Baker Hughes Accelerates Product Development with HyperWorks-Driven Simulation

• Analytics & Modeling - Digital Twin / Simulation
• Sensors - Utility Meters

• Cement
• Oil & Gas

• Product Research & Development
• Quality Assurance

• Virtual Prototyping & Product Testing
• Virtual Reality

• System Integration
• Testing & Certification

Baker Hughes, a leading supplier of oilfield services, products, technology, and systems, faced a significant challenge in validating an advanced oil well liner. The company's customers operate in a challenging market, drilling offshore in deep water and arctic regions, perfecting shale and hydraulic fracturing techniques, and consistently complying with strict environmental and safety regulations. They also have to manage technological challenges such as ever-deeper wells, extreme pressures and temperatures, and unconventional geological variations. Product reliability, safety, speed to market, and cost control are all vital to the industry’s success. To remain competitive, oil and gas service companies must ensure that the right products are built reliably and meet customer expectations ahead of those from competitors. The challenge of creating a cost-effective, safe, and reliable expandable liner hanger required the use of simulation throughout the product development process.

Baker Hughes is one of the world’s leading suppliers of oilfield services, products, technology, and systems. The company operates globally with nearly 59,000 employees and is headquartered in Houston, Texas. It recently recorded $21.4 billion in annual revenue from sales of both services and highly innovative products for the world’s oil and natural gas industry. Baker Hughes customers operate in a challenging market, drilling offshore in deep water and arctic regions, perfecting shale and hydraulic fracturing techniques, and consistently complying with strict environmental and safety regulations. They also have to manage technological challenges such as ever-deeper wells, extreme pressures and temperatures, and unconventional geological variations.

Baker Hughes turned to FEA simulation that incorporated HyperWorks computer-aided engineering tools from Altair to capitalize on simulation’s many benefits in the product development cycle. The company relied on a seven-step methodology to verify and validate an expandable liner hanger virtual simulation model. Developers built an FEA model, then verified that model against past experience, judgment, hand calculations, and test data for similar products. The model was refined, if necessary, and an optional reliability assessment step was executed utilizing the design of experiments (DOE) technique, leading to more refinements and optimization that were re-verified. Next, simulation model results were validated against physical prototype test data. Analysts progressed back and forth between steps to build, verify, and validate data until results represented real behavior and produced high-quality correlations with physical prototype tests. Once the validated simulation model was prepared, further design evaluations and performance predictions could be completed with confidence.

• The use of HyperWorks-driven simulation in the product development process led to significant operational benefits for Baker Hughes. The seven-step validation process used by the company achieved a high correlation between the FE model and physical tests, reducing the number of prototypes required and improving system capability. The hanging capacity of the system was improved by 40 percent with optimization of the slip ring design, guided by HyperStudy. The use of simulation in the development of the expandable liner hanger demonstrates the value that simulation brings to innovation, helping meet the world’s energy needs through a virtual process that speeds product to market with higher quality at lower costs.

• Reduced the number of prototypes required by 60 to 70 percent
• Improved the hanging capacity of the system by 40 percent with optimization of the slip ring design
• Achieved a correlation between the FE model and physical tests within +/- 4 percent