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Development of an Automated Data Collection and Asset Management System for Oil & Gas Operations
  1. case
  2. Development of an Automated Data Collection and Asset Management System for Oil & Gas Operations

Development of an Automated Data Collection and Asset Management System for Oil & Gas Operations

capitalnumbers.com
Energy & natural resources
Supply Chain
Logistics

Identifying Operational Inefficiencies in Oil & Gas Workflow Management

Disjointed and time-consuming processes across oil well operations and asset management result in operational inefficiencies. Manual data entry at field sites causes delays and duplicate records, hindering real-time monitoring and decision-making. The client requires an automated, responsive system for real-time data capture, workflow visibility, and asset tracking to enhance operational efficiency.

About the Client

A large-scale energy company specializing in upstream, midstream, and downstream oil and gas operations seeking to optimize workflow monitoring and asset management.

Goals for Automating Data Collection and Asset Monitoring in Oil & Gas Operations

  • Implement a responsive web application to enable real-time data entry and reporting from field personnel.
  • Eliminate manual data entry delays by digitizing workflows related to oil well locations, properties, and asset management.
  • Enhance operational transparency by providing instant access to updated data on drilling sites, assets, and personnel routes.
  • Improve decision-making capabilities with integrated business intelligence and reporting tools.
  • Achieve faster data retrieval through optimized caching and security via robust authorization protocols.
  • Streamline pumper route planning and reduce equipment idle time to increase efficiency.

Core Functional Specifications for Real-Time Oil & Gas Data Management System

  • User management system to maintain and monitor personnel profiles and activity statuses.
  • Geographical search capabilities for locating oil wells by regions and specific locations.
  • Asset management module covering oil tanks, reservoirs, wells, and drilling sites with insights into operational status.
  • Route planning and pumper management to optimize field personnel movement and reduce downtime.
  • Real-time data capture from field devices, including drilling parameters, tank status, and production metrics.
  • Instant reporting features with integrated business intelligence tools for analytics and decision support.
  • Secure login and multi-level authorization to protect sensitive operational data.
  • Responsive design ensuring usability across devices and locations.

Technology Stack and Architectural Preferences for the Data Management System

Web application built using a robust backend framework (e.g., Laravel or equivalent).
Frontend developed with HTML and CSS for responsive design.
Caching mechanisms to optimize quick data retrieval.
Security protocols implementing strong authorization and user access control.
Integration of business intelligence tools for real-time reporting.

Essential External and Internal System Integrations

  • External data sources such as field sensors or devices for real-time data capture.
  • Business intelligence or reporting tools for analytics and visualization.
  • Asset management systems or databases for inventory and equipment tracking.

Non-Functional System Requirements for Performance and Security

  • High availability with system uptime of at least 99.9%.
  • Fast data retrieval with caching to ensure instantaneous report generation.
  • Secure authentication and authorization protocols to prevent unauthorized data access.
  • Scalability to support increasing data volume and user load as operations expand.
  • Responsive user interface adaptable to various devices and field tablets.

Expected Business Benefits from the Automated Data and Asset Management System

The implementation of this system is projected to significantly improve operational efficiency by reducing manual data entry delays, enabling real-time monitoring and decision-making, leading to faster response times and optimized resource utilization. It aims to eliminate discrepancies caused by manual updates, enhance transparency across locations, and enable smarter asset management. Expected key impacts include faster data access, improved accuracy, and reduced operational downtime, resulting in measurable productivity gains in oilfield operations.

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