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Key Oil & Gas Engagements
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Subsurface Data Analytics - UDA 
We have designed a SAP HANA certified solution called “Upstream Data Analyzer (UDA)” – which helps in instant visualization as well as predictive analysis of logs from Oil & Gas upstream operations.
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  • On-demand, predictive and agile data-to-insights (d2i) platform 
  • Solution can be plugged in as part of Digital Oil Field (DOF) strategy for an upstream oil & gas firm
  • Combines both structured and unstructured data sources
  • Uses prediction models for sub-surface characteristics, drilling plans, production, etc. 
  • Supports application of AI/ML algorithms for NPT reduction strategies
  • SAP HANA is used as the primary database for on-demand queries for processed data and predictive analysis
  • Flexibility to be deployed on clients’ private cloud as well as access at the offshore project sites. 

Refer our Case Studies section to download the case study on 
"Reduce your NPT using Upstream Data Analyzer (UDA)
Drilling Logs Management  - DrillNet 
We have developed a “Driller’s Data Network (DrillNet)”  to address the need for real-time dashboards for drilling consoles for mud, pump, drill assembly, well integrity and pit/tank monitoring. 
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  • Handles real-time sub-surface data from drilling operations
  • Allows real-time as well batch wise visualization as well as analytics - time/depth perspective
  • Manages multiple monitoring dashboards - visibility to well parameters, such as mud properties, pump and casing pressure, etc. 
  • Combined data-to-insights process managing WITS, WITSML and LAS sources 
  • Private/Public cloud as available deployment options 
  • Solution can be plugged in as part of Digital Oil Field (DOF) strategy 
  • Ready implementation framework to perform advanced drilling data 

Refer our Case Studies section to download the case study on 
"Subsurface Data Analytics for Oil & Gas Operators
Pipeline Incidents Data Analyzer - PDA 
We have designed and developed a "Pipeline Incidents Data Analyzer (PDA)" by applying analytics on incidents data gathered from multiple sources (external as well as internal) that can be applicable to any midstream pipeline operator

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  • Understanding health of pipelines and take necessary action incase of discrepancies from data analyzed from past incidents
  • Other data sources which were considered were pigging/inspections data as well as real-time IoT/sensor data
  • Applying predictive as well as prescriptive analytics in a cognitive platform to understand the correlation and relationship between various reported events
  • Improves pipeline monitoring by analysis of incidents
  • Extension of the design of the system to enable edge analytics ​
Solutions impact on Oil & Gas business areas
  • Improves drilling performance by comparing drilling patterns across wells
  • Enhances local reporting and decision making
  • Enhances real-time analytics at the site level
  • Provides an unified view of data from multiple sources – structured, semi-structured and unstructured
  • Increases predictability of hydrocarbon deposits from test drills data
  • Improves drilling visibility and operations across multiple wells
  • Improves pipeline monitoring by analysis of incidents
  • Monitors and predicts asset integrity across the energy value chain