Log Visualization
Compare multiple wells, align tracks, and inspect curves at the depth scale your interpretation requires.
PETROSTACKS AI / PLATFORM GUIDE
Subsurface intelligence.
Connected.
Six solution areas. A connected approach to well information, analytical workflows, and engineering review.
SOLUTION 01
Petrophysics
Bring well-log analysis, formation evaluation, and reservoir characterization into a connected interpretation workflow.
Missing Log Prediction
Estimate absent log curves using available measurements from the same well or related wells.
AI Facies Classification
Use log signatures to distinguish lithofacies and compare classifications with geological context.
AI Formation Tops
Identify stratigraphic boundaries and support marker correlation across a group of wells.
AI Parameter Prediction
Estimate properties such as porosity, permeability, and elastic parameters from available log suites.
AI Uncertainty
Examine prediction variability alongside estimated curves to inform engineering review.
Auto Log Splicer
Align overlapping runs and combine them into a continuous, depth-matched log dataset.
AI Histograms
Inspect curve distributions and compare log-property patterns before interpretation.
AI Low Frequency Enhancer
Explore low-frequency enhancement as part of the petrophysical analytical toolset.
INPUTS: LAS · DLIS · ASCII
OUTPUTS: Log curves · Formation markers · Property estimates
SOLUTION 02
Geoscience
Connect seismic interpretation, geomechanical assessment, and rock physics for a more complete subsurface view.
Seismic
Explore seismic signals and subsurface structures in the context of an interpretation project.
Geomechanics
Assess rock strength, stress, and wellbore stability with an engineering-led workflow.
Rock Physics
Connect elastic responses and petrophysical properties to strengthen geological interpretation.
INPUTS: Seismic data · Well logs · Rock properties
OUTPUTS: Interpretations · Integrated subsurface views
SOLUTION 03
Production
Combine production history, operating signals, and engineering context to investigate well performance and operational opportunities.
Production Intelligence
Bring operating information into a connected view of asset performance.
Artificial Lift Failure Prediction
Look for changing sensor patterns in lift systems to support earlier investigation of equipment issues.
Production Optimizer
Evaluate the relationships between production, pressure, and operating constraints.
Decline Curve Analysis
Review historical decline trends and compare production forecast scenarios.
Well Performance Monitoring
Follow changes in well behavior and identify patterns that merit attention.
Downtime & Lost Production
Investigate interruptions and relate downtime to its production impact.
Workover Candidate Ranking
Compare candidate wells against operational and performance criteria.
INPUTS: Production history · Operating signals · Well context
OUTPUTS: Forecast scenarios · Performance views · Candidate rankings
SOLUTION 04
CCUS
Use well-log intelligence to examine early-stage geological storage opportunities and identify intervals for further evaluation.
AI Preliminary Screening
Review well logs and reservoir characteristics to help identify potential carbon-storage intervals.
INPUTS: Well logs · Reservoir context
OUTPUTS: Screening intervals · Property summaries
SOLUTION 05
Geothermal
Explore geothermal resource potential by connecting log-derived properties and geological context.
Geothermal Log-Based Screening
Use available well information to investigate reservoir conditions relevant to geothermal resource assessment.
INPUTS: Well logs · Geological context
OUTPUTS: Resource screening · Candidate intervals
SOLUTION 06
AI Digitization
Turn scanned reports and raster well logs into structured information that can be reviewed, analyzed, and reused.
Document OCR
Extract text, tables, and header information from scanned technical documents.
Document Intelligence
Ask questions, summarize findings, and compare information across a collection of reports.
Well Log Digitizer
Detect curves, align depth scales, and prepare digital log traces from raster scans.
INPUTS: TIFF · PDF · JPG · PNG · BMP
OUTPUTS: LAS · Structured tables · PDF · Word · Excel
Technical characteristics
Well-log formats
Workflows reference LAS, DLIS, and ASCII well information, with depth and curve context retained for interpretation.
Document & image inputs
Digitization workflows cover TIFF, PDF, JPG, PNG, and BMP source material.
Curve extraction & alignment
Grid detection, scale calibration, multi-curve extraction, and depth matching support the transition from raster logs to digital curves.
Prediction & uncertainty
Log completion, property estimation, and classification are reviewed alongside the uncertainty and geological context of the result.
Retrieval-based intelligence
Document question-answering connects a question with retrieved material rather than removing the answer from its source context.
Interoperable outputs
Reviewed information can move into LAS curves, structured tables, and document-oriented outputs such as PDF, Word, and Excel.
Capability descriptions adapted from Drake AI's published feature catalogue for this PetroStacks AI website review. Illustrations and reference examples are not PetroStacks AI client results. Availability and delivery scope are subject to confirmation.