Petrophysical Data QC & Preprocessing

Depth Matching

Ensures accurate correlation between well logs, petrophysical measurements, and seismic data:

Alignment of well log depths with seismic and formation tops
Time–depth and depth–depth calibration using checkshots or VSP
Correction for KB vs. DRL vs. log reference depths
Supports reliable reservoir property modeling and seismic tie

Environmental Corrections

Removes acquisition- and environment-related artifacts from well and petrophysical data:

Temperature, pressure, and borehole environmental corrections
Compensation for tool drift, sensor offsets, and borehole conditions
Standardization of log units and calibration across wells
Ensures consistent and comparable petrophysical measurements

Identification of Bad Data

Detection and handling of invalid, noisy, or inconsistent petrophysical measurements:

Outlier detection and removal in logs and core data
Flagging of missing, noisy, or non-representative measurements
Verification of tool responses and quality of derived properties
Provides clean datasets for rock physics modeling, inversion, and reservoir characterization

Petrophysical Modeling & Reservoir Characterization

Cross-Plot Techniques

Enables robust identification of lithological and fluid variations in the reservoir. Quantitative analysis of well logs to differentiate lithology and fluid properties:

Multi-parameter cross-plots (e.g., Vp/Vs vs. density, AI vs. SI)
Lithology and fluid discrimination
Detection of anomalies and facies trends
Input for rock physics and seismic inversion calibration

Multi-Mineral Models

Provides high-resolution understanding of reservoir composition for seismic tie and quantitative interpretation. Detailed estimation of mineral composition and volumetrics from petrophysical data:

Construction of volumetric fractions of quartz, clay, carbonate, and other minerals
Integration of density, neutron, sonic, and resistivity logs
Support for rock physics template generation and elastic modeling
Calibration against core and laboratory data

Zonation

Supports consistent reservoir characterization and targeted development planning. Subdivision of the reservoir into meaningful stratigraphic or petrophysical units:

Layer-based or property-driven zonation
Integration of log trends, core data, and seismic markers
Identification of productive, non-productive, or transition zones
Input for volumetric estimation, facies mapping, and reservoir modeling

Shale Volume Estimation & Petrophysical Analysis

Shale Volume (Vsh) Estimation

Quantitative assessment of clay and shale content in the reservoir:

Determination of shale fraction from well logs
Support for lithology classification, porosity, and permeability estimation
Integration with rock physics models and seismic inversion

Single-Log Methods

Shale volume estimation using individual petrophysical logs:

Gamma-ray, density, neutron, or sonic log analysis
Simple and fast evaluation of clay content
Useful for preliminary petrophysical interpretation and facies identification
Calibration with core or other logs for accuracy

Multi-Log Methods

Integrated approach combining multiple logs for improved accuracy:

Cross-plot and multi-log regression techniques
Simultaneous analysis of gamma-ray, density, neutron, and sonic logs
Enhanced lithology discrimination and shale correction
Supports reliable input for rock physics modeling, inversion, and zonation

Porosity Determination & Reservoir Characterization

Density–Neutron–Sonic Log Analysis

Multi-log integration for accurate porosity estimation:

Cross-validation of density, neutron, and sonic logs
Determination of total, effective, and clay-corrected porosity
Identification of porosity trends and heterogeneity
Calibration with rock physics models for seismic inversion and reservoir modeling

Nuclear Magnetic Resonance (NMR)

Advanced porosity and fluid typing using NMR measurements:

Total and effective porosity determination
Fluid typing (bound vs. free fluids) and movable hydrocarbon estimation
T2 distribution analysis for pore-size and permeability insights
Integration with conventional logs for robust reservoir evaluation

Integration with Core Data

High-fidelity calibration and validation of log-derived porosity:

Core–log cross-plots for porosity and lithology verification
Correction of log-scale biases and environmental effects
Establishes a reliable link between well measurements and seismic properties
Supports accurate input for inversion, petrophysical modeling, and reservoir simulation

Fluid Saturation & Reservoir Evaluation

Archie’s Equation

Quantitative estimation of water and hydrocarbon saturation in clean formations:

Determination of water saturation (Sw) using resistivity and porosity logs
Calibration of formation factor and saturation exponent
Integration with lithology and porosity models
Supports volumetric calculations and hydrocarbon-in-place estimation

Shaly-Sand Models

Fluid saturation analysis in clay-bearing reservoirs:

Simultaneous consideration of shale content and resistivity response
Models include Waxman–Smits, Simandoux, and Dual Water approaches
Improved Sw estimation in shaly sands for accurate hydrocarbon quantification
Integration with log-derived shale volume and porosity

Capillary Pressure Methods

Reservoir fluid distribution and relative permeability assessment:

Analysis of laboratory core capillary pressure measurements
Estimation of residual oil and water saturations
Integration with log-derived Sw profiles and facies mapping
Supports reservoir modeling, flow simulation, and recovery prediction

Permeability Determination & Reservoir Flow Characterization

Empirical Correlations

Estimation of permeability from conventional well logs:

Cross-plots of porosity, water saturation, and lithology
Established empirical models (e.g., Timur, Coates, Wyllie–Rose)
Rapid permeability assessment across the reservoir
Supports initial reservoir modeling and simulation inputs

Flow Zone Indicator / Hydraulic Flow Units

Classification of reservoir intervals based on flow capacity:

Integration of porosity, permeability, and lithology trends
Identification of high- and low-permeability zones
Hydraulic flow units (HFU) for consistent reservoir modeling
Supports zonal production analysis and well placement

NMR Logs

Advanced permeability and flow characterization using NMR data:

Pore-size distribution analysis (T2 distributions)
Calculation of effective and movable fluid volumes
Estimation of permeability via NMR-based models (e.g., Timur-Coates)
Integration with porosity and facies data for high-resolution flow modeling