logs over bad borehole intervals
- hand editing when other approaches are not possible
- Saturation-height modelling for reservoir description using capillary pressure curves
- convert laboratory data to reservoir fluid system and relate to rock types
- allows saturation to be calculated independent of the resistivity log
- Log blocking between layers defined by inflection points
- improves the accuracy of mechanical rock property models
- eliminates / minimizes shoulder bed effects
- Design and manage core programs
- routine core analysis
- special core analysis
- Nuclear magnetic resonance (NMR) data
- use DLIS NMR data to run custom T2 cutoffs to determine moveable fluid volumes
- Mechanical rock properties from reconstructed sonic and density logs
- bulk modulus
- shear modulus
- dynamic Young’s modulus
- static Young’s modulus
- Poisson’s ratio
- vertical Biot’s factor
- Transverse isotropic mechanical rock properties using ANNIE or MANNIE models
- vertical and horizontal values for Young’s modulus and Poisson’s ratio are determined
- Overburden stress calculation
- based on a full summation (integration) of the corrected bulk density log from surface to target depth
- Closure stress (minimum principal stress)
- use calculated overburden stress, mechanical rock properties and field data to determine a calibrated closure stress for target intervals
- Machine learning and deep learning petrophysical techniques
- supervised and unsupervised rock type classification
- unbalanced sampling algorithms to eliminate bias
- probabilistic data analysis to help predict rock type or missing logs
- Build 3D geologic grids with Petrel software for reservoir simulation
- Petrophysical results are used to build 3D geologic grids which are then upscaled for input to reservoir simulation software packages
- Petrophysical mentoring
- Aptian will get you up and running with your petrophysical software
- Software development
- PowerLog and PRIZM proprietary software module design and implementation
- purpose-built crossplots to solve common petrophysical problems
