OriGenAI

OriGenAI, founded in 2018 by Ruben Rodriguez Torrado, operates with the mission to address critical inefficiencies within the oil and gas exploration and production sector. The company is headquartered in New York and maintains a core engineering and development office in Madrid. The firm targets the persistent challenge where reservoir engineers spend extensive time on simulations, often leading to sub-optimal field development decisions, excess capital expenditure, and reduced production.

The company's core offering is the PROTEUS platform, a cloud-native software-as-a-service (SaaS) solution that leverages physics-informed AI. This platform can accelerate full reservoir simulations by a significant margin—reportedly up to 10,000 times faster than conventional methods. By directly solving the representative differential equations, PROTEUS provides granular data on pressure, saturation, and velocity at every point in the reservoir. The suite includes tools for automated geological model generation, a cloud-based black-oil simulator, and physics-informed neural networks (PINN) that deliver simulation results in formats compatible with commercial simulators. This capability enables rapid, automated history-matching and allows for the analysis of millions of field development scenarios, which can enhance a project's Net Present Value (NPV) by up to 20%.

OriGenAI's business model is based on annual recurring revenue from per-seat licenses for its SaaS platform. It serves major global energy companies and Fortune 500 firms, helping them optimize complex field development projects and manage existing assets more effectively. In November 2020, the company secured $1 million in seed financing led by Wisdom LLP, a venture capital fund, which followed its participation in the Creative Destruction Lab (CDL) accelerator program. This funding was aimed at expanding the company's sales and operational teams.

Keywords: reservoir simulation, oil and gas AI, field development planning, production optimization, physics-informed AI, subsurface modeling, real-time optimization, assisted history matching, petroleum engineering, energy technology, geostatistical modeling, reservoir management, E&P technology, cloud-native simulation, asset optimization, capital expenditure reduction, NPV improvement, energy sector SaaS, generative AI in energy, black-oil simulator