Sold by: Xecta Digital Labs
Deployed on AWS
We provide automated production optimization Opportunities for every well, daily. They result in increased investment-free barrels or cost reductions, covering wells from natural flow, through any type of artificial lift type, to abandonment.
Overview
Xecta leverages modern grade data infrastructure in the cloud, historized rate-pressure information from 100s of sensors in the field, setting up highly distributed and continuously streaming analytical models and workloads.
Autonomous well-twins compute pressure evolution and downhole pressure for all wells and reconstruct entire history from free-flow to artificial lift. Our solution provides continuous calibration of well-twins to live incoming sensory data with self-driving models using recursive learning procs
Highlights
- We provide companies with actionable and timely insights that remove the uncertainty surrounding asset and well optimization
Details
Sold by
Delivery method
Deployed on AWS
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Dimension | Description | Cost/12 months |
|---|---|---|
Small asset | less than 500 wells | $200,000.00 |
Medium asset | more than 500 up to 1,000 wells | $500,000.00 |
Large assets | more than 1,000 wells up to 3,000 wells | $1,000,000.00 |
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Delivery details
Software as a Service (SaaS)
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Updated weekly
By Xecta Digital Labs
By Cirrus Link
By MeghaAI RAIN
Top
100
In Analytic Platforms
Top
10
In Device Connectivity, ML Solutions, Big Data
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In Industrial IoT
AI generated from product descriptions
Real-time Sensor Data Integration
Processes historized rate-pressure information from hundreds of field sensors with continuous streaming analytical models
Digital Twin Technology
Autonomous well-twins compute pressure evolution and downhole pressure for all wells, reconstructing complete operational history from natural flow to artificial lift stages
Continuous Model Calibration
Self-driving models utilize recursive learning processes to continuously calibrate well-twins against live incoming sensory data
Cloud-based Data Infrastructure
Leverages modern cloud-grade data infrastructure for distributed and continuously streaming analytical workloads
Daily Optimization Recommendations
Generates automated production optimization opportunities for individual wells on a daily basis across natural flow, artificial lift, and abandonment scenarios
Data Integration Protocol
Utilizes open standard MQTT Protocol specification for data communication
Operational Technology Data Connectivity
Connects operational technology data from industrial operations to Snowflake data platform
Configuration Complexity
Requires minimal configuration and zero coding for deployment
Data Transformation
Eliminates need for OT protocol conversions and time-consuming data transformation processes
Analytics and Machine Learning Integration
Enables big data analytics and machine learning capabilities on operational data
Digital Twin Technology
Enables creation of a digital twin representation of the plant floor for real-time monitoring and simulation.
Machine Learning Model Deployment
Supports deployment of machine learning models for asset health monitoring and predictive maintenance.
Anomaly Detection and Diagnosis
Implements AI/ML-based anomaly detection, diagnosis, and conditional monitoring capabilities for asset performance analysis.
Real-time Data Visualization
Provides configurable dashboard with real-time data visualization and machine insights display.
Asset Navigation and Management
Includes asset navigator functionality for tracking and managing plant floor assets.
Standard contract
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