Turn Microseismic Data into Actionable Insights
Bridging the gap between microseismic data and business value using proprietary AI analytics augmented by expert opinion
Increase Return On Microseismic Monitoring Investment
Microseismic data acquisition and processing is time-consuming and expensive; Discover how metaKinetic-AI powered Analytics can help
Automated Data Validation
metaKinetic-AI brings clarification on reliable vs. unreliable microseismic data, giving operators a chance to recognize and mitigate faulty data interpretation.
Completion Optimization
metaKinetic-AI generates insight for operators to implement cost-effective engineered completion programs without sacrificing productive SRV.
Well Performance Analysis
metaKinetic-AI is designed to greatly simplify the access and comparison of disparate datasets to identify the key parameters that yield optimal fracking performance.
Accurate microseismic data for cost-effective operational decisions
DQI™ (Data Quality Intelligence) is metaKinetic AI analytics solution providing accelerated data quality control by leveraging machine learning augmented with expert opinion.
With metaKinetic-DQI, operators can interact with the QC algorithm and visualize results instantaneously to take action as needed.
Intelligent estimation of producing volume for EUR projections
ProSRV™ (Productive SRV) is metaKinetic AI analytics solution to outline a logical estimation of productive stimulated reservoir volume using statistical 4D characterization of rock deformation generated by hydraulic fracturing.
With metaKinetic-ProSRV, operators can interact with the SRV calculations and visualize results quickly to make scientifically sound decisions.
Completion performance comparison for better engineered programs
EPYFFNI™ (epiphany) is metaKinetic AI analytics solution to enable stage-by-stage completion performance comparison by quantification of fracture network connectivity.
With metaKinetic-EPYFFNI, operators can put expensive microseismic moment tensor data into use to image, visualize, and evaluate subsurface fracture network connectivity associated with hydraulic fracturing.
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