Selected Work
Selected Work
Case studies demonstrating measurable impact
We partner with engineering-led organizations to deliver AI enabled physical systems that produce real results. Here are examples of our work across energy, automotive, and advanced manufacturing.
Case Studies
Real projects with measurable outcomes
Turning Real-Time Intelligence into Lower Costs
Physics‑Informed AI Digital Twins for Real‑Time Drilling Optimization
Energy | Edge AI | Digital Twins
Non-productive time, drilling dysfunctions, and conservative operating practices are among the largest drivers of avoidable drilling cost. InEarth Ventures developed a physics-informed AI digital twin that operates in real time at the rig edge, continuously optimizing drilling parameters as conditions evolve. By combining fast, physics-based time-domain models with machine learning, the system enabled proactive control of drilling behavior reducing NPT, improving rate of penetration, and lowering total well cost across multiple deployments.
Reducing Product Risk and Lifecycle Uncertainty
Advancing the Failure Prediction of Hyperelastic and Viscoelastic Materials
Automotive | Materials Engineering | Simulation
Material-driven failures are among the most expensive and difficult problems to diagnose in product development often surfacing late through testing, warranty claims, or field failures. InEarth Ventures developed a validated material modeling framework for hyperelastic and viscoelastic materials that enables reliable prediction of deformation, durability, and failure under real operating conditions. The result is higher confidence in design decisions, reduced physical testing burden, and improved product reliability before release to market.
Protecting Uptime and Reducing Costly Downhole Failures
Improving Reliability of Drilling Mud Motors
Advanced Design | FEA | Simulation
Mud motor failures drive significant non-productive time, unplanned trips, and tool replacement costs, directly impacting well economics and operational predictability. InEarth Ventures developed predictive modeling capabilities that accurately captured mud motor power section behavior under real downhole conditions. By identifying failure mechanisms before deployment, the work enabled improved reliability, longer tool life, and reduced risk of costly downhole failures.
Flush Efficiency - Multiphase Flow
Advancing Multiphase Modeling and Improving Flushing Efficiency
Multiphase | CFD | Optimization
Water efficiency regulations and consumer performance expectations place competing demands on modern toilet design. InEarth Ventures developed and validated a high-fidelity multiphase modeling framework that enabled manufacturers to reduce water usage while preserving or improving flushing performance. By replacing trial-and-error testing with predictive simulation, the work reduced development cost, shortened design cycles, and supported compliant, high-performing product launches.
Mitigate Flow-Induced Erosion
Reducing Erosion and Improving Product Reliability
Erosion | CFD | Design Optimization
Premature erosion-driven failures directly impact product reliability, warranty exposure, and customer trust, often forcing costly redesigns or field replacements. InEarth Ventures applied advanced flow and erosion modeling to identify root-cause erosion mechanisms early, enabling targeted design and material optimizations that significantly extended product life, reduced failure risk, and lowered total lifecycle cost before physical testing or field deployment.
Short Casing Collapse Ratings
Bridging the Gap Between API Collapse Calculations and Real-World Performance
Performance | FEA | Simulation
Conservative design standards can unintentionally limit product performance, delay qualification, and restrict access to higher-value applications. InEarth Ventures partnered with a leading oilfield service provider to accurately predict true collapse limits of short casing components. By replacing overly conservative API calculations with validated physics-based models, the engagement enabled higher pressure ratings, reduced testing requirements, and unlocked new deployment opportunities directly improving time-to-market and product competitiveness.
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