Stone Ridge Technology
Assembly Line
Building a generative AI reservoir simulation assistant with Stone Ridge Technology
In the field of reservoir simulation, accurate modeling is paramount for understanding and predicting the behavior of subsurface flow through geological formations. However, the complexities involved in creating, implementing, and optimizing these models often pose significant challenges, even for experienced professionals. Fortunately, the integration of artificial intelligence (AI) and large language models (LLMs) offers a transformative solution to streamline and enhance the reservoir simulation workflow. This post describes our efforts in developing an intelligent simulation assistant powered by Amazon Bedrock, Anthropic’s Claude, and Amazon Titan LLMs, aiming to revolutionize the way reservoir engineers approach simulation tasks.
Although not covered in this architecture, two key elements enhance this workflow significantly and are the topic of future exploration: 1) simulation execution using natural language by orchestration through a generative AI agent, and 2) multimodal generative AI (vision and text) analysis and interpretation of reservoir simulation results such as well production logs and 3D depth slices for pressure and saturation evolution. As future work, automating aspects of our current architecture is being explored using an agentic workflow framework as described in this AWS HPC post.