Oil & Gas

The operational, financial and environmental risks of system failure; a highly regulated industry and harsh operating conditions offer specific challenges for the systems that are used in the Oil & Gas sector.

MADe is a technology solution that provides the engineering capability to effectively model and analyse the necessary information from a system design to optimise the design process, commissioning and operations of oil and gas platforms.

Importantly, MADe can be effectively applied to meet the requirements of a variety of challenges in the Oil and Gas sector, ranging from unmanned / remote platforms to efficient dispatch regimes and highly iterant and transitional workforces.

Roles

1. Executive level

Cost: optimize / validate the accuracy of economic forecasting for design / support budgets

Process: ensure consistency and traceability of engineering validation for corporate engineering processes

Technical: integrate safety, reliability and supportability engineering analysis tools and data with the enterprise IT architecture (CAD / PLM)

2. Manager level

Cost: automation of analysis in MADe generates significant productivity / schedule improvements for a project and/or team

Process: parallel / concurrent analyses based on a single source of truth (the MADe model) ensures consistency between different functional groups / silos

Technical: leverage GUI based knowledge management on engineering decisions across the program lifecycle

3. Engineer / Analyst level

Cost: enable cost-effective trade studies, automation of analysis in MADe enables engineers to focus on technical decision making rather than data entry

Process: ensure technically validated design / support concepts are generated based on a consistent, extensible analysis framework

Technical: integrated analysis solution ensures data quality & process consistency for analyses

4. Academic (Research)

Cost: model-based simulation and automation of analysis in MADe ensures researchers can focus their efforts on investigation of outcomes rather than data entry

Process: structured model / taxonomy and automation ensures traceability of data used to support research projects

Technical: integrated analysis solution ensures data quality & process consistency for analyses