Migration and Modernization Journey with bpx Energy

Opportunity and Challenges in Cloud Migration and Modernization

• Customers have various reasons to migrate to AWS:

  • Data center exit and consolidation
  • Going global
  • Mergers and acquisitions
  • Increasing agility and staff productivity
  • Transforming into data-driven organizations
  • Cost reduction (25-50% on average)
  • Improving security and operational resilience
  • Delivering digital transformation and enterprise modernization
  • Responsible corporate citizenship on sustainability
  • Reinvesting cost savings into Gen (generative AI) solutions

• Common challenges in migration and modernization:

  • Cloud operations and security
  • Program management and planning
  • Resource availability (people, money, time)
  • Technical blockers (networking, version incompatibility, system integrations)

• Structured approach to migration and modernization:

  1. Assess readiness
  2. Mobilize through early wins
  3. Migrate and modernize at scale
  4. Continuous optimization

bpx Energy's One Cloud Journey

• About bpx Energy:

  • US onshore oil and gas division of BP
  • Focused on Permian, Eagleford, and Haynesville basins
  • Divested most legacy assets to focus on acquired BHP assets

• Journey Timeline:

  • 2017: Experimented with cloud services and IoT
  • 2019: Serious cloud adoption, dual-cloud strategy
  • 2023: Decided to migrate to a single cloud (One Cloud initiative)

• Drivers for One Cloud:

  • Simplification
  • Increased efficiency
  • Higher pace of innovation and value delivery
  • Preparation for 2030 goals (doubling production without increasing costs/headcount)

• Migration Details:

  • 18-month project, migrated 91 applications and 280 TB of data
  • Migrated SAP first, then ArcGIS, and custom "Well-Connected Portal"
  • Modernized platforms, improved availability, and increased automation

• Lessons Learned:

  • Balance modernization with migration timeline
  • Communicate and coordinate early and often
  • Document everything
  • Beware of unknown dependencies and changes

Gen (Generative AI) Vision and Solution

• Gen Vision and Roadmap:

  • Identify key business goals (e.g., increase production, safety, decrease costs)
  • Assess current technology and data platforms
  • Simplify complexity, build capabilities
  • Develop AI and data strategy, upskill employees
  • Establish governance, security, and risk management
  • Build/acquire AI and Gen solutions, pilot, test, deploy, and scale

• Data Strategy and Considerations:

  • Scalable data lake and purpose-built data services
  • Data integration, transformation, and governance

• Getting Started with Gen:

  • Engage with AWS Solution Architects
  • Leverage AWS Generative AI Innovation Center
  • Utilize AWS Professional Services and Innovation methodology

• Gen Solution Architecture:

  • Question rewriter, router, Python/SQL generators, data-to-text synthesizer
  • Serverless architecture with API Gateway, Lambda, SQS, DynamoDB
  • Leveraging Amazon S3, Textract, Opensearch, and Bedrock (large language models)

• Model Selection Considerations:

  • Balance of accuracy, latency, and cost
  • Experimentation and prompt engineering techniques