The makeSENSE project aims to advance reservoir modeling by integrating ensemble-based data assimilation with exact sensitivity calculations, enhancing decision-making, and optimizing resource use.
Norway is committed to reducing oil and gas emissions by 50% by 2030 and achieving near-zero emissions by 2050. The makeSENSE project provides an enabling solution by improving reservoir management efficiency while minimizing environmental impact.
While widely used, traditional ensemble methods struggle with nonlinear models and fail to fully capture multimodal uncertainty distributions. The makeSENSE project overcomes these limitations by incorporating adjoint-based sensitivity analysis and automatic differentiation (AD) in the reservoir modeling tool, enabling precise uncertainty quantification and improved optimization. These innovations will enhance energy efficiency, lower emissions, and support sustainable field development.
The project will develop fully differentiable workflows, leveraging machine learning and hybrid sensitivity approaches to improve computational efficiency without sacrificing accuracy. It will integrate the technology into industry-standard tools such as OPM Flow, ERT, and Everest, ensuring real-world applicability and seamless adoption. By validating these methods in operational environments, makeSENSE will accelerate technology transfer and adoption in the industry.
Expected impacts include improved reservoir forecasting, optimized production strategies, and significant emission reductions. The project strengthens Norway’s leadership in computational geoscience, promoting open collaboration between industry, academia, and software communities. The makeSENSE project sets a new standard for sustainable subsurface resource management, balancing economic value with environmental responsibility.
