APG’s workflow for multi-physics, multi-frequency, and multi-scale modeling and inversion
Our experts bring the following technologies to the table and help clients to fully characterize their resource plays:
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Data review and quality control – Log normalization, depth shifting, and project setup – Well log interpretation and well summary calculations
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Rock typing and permeability calculations – Borehole image log interpretations – Resistivity modeling and geosteering post processing
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Production log analysis – Deterministic and probabilistic (Neural Network) methods to predict pseudo logs
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Log-derived geomechanical properties – Rock properties data from well logs
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Diagnosis and modeling of Formation tester measurement and fluid sampling – Pore pressure and fracture gradient analysis
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Python programming and workflow development
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Advanced carbonate formation evaluation using multi-physics modeling and stochastic inversion
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Global optimization to estimate petrophysical properties of shaly sandstones
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Low resistivity pay (LRP) zone detection using model-based and data-driven algorithms
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Detecting and quantifying fractured carbonates using conventional logs (Without core, FMI, UBI)
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Retrieving petrophysical properties (TOC, frackability, etc.) of unconventional resource plays
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Pore pressure and fracture gradient (PPFG) prediction using conventional well logs
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Applications of machine learning techniques in well log processing and interpretation
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Bayesian rock typing using well logs calibrated with core data
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Joint inversion of NMR and other well logs to simultaneously estimate petrophysical properties
The philosophy behind APG’s stochastic multi-physics inversion
Rock typing
Dual porosity carbonate: stochastic well log inversion
